mcp-sam-gov

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.12.0
Disambiguation5/5
Each tool targets a distinct data source or operation, with very detailed descriptions that explicitly differentiate overlapping areas (e.g., USAS vs SAM vs Grants.gov). The rare potential confusions (e.g., multiple 'search' tools) are resolved by naming prefixes and contextual descriptions.
Naming Consistency4/5
Tools consistently use a `source_verb_noun` pattern (e.g., usas_search_awards, sam_get_opportunity). Minor deviations exist (e.g., `feedback` vs `api_key_status`), and some verbs vary ('search' vs 'lookup' vs 'get'), but the overall pattern is predictable and domain-grouped.
Tool Count2/5
152 tools is extremely large for a single MCP server, covering a vast range of federal data domains. While each tool serves a distinct purpose, this number may overwhelm agents and suggests the server is trying to be too many things at once.
Completeness4/5
The tool surface is remarkably broad, covering federal spending, procurement, regulations, healthcare, environmental data, and more. Minor gaps exist (e.g., no tools for USDA or Department of Education), but the coverage is impressive for a single server.
Average 4.6/5 across 152 of 152 tools scored. Lowest: 3/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 262 commits in the last 12 weeks
- Last stable release on July 24, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
Tools from this server were used 30 times in the last 30 days.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and openWorldHint. Description adds no behavioral context beyond the example, missing details on pagination or response structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, efficient and front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, limited parameter documentation, and no description of return values. Tool definition feels incomplete for a spending query.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 25% (agency described). Description does not elaborate on any parameters, failing to compensate for low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it retrieves spending by federal account/TAS and gives an example. However, it does not distinguish from siblings like usas_search_agency_spending or usas_search_subagency_spending.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage: 'Use to map money to the actual budget line item.' No explicit when-not or alternatives provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the description does not need to repeat safety traits. It adds the context that spending is aggregated by awarding agency, but does not disclose other behavioral details like pagination or response format. This is adequate given the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no filler. It front-loads the core purpose and provides a concrete example. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and 4 undocumented parameters, the description provides insufficient context for correct invocation. The example only hints at one parameter (NAICS). An agent would need more information on required vs optional params, result format, and typical usage patterns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only mentions 'NAICS' in the example. It does not explain any of the four parameters (limit, naics, setAside, fiscalYear), so the description fails to compensate for the missing schema documentation. The agent must infer parameter meanings from names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns spending broken down by awarding agency and gives a specific example query (NAICS 541512). This distinguishes it from siblings like usas_search_subagency_spending or usas_search_psc_spending, which break down by other dimensions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a concrete use case ('which agencies spend the most on NAICS 541512') and implies this tool is for top-level agency aggregation. It does not explicitly state when not to use it, but the purpose is clear enough for an AI to select it over similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint true and openWorldHint true. The description adds the behavioral trait of surfacing sub-agency budget holders, but it does not go beyond what annotations suggest. No mention of performance, indexing, or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the main purpose. No wasted words. The structure efficiently conveys the tool's function and gives concrete examples.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is complete for a query tool that returns sub-agency spending breakdowns. However, it does not mention whether results are aggregated or list-based, nor does it address pagination or limits. Given no output schema, a bit more detail on what the response contains would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not add meaning beyond the input schema. The schema has detailed description for 'agency' but none for 'fiscalYear'. The description fails to compensate for the missing schema coverage on fiscalYear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: breaking down a parent agency's spending by sub-agency/office. It uses specific verbs and provides examples (VA OI&T vs VHA) that distinguish it from sibling tools like usas_search_agency_spending.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a sub-agency breakdown is needed, but it does not explicitly state when to use this tool versus alternatives or provide exclusions. No direct comparison with sibling tools is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and openWorldHint, so safety and dynamic data are covered. The description adds that it lists 'all' agencies and that slugs are needed for another tool. It does not discuss pagination or the perPage parameter, but overall adds moderate value beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and includes a concrete example. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main purpose and linkage to another tool, but lacks detail on the output format and the perPage parameter. Given no output schema, the agent might need more info about what is returned.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (no descriptions in schema). The description does not mention the only parameter 'perPage', leaving its purpose and usage unexplained. For a single optional parameter, the description should clarify its effect.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists Federal Register agencies with slugs, specifies the verb 'List', the resource 'agencies', and the output 'slugs'. It explicitly distinguishes from siblings like fed_register_search_documents by stating slugs are needed for that tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides good usage guidance: it tells when to use (to get slugs for fed_register_search_documents) and gives an example query. However, it does not explicitly mention when not to use or list alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so description does not need to state it's read-only. The description adds context about output format (spending by program area with dollar amounts) but omits behavioral traits like pagination (limit parameter) or what happens if fiscalYear is omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with an example, perfectly front-loaded. Every word adds value with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description provides a helpful example of the return structure. However, it lacks details on pagination (limit parameter) and the optional fiscalYear default, which would improve completeness for a complex tool with 3 parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 3 parameters with 33% description coverage. The description adds meaning for toptierCode (links to usas_lookup_agency) and implicitly mentions fiscalYear, but does not explain limit or fiscalYear defaults/format. With low schema coverage, more parameter detail in description would be beneficial.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a 'budget function breakdown for an agency × fiscal year' with spending by program area, using a concrete example for VA. This is a specific verb+resource that distinguishes it from sibling tools like usas_get_agency_profile or usas_search_agency_spending.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (when needing spending by budget function) but does not explicitly state when to use this tool versus alternatives like usas_search_agency_spending. No guidance on prerequisites or excluded scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly and openWorld hints. Description adds hierarchy and return field details but does not disclose additional behavioral traits. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states purpose and output, second gives usage example. No wasted words, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with no output schema, description adequately covers purpose, parameter implications, and expected output. Missing some detail on limit and pagination, but sufficient for common use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is low (33%) with only recipientLevel described. Description does not compensate for keyword or limit parameters; it only explains the return value hierarchy. Minimal added value over schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it searches USAspending recipient list with hierarchy detail (parent/child/recipient) and specifies return fields. It distinguishes itself as preliminary step before usas_get_recipient_profile, differentiating from siblings like usas_autocomplete_recipient.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit use case example ('find the recipient_id for Booz Allen') and indicates it should be used before usas_get_recipient_profile. Lacks explicit alternatives or when-not-to-use, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant behavioral context beyond the readOnlyHint and openWorldHint annotations. It explains that data comes directly from spending_by_award, that missing end dates are counted but not dropped, and that a truncation flag appears in _meta. It also notes limitations ('no per-award enrichment'). This is valuable transparency for a read-only tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately concise and front-loaded with the core purpose. However, it includes some technical details ('spending_by_award', '_meta') that could be streamlined. While every sentence adds information, the overall length and density could be slightly reduced without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (12 parameters, no output schema), the description provides substantial context: core logic, filtering, limitations, and behavioral flags. It explains what the tool returns (rows, _meta) and mentions missing end dates. The only minor gap is the lack of explicit output format or example, but the description is still quite complete for effective usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents each parameter well. The description adds value by explaining the window concept (windowStartDays/windowEndDays) and how scanBudgetPages affects results. It also clarifies that setAside is 'honored server-side'. This contextual information enhances understanding beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose using a specific verb ('search recompetes') and describes the resource (federal contracts with ending PoP within a window). It provides a usage example ('what VA 541512 contracts are up for recompete in the next 18 months'), which aids understanding. However, it does not explicitly differentiate from the similar sibling tool 'usas_search_expiring_contracts', which slightly reduces clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear usage example and lists filtering options (agency, naics, pscCodes, etc.). It also states what the tool does NOT cover ('Public signals only — no CPARS/protest/option-intent'), giving implicit guidance on when not to use it. However, it does not explicitly compare with alternatives like 'usas_search_expiring_contracts' or 'usas_search_awards'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, indicating a safe read operation. The description adds context about document types and filters but does not elaborate on behavioral traits such as pagination, rate limits, or the nature of results (e.g., summary vs. full text). Since annotations cover the safety profile, the description adds moderate value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, consisting of two sentences with no redundant information. It front-loads the core action and resource, then provides a usage example. Every sentence adds value, and the structure is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential functionality and provides a concrete use case. Although there is no output schema, the openWorldHint annotation suggests the tool returns results in a standard format. The description does not explain pagination or result details, but for a search tool with 7 parameters, it provides sufficient context for an agent to understand when and how to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 71% (5 of 7 parameters have descriptions). The description reiterates the filter parameters (query, agency, type, date range) but does not add new semantic meaning beyond the schema. The 'perPage' parameter lacks a schema description and is not mentioned in the tool description. With high coverage, baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool's action ('Search Federal Register documents') and specifies the resource types ('proposed rules, final rules, notices, presidential documents'). It lists key filtering criteria (query, agency, type, date range) and provides a concrete example. This clearly distinguishes it from sibling tools, which cover other registries or data sources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes a clear usage context ('Use for regulatory-context queries') and a specific example ('what new VA cybersecurity rules came out this quarter?'). While it does not explicitly mention when not to use the tool, the provided guidance is sufficient for an agent to select this tool over siblings like 'ecfr_search' or 'regulations_search_documents'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and openWorldHint. The description adds valuable behavioral details such as OR-matching for keywords, phrase quoting returning 0, and default statuses. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with purpose and filtering, then provides keyword behavior details. It is somewhat lengthy but each sentence adds value. Could be slightly more concise, but it is well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description could mention what the search results contain (e.g., grant opportunity summaries). It covers filtering and defaults but lacks information on result structure or pagination. The annotations partially compensate with openWorldHint.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67%, setting a baseline of 3. The description adds meaningful nuance for the keyword parameter (OR matching, phrase quoting behavior), but does not elaborate on other parameters beyond what the schema provides. It briefly mentions narrowing with cfda/agency/oppStatuses, which is already implied.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Search' and resource 'Grants.gov federal grant opportunities', and distinguishes from SAM.gov contracts, which is valuable given sibling tools from SAM.gov. It also lists key filtering capabilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides detailed guidance on keyword usage and narrowing with other parameters, and distinguishes from SAM.gov contracts. However, it does not explicitly mention when to use this tool over the sibling grants_get_opportunity or other alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as readOnlyHint=true and openWorldHint=true. The description adds value by specifying the scope (151 terms from USAspending) and giving example queries, which helps the agent understand what behavior to expect beyond the annotation tags.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no superfluous information. It front-loads the core purpose and immediately follows with a practical usage directive, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple glossary tool, the description covers purpose and usage but omits output details and parameter semantics. Given the lack of output schema, the agent might need to guess at the response format, but the simplicity keeps this gap manageable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning no parameter descriptions exist in the schema. The description does not explain what 'limit' or 'search' do, leaving the agent to infer their purpose from context. Only minimal guidance is provided through the overall purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it's a glossary of 151 federal-spending terms and provides specific usage examples like 'what's a TAS?' and 'obligation vs outlay?'. This clearly distinguishes it from sibling tools, none of which serve a glossary purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description tells the agent to use the tool to confirm terminology before answering compliance/budget questions, providing clear context. However, it does not specify when not to use or suggest alternatives, though the sibling list lacks similar tools so confusion is minimal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already state readOnlyHint=true and openWorldHint=true. Description adds value by specifying the output fields (toptier_code, abbreviation, slug, obligations) and the scope (list all toptier agencies). No contradiction; it complements annotations well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, no fluff. The first sentence states the action and output; the second provides usage context. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, output, and usage, but lacks details on default behavior of the optional limit parameter (e.g., no pagination info, default count). Also does not mention data freshness or error handling. Given the simple tool, it's adequate but incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'limit' has 0% schema description coverage; the description does not mention it at all. The description fails to explain what limit does (e.g., maximum number of agencies), which is critical for an agent to use the tool correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'list', the resource 'toptier federal agencies', and the specific data returned (toptier_code, abbreviation, slug, current-FY obligations). Provides concrete use case examples, effectively distinguishing it from sibling tools like usas_get_agency_profile or usas_lookup_agency.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly gives two use cases: listing all cabinet departments with spending and finding a toptier_code for other agency tools. While it doesn't explicitly state when not to use, the examples imply appropriate context. Could mention alternatives but still provides clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and openWorldHint. Description confirms it returns spending data broken by PSC, adding market structure insight. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose and immediate use case. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, description only states returns PSC spending. Could be improved by mentioning data format, sorting, or pagination. Adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 25% (agency has description). Description does not explain limit, naics, or fiscalYear parameters beyond the general purpose. Agent gets little guidance on how to use these parameters correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'Search' and resource 'PSC Spending' with example use case ('what PSC categories see the most $ at DoD') and differentiation from NAICS. Distinguishes from sibling tools like usas_search_awards and usas_search_agency_spending.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides concrete use case ('find spending by PSC categories') and hints at when to use over NAICS-based tools. Lacks explicit when-not-to-use or comparison to other similar tools, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint, so the description adds limited behavioral context beyond specifying the output is plain text. It does not disclose error handling or rate limits, but given the safe read-only nature, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the purpose, and every word provides value. No unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description fully covers purpose, use case, and output type. No additional explanation is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a clear description for noticeId ('32-char hex notice id'). The tool description does not add any additional meaning for the parameter beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool returns the full description/RFP body text as plain text for a notice, and distinguishes from the sibling tool sam_get_opportunity by addressing the case where that tool returns a URL instead of inline body.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use: when sam_get_opportunity returns a URL instead of inline body, or for an LLM-friendly text dump. It implies alternatives and usage scenarios but does not explicitly state when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and openWorldHint. The description adds value by specifying the return of up to 10 fuzzy matches with UEI/DUNS and highlighting anti-hallucination behavior, which are not in annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the purpose and anti-hallucination warning. Every sentence provides essential information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple input schema and no output schema, the description covers the tool's behavior adequately: it mentions fuzzy matches, limits, and UEI/DUNS. It could mention what 'fuzzy' means, but overall sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description does not explain the 'searchText' or 'limit' parameters. It only hints at 'searchText' by context. For a tool with 2 parameters, more explicit parameter description is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Autocomplete' and the resource 'recipient names', and explains the anti-hallucination purpose. It distinguishes itself from siblings like usas_search_recipients by specifying a focused autocomplete function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises using this tool to confirm exact legal names before searching, which is clear guidance on when to use it. However, it does not explicitly state when not to use it (e.g., if you already have the exact name).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. Description adds return field details but no further behavioral traits. Consistent with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-record lookup with no output schema, description fully covers purpose, parameter, and return fields. Adequate for agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with description including example. Description repeats code format and adds parenthetical example, but does not add significant new meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Get' and resource 'agency profile', specifies parameter (toptier code) and return fields. Distinguishes from siblings like usas_lookup_agency which lists agencies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides context for when to use: 'by toptier code (3-4 digits, from usas_lookup_agency)'. Implies prerequisite lookup but lacks explicit alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds value by detailing the returned fields (e.g., M&A history, parent linkage), confirming the read-only nature without contradicting annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the purpose and output. It could be slightly more structured, but it lacks unnecessary fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description adequately lists the key fields returned. For a simple retrieval tool with one parameter, this is sufficient to inform an agent about what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the schema description already provides an example format. The description doesn't add significant new meaning beyond stating the source, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a full recipient profile by recipient_id and lists the specific fields returned (alternate_names, DUNS, UEI, etc.). It distinguishes itself from sibling tools like usas_search_recipients by focusing on a single record detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly mentions that the recipient_id comes from usas_search_recipients, providing a clear prerequisite. While it doesn't list all alternatives, the sibling context and this hint are sufficient for an agent to determine when to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds context about the granularity (state/territory breakdown) and example output format, without contradicting annotations. No additional behavioral traits are disclosed, but the baseline is already covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with a concrete example. It is front-loaded with the core purpose and uses minimal words, earning its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 optional parameters, no output schema, and annotations covering safety and open world, the description provides a clear use case and output format hint. It is sufficient for a search tool but could address more parameter scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 25% (only the 'agency' parameter has a description). The description does not explain 'limit', 'fiscalYear', or 'naics' beyond the example implicit usage. With low coverage, the description should compensate but fails to do so.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides spending broken down by state/territory. It gives a specific example query and answer format, and distinguishes from sibling tools like usas_search_agency_spending (agency-level) and usas_search_subagency_spending.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes an example query ('where is the most federal $ flowing for NAICS 541512') and what answer to expect, providing clear context for when to use this tool. However, it does not explicitly state when not to use or mention alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, openWorldHint), the description discloses that results are ranked by agencyObligated with specific fields, that top candidates are optionally screened via sam_check_exclusions with default debarred exclusion, and that a bogus cert triggers invalid_input. This adds valuable behavioral context beyond what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement, details on ranking and filtering, and a notable honesty section. While somewhat lengthy, every sentence contributes meaning, and it avoids unnecessary fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 11 parameters and no output schema, the description adequately explains the return structure (ranked candidates with specific fields) and error behavior (invalid_input). It also notes meta field details for exclusion screening, making it fairly complete for an AI agent's needs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all 11 parameters. The description adds marginal value by explaining the cert limitation and that subagency requires agency, but the schema already covers the basics. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool is for 'small-business teaming-partner discovery' using specific criteria (certification, NAICS, agency award history), and distinguishes it from sibling tools like usas_search_recipients and usas_search_awards by mentioning the certification-based filtering and integrity screening.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on usage, including that the cert is award-derived (not SBA certification) and instructs users to verify active certification in SAM/SBS before teaming. It implicitly advises against using this tool when actual SBA certification status is needed, though it does not explicitly name alternative tools like sam_lookup_organization.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. The description adds behavioral context beyond annotations by specifying that grantObligations/idvObligations are returned as null (not 0) to avoid misleading implications. This is a meaningful behavioral trait. It also mentions that the exclusion of non-contract types is disclosed in _meta.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured paragraph that front-loads the core purpose, then adds exclusions, behavior, and a usage example. It is relatively concise at ~100 words. Minor parenthetical aside about _meta adds a bit of density but is relevant.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the tool's output (time-series rollups), key parameters, null behavior, and gives a usage pattern. Given there is no output schema, this is fairly complete. It could mention whether grouping is required or optional, or note any pagination or result limits, but the core functionality is well-described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides a usage example that demonstrates how to use agency ('VA') and NAICS ('541512') parameters, adding context beyond the schema. However, with 0% schema description coverage, the description does not fully explain each parameter's format or constraints (e.g., agency is a string but no example of valid codes, NAICS as a string but no length). It lists the group enum options but doesn't elaborate on them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the purpose as 'Time-series aggregation of federal CONTRACT spending' and explicitly excludes non-contract award types (grants, IDVs, loans), distinguishing it from siblings like usas_search_agency_spending or grants_search. It uses a specific verb ('aggregate') and resource ('federal contract spending').
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a concrete usage example ('how has VA 541512 contract spending trended over the past 5 years') and explains what it returns. It implies when not to use by excluding grants/IDVs/loans. However, it does not explicitly name alternative sibling tools for those excluded types beyond noting that it matches 'other usas_search_*_spending tools'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Extensive disclosure beyond annotations: explains exact behavior of totalAvailable, ASSET normalization (null vs 0), error handling (throws, not fake empties), multi-word token matching, and point-in-time snapshot. No contradiction with readOnlyHint/openWorldHint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is informative but lengthy and dense, with a single-paragraph structure that may overwhelm. The 'HONESTY' section adds value but reduces conciseness. Could be more structured with bullet points.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 9 parameters, no output schema, and only readOnlyHint/openWorldHint annotations, the description is remarkably complete: covers return format, pagination, null handling, error behavior, and even the underlying API's key scheme (CERT). Leaves no major gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds critical nuance: distinguishes case-sensitive 'filters' from full-text 'search' for name/city, explains sortBy is allowlisted and rejected before fetch, and specifies default/limits for limit/offset. Adds significant value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches the FDIC-insured institution directory for due diligence, using specific verb and resource. It does not explicitly differentiate from sibling FDIC tools like financials or failures, but the context implies a directory search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides detailed how-to (case-sensitive vs full-text, pagination) but does not explicitly specify when to use this vs alternatives. Implicitly positioned for bank due-diligence but lacks direct comparison to siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and openWorldHint=true, indicating safe read-only behavior. The description adds value by listing specific fields returned (title, abstract, citation, etc.) and noting the raw_text_url for the full body, which helps the agent understand the output without needing an output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the purpose and key return fields, with no unnecessary words. It is front-loaded with the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one parameter, read-only), the description adequately covers the key return fields and the availability of raw text via raw_text_url. No output schema exists, but the listed fields provide sufficient context for an agent to use the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the one parameter 'documentNumber' is described with an example). The description does not add any additional meaning beyond the schema's description of the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Fetch full detail for a Federal Register document by number', using a specific verb ('Fetch') and resource ('document'). It distinguishes from siblings like 'fed_register_search_documents' which lists documents, and 'fed_register_public_inspection' which shows pending documents.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (when full details of a specific document are needed) by listing the return fields. However, it does not explicitly state when not to use it or mention alternatives like 'fed_register_search_documents' for searching.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint and openWorldHint annotations, the description discloses extensive behavior: complete results (no pagination), honest empty returns, boolean preservation for crash/fire, numeric coercion, error handling for various HTTP statuses, input validation patterns, fixed host, and intentional VIN exclusion. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but well-structured, starting with purpose, then input, output, privacy, honesty, and errors. Each sentence adds value, though it could be slightly trimmed without losing clarity. Front-loaded with core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description provides a detailed specification of return fields (odiNumber, manufacturer, component, etc.) and data types (booleans, numbers, strings). Also covers error conditions and validation, making it complete for a complex tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all 3 parameters fully with regex patterns. The description adds examples ('honda', 'accord', '2020') and reiterates requirements, but does not introduce new semantic meaning beyond the schema. Baseline 3 is appropriate given 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Look up NHTSA consumer COMPLAINTS for a specific vehicle', clearly stating the verb and resource. It specifies owner-filed safety complaints and distinguishes from recalls implicitly by focusing on complaints.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions 'KEYLESS — no API key is required or accepted' which is a feature but does not explicitly guide when to use this tool over alternatives like nhtsa_recalls. The usage context is clear but lacks explicit when-not or alternative tool mentions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. Description adds value by noting keyless access, 50-result limit, active notices, and listed fields, which are behavioral traits not in annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences front-load purpose and key constraints (keyless, 50 results, up to date). No redundant or irrelevant words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has 7 parameters and no output schema. Description covers essential return info (fields, limit, active status) and filtering hints. Lacks mention of pagination (offset) but schema covers it. Adequate for basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 86% (6/7 params have descriptions). The description mentions narrowing by NAICS/agency/set-aside/state, aligning with parameters, but adds little beyond schema details. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches SAM.gov federal contracting opportunities, specifies keyless HAL, return fields (title, agency, NAICS, noticeId), and limits to 50 active notices. This is a specific verb+resource with clear scope, distinguishing it from sibling tools like sam_get_opportunity or sam_search_shaping.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states use for discovery and narrowing by NAICS/agency/set-aside/state. While it doesn't explicitly say when not to use, the guidance is clear and contextually sufficient given sibling variety.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint and openWorldHint annotations, the description adds valuable behavioral details: the tool is 'keyless' (no authentication required), amounts are coerced to number|null with a note that null means 'no value reported' (not zero), and the ordering is newest-first in range mode. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: first identifies the dataset and returned fields, then explains the two modes (latest vs. range), and finally clarifies null handling. Every sentence adds critical information without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the returned fields, the two operation modes, date format, pagination parameters and defaults, and the null coercion behavior. Although there is no output schema, the agent can infer the output structure. It is self-contained enough for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description restates some schema fields (start/end date format) but adds the ordering (newest-first) and the default for latest. This provides marginal added value beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'Daily total US public debt outstanding' from the 'Debt to the Penny' dataset, specifying the exact fields returned (record_date, totalPublicDebtOutstanding, debtHeldByPublic, intragovernmentalHoldings). It distinguishes this tool from siblings like treasury_monthly_statement by focusing on daily data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the two usage modes (latest=true for single most-recent day vs. latest=false with date range) and the parameters involved, but does not explicitly tell the agent when to prefer this tool over alternatives like treasury_monthly_statement or treasury_avg_interest_rates. The usage context is implied but not contrasted.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds behavioral context by stating it returns line items (including naicsCode and description) rather than aggregates, which goes beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. The purpose is stated first, followed by a usage example, then output clarification. Every sentence adds unique value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Considering no output schema, the description adequately describes the output (line items with naicsCode and description) and the main parameters. It could detail what 'line items' includes but is sufficient for an agent to reason about the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaning to parameters like recipientName, agency, naics, and fiscalYear through the example and context, but does not fully document all parameters (e.g., limit is only implied). The description provides intermediate value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: pulling every contract a specific recipient has won within an agency×NAICS slice. It gives a concrete example ('show me Booz Allen wins at VA last year') and distinguishes from aggregates by noting it returns line items, not aggregates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear use case with a specific user query example. It implies when to use this tool (for recipient-specific slices) but does not explicitly exclude other cases or compare to sibling tools like 'usas_search_awards' or 'usas_search_individual_awards'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint, so the description's job is lighter. It adds value by specifying the grant scope (award types 02-05) and clarifying that this tool covers CFDA programs, not contracts. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four clear sentences that immediately convey purpose, use case, and limitations. Every sentence adds essential information with no redundancy, making it highly concise and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description gives sufficient context for a simple search tool, covering purpose and domain differentiation. However, it does not describe the output structure (e.g., list of spending amounts by CFDA code) or how the parameters affect results. For a 3-parameter tool without output schema, this is adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With only 33% schema description coverage (only agency has a description), the tool description should compensate but does not. The description mentions 'CFDA grant program code' but does not explain how parameters like limit, agency, or fiscalYear relate to that. No parameter-level guidance is provided beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides spending data broken down by CFDA grant program code, with the specific use case 'top federal grant programs by $'. It further distinguishes from sibling tools by noting that CFDA covers grants (award types 02-05) not contracts, and explicitly recommends usas_search_psc_spending for contract analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool ('Use for grant analysis') and when not to ('not contracts'), providing a direct alternative: 'Use usas_search_psc_spending for contract market analysis.' This gives clear context for choosing among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and openWorldHint=true, so no destructive actions and data from external source. Description adds that results are line-item level with a generatedInternalId for follow-up, which is useful context beyond annotations. Could mention potential issues like data freshness or pagination, but not required.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences with no wasted words. Front-loaded with the core purpose, then usage guidance, then follow-up capability. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the description gives clear purpose and usage hints, it lacks details on parameter semantics, response format (beyond listed fields), pagination, or any limitations. For a 5-parameter search tool with no output schema, more complete guidance on how to craft effective searches would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 20% (only agency parameter described). The description does not explain how to use parameters like limit, naics, setAside, fiscalYear, or their impact on results. It mentions output fields but not parameter selection, failing to compensate for low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns line-item federal contracts (specific awards) with detailed fields (recipient, $, sub-agency, state, description), and distinguishes it from the sibling tool usas_search_awards by stating to use it after that tool when the user wants actual contracts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly guides the agent to use this tool AFTER usas_search_awards for detailed contracts, and indicates follow-up with usas_get_award_detail using the generatedInternalId. Provides clear when-to-use and alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint and openWorldHint, but the description greatly expands with details on result.total behavior, total_was_estimated flag, empty vs error handling, SSRF host guard, and value typing. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long and packed with detail, but some content is verbose and technical (e.g., 'keyless; the FIRST source on the R2 DataSource port'). It could be condensed without losing essential information. Front-loading is somewhat present with the main purpose stated first.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description explains result.total and totalIsEstimated, but does not fully specify the return structure beyond value typing. It covers error cases, pagination, and limitations. Almost complete but missing explicit output field list.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds significant meaning beyond descriptions: explains q as full-text, filters as structured object with JSON.stringify, limit cap, offset default, sort error behavior, host enum details, and resourceId format. Every parameter benefits.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it queries rows from an allowlisted CKAN datastore resource, specifying the host and resourceId constraints, and ties to sibling ckan_discover_datasets. It distinctively focuses on CKAN government data portals, differentiating from siblings like socrata_query or cms_query_dataset.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for querying government CKAN data but does not explicitly state when to use vs alternatives. It mentions 'keyless; the FIRST source on the R2 DataSource port', which is not helpful for an agent. No clear when-not-to-use or alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, which cover the safety profile. The description adds that the tool returns names and last_amended_on dates, providing modest context beyond the annotations, but no additional behavioral traits like rate limits or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that front-load the purpose and efficiently convey the value. Every word earns its place, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description explicitly states the return fields (name and last_amended_on). For a simple list-all tool, this is sufficient context. The tool's behavior is straightforward and the description covers the essentials.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema coverage. Baseline for no parameters is 4, and the description does not need to add parameter details. It correctly omits any parameter explanations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List'), resource ('all 50 CFR titles'), and includes the data fields returned (name + last_amended_on date). It clearly distinguishes from sibling tools like ecfr_search and ecfr_get_section by focusing on listing titles rather than searching within them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use to discover what's in each title' and provides examples, indicating the tool is for initial exploration. It does not explicitly state when not to use it, but the context excludes the need for deeper search, which is handled by siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and openWorldHint. The description adds behavioral details such as the same JSON:API envelope, return shape with fields, pagination ceiling (40 pages / 10,000 records), and that totalElements is exact. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently conveys the purpose, input shape, output shape, and important constraints (ceiling, totalElements). Every part adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description explicitly lists the return fields and meta structure, including the pagination limit. This is sufficient for an agent to understand what the tool returns and how to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds minimal new info: it notes that 'query' is an alias for 'searchTerm' and mentions the sort set is 'live-verified' and 'non-exhaustive'. However, most parameter details are already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as searching Regulations.gov public comments, using specific verb 'Search', resource 'COMMENTS', and distinguishes from sibling 'regulations_search_documents' by noting it's the same input shape but for comments. It also states 'killer B2G dataset', providing context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions that the input shape is the same as 'regulations_search_documents', implying a differentiation from that sibling, and notes the endpoint '/v4/comments'. However, it does not explicitly state when to use this tool versus alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. The description adds the critical behavior of returning a 303 redirect to a signed S3 URL, and instructs how to follow it. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-load the purpose and immediately provide essential behavioral guidance. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (one parameter, no output schema), the description fully addresses purpose, behavior, and usage instruction. It explains the redirect and gives a practical fetch hint.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with a description for resourceId. The tool description does not add any extra meaning beyond the schema's explanation of where the resource ID comes from.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Build' and the resource 'public download URL for an attachment resourceId'. It distinguishes from sibling tools like sam_fetch_attachment_text and sam_get_opportunity which handle content retrieval or data display.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the redirect behavior and advises 'redirect:'follow' to get file bytes', providing clear usage context. It does not explicitly state when not to use or name alternatives, but the purpose is self-contained.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. Description adds detail on what is returned (title, POCs, attachments, etc.) and the action is clearly read-only. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first covers purpose and return fields, second covers when to use. Front-loaded with verb and resource. No superfluous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple get-by-ID tool, description covers input format, output fields, and usage context. No output schema, but list of returned fields is sufficient. Agent can correctly select and invoke.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter noticeId is described both in the schema and the description as '32-char hex notice id'. Schema coverage is 100%, so description adds no new semantic beyond what schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch' and the resource 'full detail for a single SAM.gov notice', listing key fields returned. It distinguishes from sibling search tools (e.g., sam_search_opportunities) by specifying it is for a single notice by ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states 'Call BEFORE drafting bid/no-bid or compliance work', providing clear usage context. Does not explicitly exclude alternatives, but the command is strong enough to guide selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and openWorldHint=true. The description adds valuable behavioral details: it always returns parseConfidence, supports three format options, distinguishes SCA vs DBA, and resolves latest revision via /history. This goes beyond what annotations provide, though it does not cover edge cases like invalid references.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a concise paragraph of three sentences, front-loaded with the main purpose. Every sentence adds value: parsing context, SCA/DBA distinction, parseConfidence, format options, and revision resolution. No redundant or unnecessary content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, but the description provides a high-level picture of what is returned (rate table, parseConfidence, SCA vs DBA). It also explains how to handle low-confidence parsing via raw output. However, it lacks detail on the exact structure of the parsed rates and error handling for invalid references. Overall, it is sufficiently complete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds substantial meaning beyond the schema. It explains the effect of omitting revision (resolves latest active revision), provides real-world examples for reference (e.g., '2015-4093'), clarifies the default for format ('parsed'), and advises when to use raw format (low parseConfidence).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Return' and clearly identifies the resource: 'prevailing-wage + fringe/H&W rate table for a specific wage determination'. It also distinguishes key subtypes (SCA vs DBA) and mentions features like parseConfidence and format options, making it highly specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage guidance for parameters (e.g., omitting revision resolves latest active revision, using raw format when confidence is low) but does not explicitly state when to use this tool versus sibling tools like sam_search_wage_determinations or gsa_benchmark_labor_rates. The usage context is implied but lacks exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true and openWorldHint=true, so no destructive behavior. The description adds that it is a thin backward-compatible alias and returns the legacy { contracts, searchedCount } shape, which is useful context beyond annotations. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, extremely concise, with the deprecation warning front-loaded. No unnecessary information; every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a deprecated alias tool, the description covers deprecation, recommendation, legacy return shape, and basic functionality. It does not detail all parameters or output fully, but given the tool's limited role, it is sufficiently complete with the sibling tool handling new use cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 5 parameters with 0% description coverage. The description only hints at agency, NAICS, and monthsUntilExpiry via usage context, but does not explain limit, minAwardValue, or provide any specific parameter details. Inadequate compensation for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a deprecated alias for usas_search_recompetes, explains it finds contracts by agency and NAICS expiring within N months, and distinguishes it from the recommended sibling tool by noting the legacy return shape.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states 'DEPRECATED — use usas_search_recompetes' and advises new callers to use usas_search_recompetes for full controls and truthful metadata, providing clear when-to-use (backward compatibility) and when-not-to-use (new callers) guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true and openWorldHint=true, which are consistent. The description adds behavioral context: the tool returns rows with specific fields (subRecipient, amount, actionDate, prime award id, NAICS), and it notes that there is no prime-name filter due to the view's structure. This goes beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (3-4 sentences) and front-loaded: it starts with the main purpose, then provides a usage example, a critical note about limitations, and finally lists return fields. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, no output schema), the description provides good context: purpose, usage, return fields, and limitations. It does not explain pagination or the limit parameter behavior, but for a search tool this is acceptable. No output schema means return fields are covered in the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only explains the subRecipientName parameter in detail, leaving limit, naics, agency, and fiscalYear unmentioned. While parameter names are somewhat self-explanatory, the description does not add enough value for all parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool enumerates federal subawards with optional filtering by subrecipient name, and provides a concrete example ('where does Leidos appear as a SUBcontractor'). It distinguishes itself from sibling tools like usas_search_awards and usas_get_award_detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool (to find subs under a prime by subrecipient name) and when not to (to find subs under a specific prime, use other tools). It provides a clear workflow: 'resolve that prime's awards first (usas_search_awards -> usas_get_award_detail) and read their sub network.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description extensively discloses behavioral traits beyond the annotations: return format including found, nctId, study with briefSummary, and _meta; error handling for 404 (found:false, study:null, never fabricated); honesty about leadSponsor.name being free text and nominal matching; plus warnings about schema_drift and outage behavior. This is highly transparent and informative for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with the purpose front-loaded. It covers parameter details, return structure, error cases, and caveats in a logical order. While slightly verbose due to extensive caveats, every sentence adds value and the conciseness is acceptable for the level of detail needed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully describes the return structure (found, nctId, study, _meta) and error handling. It also addresses edge cases (nonexistent ID, schema drift, outage) and provides honesty notes. For a simple get-by-ID tool, this is comprehensive and leaves no critical gaps for agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers the nctId parameter with a detailed description (format, validation, return behavior). The description adds the URL path and restates some of the same information but does not provide substantial new meaning beyond what the schema already conveys. With 100% schema coverage, the baseline is 3, and the description adds only marginal value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'Fetch ONE clinical study by its NCT id' which clearly specifies the action (fetch) and the resource (clinical study by ID). It distinguishes from sibling tools like clinicaltrials_search_studies by focusing on a single known study. The verb-resource combination is precise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving a single study by NCT ID but does not explicitly state when to prefer this over alternatives like clinicaltrials_search_studies. It provides clear context about ID format validation and injection safety, but lacks an explicit when-to-use or when-not-to-use statement. Baseline 4 for clear context without exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and openWorldHint. The description adds useful behavioral context: it returns a ranked EXCERPT (not full text), section path, and ecfrUrl. It does not contradict annotations and provides additional details about the output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the main purpose, and each sentence adds value. No filler or tautology.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains the return structure (excerpt, section path, ecfrUrl). It also links to sibling tools for next steps. However, it does not mention pagination or perPage behavior, which is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 33% (only titleNumber has a description). The description adds value by explaining titleNumber usage with examples (48 for FAR, 2 for financial assistance), but for query and perPage it provides no additional meaning beyond the schema's property definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Full-text search across the entire CFR' with specific examples (titleNumber=48 for FAR, titleNumber=2 for financial assistance). It distinguishes itself from sibling tools like far_clause_lookup and ecfr_get_section by emphasizing it returns excerpts for discovery.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use for DISCOVERY' and provides clear instructions for what to do after getting a hit: use far_clause_lookup for FAR/DFARS clauses, ecfr_get_section for other titles, or open the ecfrUrl. This gives excellent guidance on when to use this tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, openWorldHint), the description adds critical behavioral details: missing concepts are omitted (never 0), and concepts available only in non-default units are reported under wrongUnit with a note. Also notes keyless access.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose and key parameters, then edge-case behaviors. No redundant information, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers inputs, defaults, and edge cases well. Missing explicit description of output structure (though openWorldHint implies flexible response). With no output schema, a brief note on return format would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by listing the default 6 curated concepts and explaining edge cases for unit mismatches and absent concepts, which are not in the schema. This goes beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides curated XBRL financial facts for a filer, specifying the data source (data.sec.gov companyfacts) and key parameters. It distinguishes from sibling tools like edgar_company_concept (single concept) and edgar_xbrl_frames (aggregated frames) by focusing on multiple concepts with defaults.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving multiple financial facts with optional customization, but does not explicitly compare to sibling tools like edgar_company_concept or edgar_company_filings. No guidance on when not to use it or prerequisites, leaving the agent to infer use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description extensively discloses behavioral traits beyond annotations: keyless operation, honest _meta with exact count from separate sub-query, offset/limit pagination with hasMore, normalization of 'closed' field, null-never-empty-string for addresses/names, error handling for 4xx/5xx, and schema drift. It also clarifies that results are nominal TRI reporters, not compliance determinations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is lengthy but well-structured with clear sections and symbols (★) highlighting key information. Each sentence adds value, though it could be slightly more concise. It is appropriately front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of the tool (5 parameters, no output schema), the description is remarkably complete. It covers input requirements, output format, pagination, error handling, honesty guarantees, and limitations. It fully compensates for the lack of an output schema by explicitly describing the return shape.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already has 100% description coverage for all 5 parameters, so the baseline is 3. The description adds some extra context (e.g., validation for state, path-injection guard for facilityName) but does not significantly extend meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Look up EPA Toxics Release Inventory (TRI) reporting facilities by state / facility-name / county — an environmental-footprint / place-of-performance screen'. It specifies the verb, resource, and filtering criteria, distinguishing it from sibling tools that cover other data domains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidelines: 'provide at least state OR facilityName (an all-empty query is refused); optional limit (1–100, default 25), offset'. It also details error handling and pagination. However, it does not explicitly compare to sibling tools or state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes far beyond the readOnlyHint and openWorldHint annotations. It discloses the exact return envelope structure, normalization of financial fields (ASSET/DEP/NETINC in $thousands to USD), the honesty about totalAvailable being exact, error handling (only works if meta.total > 0, otherwise throws), and snapshot build time. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: purpose first, then parameter details, return envelope, and honesty notes. Every sentence adds value, and there is no fluff. It is concise yet comprehensive for the complexity of the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of an output schema, the description does a good job explaining the return shape (cert, financials array with specific fields) and providing an example. It covers pagination, sorting, error handling, and the data source. It is nearly complete, though it could explicitly mention the date format or other potential edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with good descriptions for all 5 parameters. The description adds minor value by restating defaults, specifying the source of cert (fdic_search_institutions), and clarifying the meaning of the default sortOrder (newest quarter first). However, it does not add substantial new semantics beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns quarterly financial time-series for one FDIC-insured institution by certificate number. It distinguishes this from sibling FDIC tools like search_institutions, bank_failures, industry_summary, etc., by specifying it is for a single institution and the data source is the FDIC BankFind API.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that the 'cert' parameter is required and comes from fdic_search_institutions, and provides pagination and sorting defaults. While it does not explicitly state when not to use this tool versus siblings, the context of the description (financials for one institution) combined with sibling tool names makes the use case clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and openWorldHint. Description adds honest details about $inlinecount behavior, null handling, and error throwing, which are beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with purpose, parameter details, and honesty section. Front-loaded but slightly verbose in spots; still efficient for the information provided.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all necessary aspects: pagination, filtering, error handling, output expectations. No output schema but description compensates fully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. Description adds disambiguation for state vs sibling but introduces contradiction: says 'NOT the 2-letter code' while schema says it accepts both and maps. Slightly confusing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Search', resource 'FEMA Hazard Mitigation Assistance projects', and explicitly distinguishes from sibling tool fema_search_public_assistance for disaster-recovery spend.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use for disaster-resilience grants (HMGP/FMA/PDM/BRIC) and contrasts with recovery-focused sibling. Also notes state parameter difference from sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the 'readOnlyHint' and 'openWorldHint' annotations, the description reveals critical behaviors: the structure of the 'agency' object (sourcing real agency from agencyDetails, not raw agencyName), the handling of nonexistent ids (returning found:false), and the fact that Grants.gov returns hollow 200s which the tool detects. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately lengthy but well-structured: core purpose first, then field list, then a detailed note about agency, then error behavior. Every sentence adds value, though minor redundancy could be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description thoroughly details return fields (including nested objects), edge cases (null agency name, nonexistent ids), and error handling. It provides complete context for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage and only one parameter, the schema already describes it as 'Grants.gov opportunity id (numeric string)'. The description adds no new parameter semantics beyond that, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Fetch full detail for a single grant opportunity by id', clearly stating the verb, resource, and scope. It distinguishes from sibling tools like 'grants_search' and 'sam_get_opportunity' by emphasizing the single-id detail retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool (to get full detail by id) and explicitly explains the behavior for nonexistent ids ('never a fabricated grant'). While it does not list alternatives, the sibling list and the tool's specificity make usage clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds extensive behavioral details: honesty policy (nulls never empty strings), error handling (404 returns empty, 400 returns invalid_input, 5xx throws, 200 non-JSON schema_drift), pagination (skip/limit, nextOffset), auth (optional key explanation, rate limits), and injection safety. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is comprehensive but lengthy, with multiple paragraphs and details about error handling and auth that could be more succinct. While well-structured and front-loaded, it could be trimmed by about 30% without losing essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (8 parameters, no output schema), the description fully explains all filter parameters, return format (listing exact field names), pagination, error handling, and auth. It leaves no gaps in understanding how to invoke and interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds significant meaning beyond the schema: it explains the mapping from parameter names to openFDA field names (e.g., deviceName → device_name), validation rules (state regex, limit range), and how filters are safely assembled into Lucene search strings. This helps the agent use parameters correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it searches openFDA 510(k) device clearances, with specific verb 'Search' and resource 'device clearances'. It details the data source and fields returned, making the purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus siblings like openfda_enforcement or openfda_drug_approvals. The description focuses on how to use filters but does not provide decision criteria or exclusions, which leaves the agent without clear alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, openWorldHint), the description discloses API key requirements and rate limits, behavior on bad IDs (invalid_input, 0 fetch), nonexistent IDs (not_found), and the possibility of null RIN. It also explains the return structure and meta fields. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose and includes organized sections (HONESTY, error handling). It is fairly long but all details are relevant. Could be slightly trimmed without losing information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema, the description thoroughly covers return fields, error cases, authentication, and cross-tool join context. It leaves no major gaps in understanding what the tool does and how to interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage with a detailed description for docketId. The tool description adds an example and validation info, but this is marginal additional value beyond the schema. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch' and the resource 'ONE Regulations.gov docket by id', specifying the endpoint '/v4/dockets/{docketId}'. It highlights that the detail view contains the 'rin' field. This differentiates it from sibling tools like regulations_search_dockets which would be used for searching or listing dockets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the tool's purpose for fetching a single docket and provides cross-source join context for 'rin'. It mentions API key rate limits and error handling. However, it does not explicitly state when to use this tool over alternatives like regulations_search_dockets.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the anti-hallucination behavior and avoidance of code invention, adding context beyond annotations (readOnlyHint, openWorldHint). No contradiction; the description complements annotations effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose and guard, no extraneous text. Efficient and effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple autocomplete tool with no output schema and few parameters, the description covers purpose, usage, and behavioral traits. Lacks explicit mention of output format or limit behavior, but these are minor omissions given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain parameters 'searchText' and 'limit'. The example implies 'searchText' is the free-text query, but 'limit' is unmentioned. This is a significant gap for a tool with 2 parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Autocomplete NAICS codes by free-text', specifying the verb (autocomplete), resource (NAICS codes), and context (free-text input). It distinguishes from sibling tools like 'usas_naics_hierarchy' by emphasizing conversion of themes to codes, preventing hallucination.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to call 'when the user mentions a NAICS theme but no specific code' and warns against inventing codes. Provides an example and frames it as an 'ANTI-HALLUCINATION GUARD', giving clear when-to-use and when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and openWorldHint, but the description adds extensive behavioral details: honesty about null geographies for non-US points, coordinate finiteness check, vintage handling with alternates, GEOIDs as strings, moving vintage warnings, and mandatory caveats. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is thorough but somewhat verbose, with sections like 'HONESTY:' that could be integrated more concisely. It is front-loaded with the purpose, which is good, but could be tighter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (6 parameters, no output schema), the description is very complete. It covers edge cases (offshore, historical vintage, bad benchmark), mandatory caveats, and explains the return structure with geographies keys.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, baseline 3. The description adds value by explaining the x/y aliases, giving examples, and clarifying benchmark/vintage compatibility and defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool resolves a longitude/latitude point to Census geographies, and distinguishes itself from address-based geocoding (sibling census_geocode_address). The verb 'resolve' and resource 'Census GEOGRAPHIES' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says 'no address parsing' and 'for a caller that already holds coordinates', indicating when to use. However, it does not explicitly compare to alternatives or state when not to use, though the implication is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description extensively discloses behavior beyond annotations: caching, honesty in field values, failure mode (throws on catalog errors, no fake-empty), and the persistent caveat. This adds significant value beyond readOnlyHint and openWorldHint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is verbose (multiple paragraphs with details about failure modes and honesty). While informative, it could be more concise. The key purpose is front-loaded, but the length exceeds what is strictly necessary for typical usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is remarkably complete given the tool's complexity: it details all 8 optional parameters, describes the response structure (including fields and caveat), failure modes, and the open-world assumption. No gaps remain for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema coverage is 100%, the description adds meaningful elaboration: explains cveId returns found:false with caveat, dueBefore as CISA deadline, and other filters' behavior. This provides extra clarity beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool filters the CISA KEV catalog, distinguishing it from general CVE lookups. It specifies the resource (KEV catalog), action (filter), and unique characteristics (keyless, cached, separate host from NVD).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit context: use when checking KEV membership, works without NVD key, and includes the critical caveat that absence from KEV does not imply safety. It doesn't list alternative tools but implies full CVEs via sibling names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds extensive behavioral details: honest pagination with totalAvailable from count, coalescing of column names across four datasets, handling of missing fields (null, never empty string), error responses (no-match → empty, invalid input → invalid_input, 4xx/5xx behavior), server-side AND filtering, and keyless access. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is quite verbose (multiple paragraphs with technical details like URL path behavior and column coalescing). While well-structured and front-loaded with core purpose, it could be more concise for quick scanning. Every sentence adds value, but length may hinder readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multi-dataset, pagination, coalescing), the description is remarkably complete. It covers return format, honest pagination, error handling, field behavior, and keyless access. No output schema exists, so the description compensates fully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. The description adds value beyond schema: provides counts for each facilityType enum, explains that the value selects a dataset id via constant map, describes state validation regex, and clarifies facilityName as case-insensitive substring match. This enhances parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to look up Medicare/Medicaid-certified healthcare facilities by type, returning name, address, city, state, zip, and ownership. It distinguishes itself from siblings by noting it generalizes cms_hospital_compare beyond hospitals.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit input requirements (facilityType required, optional state, facilityName, size, offset) and states that it is a facility directory, not a clinical-quality tool. It hints at alternatives by mentioning it generalizes cms_hospital_compare, but does not explicitly contrast with sibling tools like nppes_lookup_provider.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and openWorldHint=true. The description adds valuable context: it specifies the exact API endpoint, the requirement for an API key, the return structure ('{ bill:{…} } + single-record _meta'), and that nonexistent bills result in 'not_found' without fabrication. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences. First sentence states the core action and endpoint. Second lists the parameters. Third describes the return shape and error behavior. No unnecessary words, front-loaded, and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 required params, no output schema), the description covers everything needed: what it does, how to call it, parameter names, return structure, error case, and auth requirement. It is fully sufficient for an AI agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema covers all parameters with full descriptions (enum values for billType, examples for congress and billNumber). Description restates parameter types and connects them to the URL pattern, but does not add new semantics beyond the schema. Baseline score for 100% coverage is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Fetch ONE Congress.gov bill by id via /v3/bill/{congress}/{billType}/{billNumber}'. It specifies the action (Fetch), the resource (Congress.gov bill), and the exact endpoint. This distinguishes it from sibling tools like congress_search_bills, which is for searching.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions the API key requirement ('DATA_GOV_API_KEY or DEMO_KEY') and the error behavior for nonexistent bills. It does not explicitly state when to use this vs. alternatives, but the context of fetching by ID vs. searching in congress_search_bills is clear. No exclusions or when-not-to-use are given, but it's sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description provides extensive behavioral details: CVSS metrics handling, KEV honesty with caveats, pagination from NVD's exact totalResults, error handling for rate limits and HTTP errors, and API key usage. Annotations give readOnlyHint and openWorldHint, and the description adds significant context without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very long (multiple paragraphs) and covers many details. It is front-loaded with the main purpose, but the verbosity impacts conciseness. For a complex tool, it is acceptable, but could be more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is extremely complete: it explains input parameters, output structure (including nested objects), error states, rate limiting, and honesty policies. No output schema is provided, but the description compensates fully. It covers all necessary aspects for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds extra context beyond schema: validation details (cveId format, date pairing, max pages), edge cases (kevOnly throwing on KEV catalog failure, over-cap refused, date span clamping), and honesty policies. This adds meaningful value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool does CVE lookup via cveId or search parameters, with KEV join. It is specific about the resource (NIST NVD CVE records) and the verb (look up/search). The sibling tools are in completely different domains (USAS, SAM, etc.), so this tool is clearly distinguished.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions the tool is for FedRAMP/CMMC/SBOM IT-compliance and includes CVSS severity and CISA KEV status. It does not explicitly say when NOT to use it or list alternatives, but given the sibling tools are unrelated, the usage context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds result format and 'found:false' behavior, but annotations already provide readOnlyHint. No additional behavioral context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise two-sentence description plus a note. No unnecessary words, front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Completely describes tool behavior, including output limit, match details, and key relationship to sibling tools. No output schema needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds examples (e.g., 'AAPL') and clarifies case-insensitivity and substring matching, adding meaningful context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it resolves ticker/name to CIK via SEC company_tickers.json. Distinguishes from siblings by noting CIK is join key for edgar_company_filings/facts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly notes EDGAR keys on CIK not SAM UEI/DUNS, with no authoritative join, guiding when to use vs. other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description is extremely transparent beyond annotations. It details the POST method, error handling (invalid_input, schema_drift), caps, exact totals, and honesty about unreachable records. Annotations (readOnlyHint, openWorldHint) are simple, and the description adds significant behavioral context without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is verbose but well-structured, using sections, examples, and warnings. Every sentence adds value. It could be slightly shorter, but given the complexity (5 parameters, no output schema), the length is justified. It is not excessively wordy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is highly complete for a tool with no output schema. It describes the return structure, error conditions, and edge cases (empty results, outages, drift). Parameter count and complexity are high, but every aspect is covered, including honesty notes. No missing information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds substantial value beyond parameter names and types. It explains case sensitivity for orgStates, the cap and behavior for limit/offset, and live-conformation for all filters. This helps an agent understand proper usage and edge cases.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool searches awarded NIH RePORTER research-grant projects. It specifies the API and data nature, but does not explicitly contrast with sibling tools. However, the unique focus on NIH grants makes it distinct among the listed siblings, which are primarily USASpending and other federal tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides detailed usage guidelines, including constraints (offset cap, keyless retrieval), warnings about agencyIcCodes being omitted, and notes on data nature (grants vs contracts). It does not explicitly say when not to use this tool, but the limitations serve as implicit guidance. More explicit alternative references would improve it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description extensively discloses behavior beyond annotations: non-existent id returns found:false, never fabricated records; type handling of monetary fields; error conditions like serviceNotification and schema drift. This adds significant value over the readOnlyHint and openWorldHint annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is lengthy and includes many verbose details (e.g., about NSF award nature, type conversions). Although each piece adds value, the overall length could be reduced for better conciseness without losing essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool and lack of output schema, the description fully covers input, expected behavior, error cases, and return shape. It addresses all necessary aspects for an AI agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description reinforces the schema's description of awardId with additional details on digit length and validation. While not entirely new, it provides helpful elaboration that aids correct usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Fetch ONE NSF award by its numeric award id', specifying the exact resource and action. It distinguishes itself from sibling 'nsf_search_awards' by emphasizing 'ONE' and the specific numeric id format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context, including input validation (all-digit, 5-9 digits) and the data nature (research grants vs. contracts). However, it lacks explicit guidance on when not to use this tool or direct alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description provides extensive behavioral context beyond annotations: it is read-only (keyless GET), returns only active non-internal portals, filters client-side, uses anonymous endpoints, handles errors by throwing, and detects schema drift. It complements the readOnlyHint and openWorldHint annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose and is well-structured, covering filtering, output, usage with sibling, and honesty notes. Each sentence adds value, but it is relatively long and could be slightly more concise without losing essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description compensates for the lack of an output schema by detailing the output structure (fields like code, name, city, state, website) and behavior of _meta and totalAvailable. It also covers error handling. However, it does not fully specify the _meta object fields besides pagination, and 'schema_drift' is mentioned but not defined.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers all 4 parameters (100% coverage), so baseline is 3. The description adds semantics: explains client-side filtering for state and query, limit range 1..200, offset 0-based, and that totalAvailable is the exact filtered count. This extra context raises the score to 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List the government portals on OpenGov Procurement' and specifies the resource (directory for opengov_search_solicitations). It distinguishes from sibling tools by mentioning it provides the code needed for opengov_search_solicitations and by describing the client-side filtering behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool: to list active government portals, optionally filtered by state, query, limit, and offset. It notes the client-side filtering and the output format. However, it lacks explicit guidance on when not to use this tool or direct comparison with similar sibling tools like bonfire_list_organizations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true and openWorldHint=true, so safety is clear. The description adds behavioral context about the output format (fullParentPathName with example). No contradictions. A minor gap: it doesn't mention behavior on invalid IDs, but given low complexity and annotations, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, one for purpose and one for usage. It is front-loaded and concise with zero wasted words. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one required parameter, no output schema), the description is complete. It explains what input is needed, what output to expect, and when to use it. No gaps for an agent to misuse.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameter is well-defined in the schema. The description does not add additional meaning beyond what the schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool resolves a SAM.gov federal-organization ID to its canonical fullParentPathName, providing a specific verb and resource. It distinguishes itself from sibling tools like sam_get_opportunity by specifying the use case.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use when sam_get_opportunity returned only an organizationId', providing clear guidance on when to use this tool and an alternative. This is explicit and helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint and openWorldHint. The description adds beyond annotations by detailing memoization (5 min), latest mode behavior (pinned to latest record_date), and that avgInterestRatePercent can be null. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no fluff. First sentence clearly states purpose and output fields. Second sentence explains the two modes and optional filter. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description lists all return fields and their types. It covers both modes, pagination, and filtering. For a read-only query tool with good annotations, this is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for each parameter. The description adds meaning by explaining how latest and range modes work together, that securityType is an exact match on security_type_desc, and the implications of pagination parameters (pageSize, pageNumber) in range mode.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'average interest rate the US Treasury pays by security type/description' and lists the specific fields returned. It distinguishes itself from sibling tools by focusing on a specific Treasury dataset and explaining the 'keyless Treasury Fiscal Data' nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains two usage modes: 'latest' (default) for the most-recent month's breakdown with memoization, and range mode with start/endDate for historical data. It also notes optional securityType filter. While it doesn't explicitly state when not to use this tool, it provides sufficient context for correct usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the agent knows it is a safe read operation. The description adds useful behavioral context: keyless access, raw string values for amounts, null/empty handling, pagination behavior, and the truthful _meta field. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense and informative, covering many aspects in a single paragraph. It front-loads the core purpose and dataset list. Could be slightly more structured (e.g., bullet points for parameters) but remains efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description must cover return values. It does so: 'Returns raw rows plus a truthful `_meta` (totalAvailable = upstream total-count, offset pagination)' and explains that value/amount fields are raw strings with null/empty meaning 'no value'. It also describes error behavior for unknown columns. For a tool with 6 parameters and no output schema, this is comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, but the description adds significant extra meaning: explains that unknown columns in fields cause an upstream HTTP 400 error, provides filter syntax with examples, describes sort prefix '-' for descending, and gives pagination bounds (1..500, 1-based). Dataset enum values are explained in more detail. The description compensates completely for any ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies it is an escape-hatch query over 7 confirmed US Treasury Fiscal Data datasets, listing them explicitly (debt_to_penny, avg_interest_rates, etc.). It distinguishes from sibling tools by noting it covers rates_of_exchange and debt_outstanding without a dedicated tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states 'Choose `dataset` (enum — no free path)' and describes the tool as an escape-hatch for 7 specific datasets. It implicitly guides usage by listing datasets and mentioning that it covers datasets without dedicated tools. No explicit when-not-to-use or alternatives, but the context of sibling tools provides clear differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With readOnlyHint and openWorldHint annotations, description adds output behavior (returns canonical name+code) and implies mapping function. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences with no redundancy. Every part adds value, including the imperative 'ALWAYS call this FIRST'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete for a simple lookup tool with one parameter and no output schema. Covers purpose, usage, and output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear description for searchText. Description provides examples but doesn't add significant new semantic information beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it resolves user-friendly agency references to canonical name and 4-digit code, distinguishing from sibling tools that require canonical names.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to call this FIRST when user uses an abbreviation and explains why other tools need canonical names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes far beyond annotations by detailing null handling (0 stays 0, closed lanes are null), update time freshness, response integrity (throws on errors, no fake empties), and the _meta field. This provides deep behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is lengthy but well-structured with front-loading of the core purpose and subsequent sections for details. Every sentence adds value, though slight trimming could improve conciseness without losing content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of real-time operational data with null handling, client-side filtering, and no output schema, the description is remarkably complete. It explains the data structure, null semantics, error behavior, and metadata, leaving no critical gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already has 100% parameter descriptions. The description adds critical context: filters are applied client-side, no server-side filter, empty string reported in _meta.filtersDropped, and pagination via limit/offset. This adds meaningful semantics beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides live CBP land-border-port wait times for commercial vehicles at US Canadian and Mexican border ports, using specific verbs ('Live wait times') and resource ('CBP land-border-port'). It is unique among siblings, which are unrelated government data tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states it is for freight/logistics situational awareness and notes that passenger lanes are not surfaced. While it does not explicitly state when not to use, it provides clear context about its scope and limitations, guiding appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description disclosed all behavioral traits: pagination with honest count, null handling for ratings and emergency services, error handling (4xx, 5xx, schema drift), server-side filtering, and keyless operation. Annotations only provide readOnlyHint and openWorldHint; the description goes far beyond with concrete details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is lengthy but well-structured: a concise opening sentence, followed by parameter details, return format, honest behaviors, and error handling. It is front-loaded with the core purpose and uses bullet-like formatting for clarity. While it could be slightly trimmed, every sentence adds necessary detail for a complex tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, no output schema but return details described, pagination, null handling), the description is remarkably complete. It covers input constraints, output structure, edge cases, and error conditions, leaving no gap for an agent to misinterpret usage. The absence of an output schema is fully compensated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes all five parameters with detailed descriptions, achieving 100% coverage. The description adds value by clarifying match semantics (EXACT vs. substring), allowed characters, validation rules, and default values, enhancing agent understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool looks up Medicare-certified hospitals by state and/or facility name, detailing the specific fields returned (location, type, ownership, emergency services, star rating). It defines the resource and action precisely, and the scope is well-delineated, making it distinct from sibling CMS tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit constraints: at least one of state or facilityName is required, hospitalType alone is insufficient, and pagination parameters are specified. It does not directly state when not to use the tool or list alternatives, but the constraints are clear enough for effective selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Provides extensive behavioral details beyond annotations: honest totalAvailable from separate query, no key required, pagination behavior, null handling, error responses. Complements readOnlyHint and openWorldHint with concrete specifics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with purpose and source, then detailed sections. Though lengthy, each sentence adds value. Well-structured for quick scanning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all aspects: source, return format, pagination, error handling, data honesty, and use case. No output schema needed; description fully equips agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds meaningful context: explains pagination, notes optionality and safe unfiltered usage, and clarifies exact match for state/lastName.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Search CMS's PUBLIC Revoked Medicare Providers & Suppliers list' with specific fields returned. Distinguishes from siblings by noting it's in the same class as OFAC/SAM-exclusions lists for vetting/due diligence.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'for screening a counterparty before teaming or subcontracting' and notes input is optional with safe unfiltered paging. While it doesn't state when not to use, the context and sibling list make its niche clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant behavioral details beyond readOnlyHint annotation: the DKAN metastore ignores server pagination, applies client-side, throws on errors, and never fabricates empty results. This honesty adds value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is verbose but well-structured, front-loading purpose and return format, then usage, then caveats. It could be slightly more concise but every sentence adds necessary info.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately covers return structure, behavior, edge cases, and links to cms_query_dataset. It also explains the honesty mechanism, making it complete for the task.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters are documented in the input schema (100% coverage). The description adds context about client-side application and the exactness of totalAvailable, enhancing understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool discovers CMS Open Payments datasets on the DKAN metastore, specifies the return format, and distinguishes from cms_query_dataset by explaining how to use results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage guidance, such as feeding datasetId and distribution index to cms_query_dataset, and notes the client-side pagination behavior. However, it lacks explicit when-not-to-use or comparison with other sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint and openWorldHint annotations, the description discloses that totalAvailable is always NULL, pagination is opaque cursor, error cases (429, 5xx, non-JSON) throw specific errors, and the API key is sent only in headers. This provides deep behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but well-structured with clear sections (e.g., HONESTY, error conditions). It is front-loaded with the main purpose. While verbose, the length is justified by the complexity and transparency needs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no output schema, the description thoroughly documents return values, error behaviors, pagination details, and authentication. It covers all necessary context for an agent to use the tool correctly without additional information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds valuable context: for 'query' it confirms the mapping to 'q' and notes that '_q' is ignored; for 'cursor' it explains opaque token usage; for 'organization' it describes slug filtering. This exceeds what the schema alone provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches the data.gov DATASET CATALOG for federal open datasets. It specifies the verb 'search', the resource 'data.gov', and distinguishes it from sibling tools like ckan_discover_datasets by noting it is the replacement for the retired CKAN endpoint.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use this tool (as the successor to the retired CKAN endpoint) and provides context on API key limits (DEMO_KEY vs. dedicated key). It does not explicitly list exclusions, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint and openWorldHint. Description adds substantial behavioral details: PII exclusion, honest handling of totalAvailable and total_amount_expended, error behaviors (e.g., 206 success, non-array throw), and rate limits. Far exceeds annotation-only information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is dense and well-structured with clear sections (PII, HONESTY, etc.), but slightly verbose due to extensive edge-case details. Front-loaded purpose is good.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete coverage for a parameter-rich tool with no output schema. Describes return format, pagination, error behavior, and integration with fac_get_findings. All necessary context for agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions. Description adds value by explaining auditeeUei as primary join key, state code casing, min/max for totalExpended, and default/bound for limit. Slight improvement over schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it searches entity Single Audit summaries from the Federal Audit Clearinghouse for audit-risk vetting. Provides source details and distinguishes from sibling tool fac_get_findings by mentioning how to feed report_id.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly identifies as entry point for subcontractor/teaming risk vetting under 2 CFR 200. Clarifies it is not a debarment/exclusion determination and directs cross-checking with SAM/OFAC. Notes keyless usage and production key. Does not explicitly list alternatives, but context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations include readOnlyHint=true, consistent with description stating 'The server does NOT post anything: it only builds the link; the human submits it.' Description adds critical behavioral details beyond annotations, including privacy warnings and no network call.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is front-loaded with purpose and mechanism, then lists inputs and output. Slightly lengthy but all sentences earn their place. Could be trimmed slightly but remains effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 3-param tool with no output schema, the description is exhaustive. It explains return fields, behavior (no automatic posting), privacy, and instructions. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds value by clarifying defaults (kind default bug), providing examples, and emphasizing privacy concerns for summary. This extra guidance improves usability.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly defines the tool's purpose: 'Report a problem, request a feature, or flag a wrong-looking result for THIS server'. It uses specific verbs and resources, and is distinct from all sibling data-retrieval tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit usage contexts: 'Use when the user reports a bug, says a tool's output looks wrong, or wants a capability this server doesn't have.' Does not explicitly state when not to use or mention alternatives, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint and openWorldHint annotations, the description details the OData query mechanics (always sends $inlinecount=allpages), the meaning of totalAvailable, and genuine empty vs. error handling. It also explains how filters are built and verified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is detailed but well-organized, with sections for filters, pagination, honesty notes, and field-name caveats. It is longer than ideal, but every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 11 parameters, no required fields, and no output schema, the description covers the data source, filter construction, pagination, error handling, and field name nuances. It is comprehensive for an API tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, baseline is 3. The description adds value by explaining the OData filter syntax for each parameter, noting the real field names, and comparing to other tools. It clarifies the meaning of date parameters and boolean filters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool looks up FEMA disaster/emergency declarations by various filters such as state, type, incident, year, or date. It distinguishes itself from sibling tools like fema_search_public_assistance by noting field name differences, and from fema_search_hazard_mitigation by focusing on declarations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context by noting that the state field matches the real field in the dataset, contrasting with other tools. It also mentions the dataset size and filter construction, but does not explicitly state when to use this tool over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description extensively discloses behaviors: key requirement, error types (400, 5xx, 200 non-JSON), pagination details, null handling, honest empty results, and key security (only in query param, not logged). This goes far beyond the readOnlyHint and openWorldHint annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is fairly long but front-loaded with the core purpose. Every sentence adds value, though some repetition (e.g., 'honest' multiple times). Structure is logical and informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description fully documents return structure ({ series: [...] } + _meta), error conditions, pagination, and next steps. It is comprehensive for a search tool with complex API behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaningful context: defaults (25, 1000 max, offset 0), pagination with nextOffset, and example query values. This enhances the parameter understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it discovers FRED economic series by free-text search, listing examples like GDP, CPI, etc., and explicitly references the companion tool fred_series_observations, distinguishing it from siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly requires a FRED_API_KEY, explains the consequence of missing it, and guides users to api_key_status for key requirements. It provides input examples and output usage (feed id to fred_series_observations). However, it does not explicitly exclude alternative tools or usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant behavioral context beyond the 'readOnlyHint' and 'openWorldHint' annotations, including memoization (6h), details on count semantics (null vs 0 for granuleCount), and its role as validator source for search_packages. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loads the purpose, output structure, and usage hints. It packs multiple pieces of information into a single paragraph without redundancy, though it could be slightly more structured for readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no params, no output schema), the description fully covers the output format, memoization, edge cases (null counts), and integration with sibling tools, making it complete for an AI agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters and 100% schema coverage (empty schema), the description correctly adds no parameter details. The baseline for zero-param tools is 4, and the description focuses on output and usage, which is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists the GovInfo collection catalog and distinguishes itself from sibling tools like 'govinfo_search_packages' by noting it is the discovery entry-point that provides collection codes for further searches.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states 'No input' and positions itself as the starting point for using 'govinfo_search_packages', providing clear usage context. However, it does not explicitly list conditions where it should not be used, though its simplicity makes this less necessary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond annotations (readOnlyHint, openWorldHint) by detailing return structure, seasonal variation, null vs 0 handling, error scenarios (429, 5xx, non-JSON), and API key usage. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is verbose but well-structured with clear sections. Every sentence adds necessary detail for correct usage. Could be slightly more concise, but it is not wasteful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description thoroughly explains the return object, including nested fields like monthlyLodgingUsd. It covers error conditions and key management, making it complete for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining why city+state must be together, default fiscal year computation, and validation patterns. It does not repeat schema but provides useful context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool looks up GSA Federal Travel PER-DIEM rates, specifying lodging and M&IE ceilings. It distinguishes from sibling tools which are mostly about contracts, awards, regulations, etc., making this unique.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit input requirements: EITHER city+state OR zip, and warns against supplying both or neither. It also notes optional year with default behavior. However, it lacks explicit guidance on when to use this tool versus alternatives among the sibling tools, though the siblings are diverse.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description extensively discloses behavioral traits beyond annotations: duty-rate honesty (no numeric coercion), hierarchy inheritance, additional duties via Chapter-99, pagination behavior (offset ignored, client-side slice), error handling, and query length restrictions. No contradictions with annotations (readOnlyHint, openWorldHint).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is lengthy but well-structured with headings indicated by stars, and each paragraph serves a distinct purpose (duty-rate honesty, hierarchy, additional duties, completeness). Every sentence is informative; no fluff. Could be slightly more concise but justified by complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so the description must explain return values and edge cases. It details the response structure (query, lines array with fields), includes error behavior (throws on 404/5xx, invalid input, transient 400), and covers no-match case. Very complete for a lookup tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the description adds meaningful context: query must be ≥3 non-whitespace chars, limit ≤200 default 50, offset is client-side. It reinforces the dual-mode of query (keyword vs HTS number). This goes beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it looks up US import-tariff classification and duty rates from USITC HTS. It specifies the resource (Harmonized Tariff Schedule) and action (lookup). It distinguishes itself from sibling tool gsa_benchmark_labor_rates by noting it extends the price lane with a non-labor cost input.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use the tool (for import-tariff pricing in supply-chain contexts) and what it is not (not a binding ruling, not a landed-cost quote). It names a sibling (gsa_benchmark_labor_rates) but does not systematically list alternatives for each context. Overall, usage context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations mark readOnlyHint=true, and the description adds extensive behavioral details: keyless anonymous access, rate limit handling, honest pagination, specific handling of income/expenses (null vs 0), empty arrays, and error types (400, 429, 5xx, schema_drift). This provides exceptional transparency beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is comprehensive and well-structured, starting with purpose, then parameter notes, return format, and error handling. While somewhat lengthy, each sentence adds unique value; no waste. Minor conciseness improvement possible by grouping related notes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description provides a detailed return structure and covers all critical aspects: input parameters, pagination, data interpretation, error states, and authentication. It leaves no significant gaps for a complex API with 9 optional parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. The description adds valuable context: agency filter is silently ignored, authentication key goes in header, validation for filingYear, and filingType mapping examples. This enhances the schema definitions without redundancy.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches US Senate LDA filings and enumerates available filters (registrantName, clientName, etc.). It distinguishes from sibling tools by being specific to lobbying data, with no ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (searching LDA filings) and details all parameters being optional. It notes the agency filter limitation and advises alternative approaches (inspecting lobbyingActivities). However, it does not explicitly state when not to use it or list alternative tools, though siblings are clearly other government data tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond annotations by detailing honesty guarantees (complete:true, no pagination, empty instead of error, boolean flags preserved as is), error handling (4xx vs 5xx vs 200 non-JSON), and input validation (regex patterns). This adds significant context beyond the readOnlyHint and openWorldHint annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively long but well-structured with clear sections for behavior, input, output, and honesty. Every sentence adds necessary detail, though some redundancy with the schema exists.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description fully specifies the return structure and field semantics (dates as strings, null vs empty string, boolean flags). It also covers all edge cases and error modes, making the tool's behavior fully predictable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes all three parameters with 100% coverage. The description reinforces the validation patterns and adds examples, providing marginal added value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific verb-noun pair ('Look up NHTSA vehicle safety RECALLS') and immediately clarifies the tool's resource and domain. It distinguishes from sibling tools like 'nhtsa_complaints' by specifying safety recalls rather than complaints.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states that no API key is required ('KEYLESS — no API key is required or accepted'), which is a key usage guideline. It also details the required input parameters. However, it does not explicitly mention when not to use this tool or provide alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds extensive behavioral context beyond annotations: data provenance (IRS Form 990, ProPublica republishing), keyless access, error behavior (rate limiting with Retry-After, etc.), and return format details. Annotations only provide readOnlyHint and openWorldHint; description greatly enriches agent understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is lengthy but well-structured: starts with core purpose, then provenance, keyless access, parameter details, error handling. Each sentence adds value; minimal redundancy. Could be slightly more concise but remains efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully explains return structure (organizations array with fields, _meta with pagination), no-match behavior, error types, and data source. Combined with annotations, this is comprehensive for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with basic descriptions, but the tool description adds meaning: explains mapping to API query parameters (q, state[id], ntee[id]), default for page, and validation hints (state regex). This adds value beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches US tax-exempt nonprofits via IRS Form 990 data from ProPublica, specifying the exact data source and API. This distinguishes it from sibling tools like nonprofit_financials, which likely provide detailed financial data rather than search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides detailed guidance on pagination (0-based, pass page=cur_page+1 when hasMore), error handling (4xx, 429, 5xx, schema drift), and how to interpret results (totalAvailable vs current page). It lacks explicit when-not-to-use or alternative tools, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes far beyond annotations (readOnlyHint=true, openWorldHint=true). It discloses key behaviors: how no-match queries return empty, not error; pagination honesty (totalAvailable is meta.results.total); error handling for 400, 5xx, 200 non-JSON; and that 'Discontinued' marketing status is not an approval revocation. This provides rich behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is detailed but verbose, spanning multiple paragraphs. While front-loaded with the main purpose, it includes extensive technical details that could be streamlined. Some sentences are dense but necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully specifies the return structure (applications array with nested fields) and includes edge cases (404 handling, honest pagination, error behavior). This makes it complete for an agent to understand behavior and expected output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by explaining the mapping from parameter names to openFDA fields (e.g., sponsorName → sponsor_name) and emphasizes injection-safe Lucene escaping. This clarifies meaning beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches openFDA Drugs@FDA DRUG APPROVALS, specifies the verb 'Search' and the resource, and answers specific questions like 'what drugs did sponsor X get approved'. It distinguishes from sibling tools (e.g., openfda_device_clearances, openfda_enforcement) by focusing on drug approvals.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use: for pharma vendor product/approval intelligence. It mentions the optional API key and rate limits. However, it does not explicitly list cases when not to use or alternative tools, though siblings are clearly different.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, openWorldHint), the description adds rich behavioral details: it explains the `status` field is surfaced verbatim, the `link` field points to the public portal, the `totalAvailable` (count) is the org's total public project count, pagination behavior (offset snapped to page boundary), error handling (429/5xx throws, bad governmentCode triggers invalid_input pre-fetch), and ensures trustworthiness. This goes far beyond the minimal annotation information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively long but well-structured with clear sections, line breaks, and emphasis (e.g., ★STATUS, HONESTY). While every sentence earns its place, some redundancy could be trimmed, but the level of detail justifies the length. The structure aids readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (no output schema, many edge cases), the description covers the return structure (governmentCode, solicitations array with fields, _meta), error conditions, and honest behavior. It fully accounts for what the agent needs to use the tool correctly and interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema descriptions cover all parameters (100% coverage). The description adds extra value by specifying that governmentCode comes from opengov_list_governments, that limit defaults to 50 and offset is snapped to the API's page boundary, and mentioning _meta.pagination.nextOffset for pagination. This enhances understanding beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists public solicitations on OpenGov Procurement, specifying the verb 'List', the resource 'public solicitations', and includes the endpoint details, required parameters, and return structure. It distinguishes itself from sibling tools like opengov_list_governments (which lists governments) and bonfire_search_opportunities (different platform).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: governmentCode is required, sourced from opengov_list_governments, and explains limit/offset parameters. It also advises filtering status='open' for live bids and explains the significance of different statuses. It could be clearer about when not to use this tool versus alternatives, but it does give context for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations 'readOnlyHint' and 'openWorldHint' are present, and the description significantly expands on them by explaining the meaning of empty results, the need for verification, and the caveat about name matches. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but not verbose. Every sentence adds value. Could be slightly better structured (e.g., bullet points for caveats), but it remains concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully describes the return structure (excluded, matchCount, per-record fields) and includes interpretation notes. Parameters are covered in schema and description. The tool's purpose and limitations are well-communicated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description goes beyond by explaining interaction rules ('post-filtered when combined with name query'), requiring at least one parameter, and clarifying the behavior of 'activeOnly' and 'classification'. This adds meaningful value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('screen'), the target ('firm or individual'), the data source ('SAM exclusions index (FAPIIS)'), and the input methods (name/UEI/CAGE). It is specific and distinct from sibling screening tools like 'sam_integrity_lookup' or 'ofac_screen_entity'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use this tool (for debarment/exclusion screening) and critical interpretation guidance (empty result ≠ general responsibility, name match not identity-proof). It does not explicitly list when not to use or compare to alternatives, but the context is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behavioral traits beyond annotations: the dataset lacks an effective date, so the result is timestamped with asOf; it clearly states that SBA adjusts standards periodically and advises re-verification. It also ensures no fabricated results for unknown NAICS. Annotations (readOnlyHint, openWorldHint) are consistent and not contradicted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is informative and well-structured, front-loading the core purpose. It uses clear labeling like 'HONESTY:' to highlight caveats. While every sentence adds value, the description could be slightly more concise without losing essential details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description thoroughly explains the return fields (standardType, threshold, unit, footnote) and the honesty note about data freshness. It also covers error handling for unknown NAICS. This is complete for a simple lookup tool with one parameter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters with a clear description of the naics parameter ('6-digit NAICS code'). The tool description adds minimal new meaning beyond the schema, merely restating the format. With high schema coverage, a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to look up the SBA small-business size standard for a 6-digit NAICS, specifically answering 'is a firm SMALL for this NAICS?' and acting as a gate for set-aside eligibility and vetting teaming partners. This distinguishes it from sibling tools that deal with contracts, agencies, or other government data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool (for set-aside eligibility and vetting candidates) and provides important caveats: the dataset has no effective-date field, so values are 'as of retrieval' and SBA adjusts standards periodically, recommending re-verification at sba.gov for high-stakes decisions. It also notes that unknown NAICS return found:false, avoiding fabricated results.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations mark it as read-only and open-world, which is consistent. The description adds significant detail: client-side filtering over a CSV, exact match counts, exclusion of security contact emails, error behavior (throws on 4xx), and potential schema drift. This goes well beyond annotation hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured, starting with a clear purpose statement. While it is relatively long, each sentence provides essential information (e.g., scope values, filter behavior, source honesty). It is efficient but could be slightly trimmed without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description lists the fields returned per row. It covers data source, filtering mechanics, error handling, and schema drift. For an 8-parameter search tool with no required params, this is thorough and addresses likely questions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters with descriptions. The tool description reinforces these with examples (e.g., 'veterans' for organization, 'cdc.gov' for domain) and lists output fields (domain, domainType, etc.). This adds value, especially since there is no output schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the tool searches the authoritative US .gov domain registry (CISA get.gov) to resolve organization ownership, enumerate federal agencies, and map SLED entities. The verb 'search' and resource are clear, and the tool is distinct from sibling tools that focus on contracts, awards, or other government data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states when to use: for resolving domain ownership, enumerating federal agencies, and marketing targeting. It also clarifies that security contacts are excluded and that errors throw rather than returning empty results. Although no explicit alternatives are given, the tool's unique purpose makes this less necessary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond the annotations (readOnlyHint, openWorldHint) by detailing key behaviors: keyless access, honest total count handling (exact via count query or null with note on failure), error behavior (throws on outage/400/404, never fake empty), and that value fields are strings. This provides extensive behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is comprehensive yet efficiently structured: purpose first, then parameter details, then behavioral honesty note. While lengthy, every sentence adds essential value without redundancy. A slight trim could be possible, but it earns its length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description covers response behavior thoroughly: row response format, total count mechanism, distinction between genuine empty and error, and value types. It also mentions the companion count query and pagination implications. Almost all necessary context is provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the baseline is 3, but the description adds significant value: explains domain as a curated allowlist enum (SSRF guard), datasetId format, each SoQL parameter (select, where, order, q) with examples, limit range (≤1000, default 100), offset, and withTotal behavior (default true, issues count query). This deep explanation compensates well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool queries rows from an allowlisted Socrata/SODA open-data portal, specifically for state spend/checkbook/contract/vendor-payment datasets. It distinguishes from the sibling tool socrata_discover_datasets which provides the required datasetId.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains what inputs are needed (domain, datasetId, optional SoQL parameters) and mentions that datasetId comes from socrata_discover_datasets. It does not explicitly state when not to use the tool, but the specificity of the allowed portals and parameter details provides clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds critical context beyond readOnlyHint/openWorldHint: explains scope spans all award types, not just contracts, and how data differs by agency type. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Efficient, front-loaded with purpose, then scope, warnings, alternatives. Slightly long but all sentences earn their place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description lists key output fields (transaction_count, obligations, latest_action_date). Explains scope and limitations fully, making tool well-understood.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 50% (only toptierCode has description). Description gives example value for toptierCode but does not explain fiscalYear format or range. Adequate but could be more detailed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'get summary' and resource 'awards' for a fiscal year, listing output fields. Distinguishes from sibling usas_spending_over_time for contracts-only.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use alternative (usas_spending_over_time for contracts-only) and warns about benefit-heavy agency interpretation. Also advises resolving toptierCode via usas_get_agency_profile.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint), the description discloses that key values are never shown, only boolean 'currentlySet'. It explains the return JSON structure, how keys are loaded (env vars/.env), and that this tool reports config state, not key validity. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is detailed but every sentence adds value. It could be slightly more concise, but the length is justified given the complexity of the tool. It front-loads the purpose and then provides necessary specifics.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is exceptionally complete: it specifies the return structure, behavior around key values, key sources, setup mechanisms, and distinguishes between config and functional verification. It compensates fully for the lack of output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema coverage, the description reinforces that the tool is 'KEYLESS (no input)', adding clarity beyond the empty schema. It eliminates any doubt about required inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List every API key this server can use' with specific details about required vs optional, signup URLs, and configuration status. It distinguishes itself from data-fetching sibling tools by focusing on configuration state.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says when to use this tool (check configuration state) and when not (to verify a key works, call the source's own tool). It provides guidance on key setup (env vars or .env file). A clear 'when-not' is given, but no explicit listing of alternative tools for verification.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes far beyond the readOnlyHint and openWorldHint annotations by detailing honesty measures (count behavior, date epoch handling, no-match responses, error surfacing, schema drift detection, SSRF protection). Comprehensive behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with sections and front-loaded with purpose. Somewhat verbose but every sentence adds value; could be slightly tightened without losing information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters, 23 services, pagination, and no output schema, the description is remarkably complete: covers return structure, pagination mechanics, date field caveats, error cases, and SSRF protections. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds substantial meaning beyond the 100% schema coverage: explains service enum values in detail, provides example where clauses, clarifies pagination with limit/offset and _meta field, and describes output format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Query rows from a curated US-government ArcGIS REST feature layer' and distinguishes itself as the QUERY companion to arcgis_hub_discover_datasets. Provides specific layer examples and context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly names the sibling tool arcgis_hub_discover_datasets and frames this tool as its query counterpart. Describes the data domain (SLED procurement/GIS) but does not provide explicit when-not-to-use scenarios or other alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description is exceptionally transparent: it discloses that missing/invalid keys produce HTTP 200 with Error object (not HTTP error), explains data parsing of comma-formatted strings, maps suppression codes to null, and clarifies that unitMult is not applied. All this goes well beyond the readOnlyHint and openWorldHint annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense and informative, but slightly long. It is front-loaded with purpose and key requirement. A more structured format (e.g., bullet points for parameters) could improve readability, but the current prose is efficient and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description fully specifies the return format ({ rows:[...], notes:[...] }) and edge cases (empty result, 5xx, non-JSON response). It covers authentication, error handling, and data interpretation, making it complete for a complex API tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds significant meaning: examples of tableName ('CAGDP2', 'SAGDP2N'), geoFips ('STATE', '06075'), lineCode (integer or 'ALL'), year ('LAST5', '2022'), frequency ('A', 'Q'). It also explains the response fields, which is not present in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns regional economic data (GDP, personal income) from the BEA. It distinguishes itself from sibling tools by specifying the exact data source and API. Even without explicit comparison, the purpose is unambiguous and complete.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage context: requires BEA_API_KEY, explains key requirement, parameter details, and error handling. It does not explicitly state when not to use the tool, but the specificity of the domain (BEA regional data) makes misuse unlikely.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes far beyond the readOnlyHint and openWorldHint annotations. Discloses that the RSS is the complete set, client-side pagination, exact totalAvailable, honest empty result, error handling (429/5xx/404 throw, no fake empty), schema drift detection, invalid input pre-fetch, fixed-suffix SSRF, and keyless access. Fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but well-structured with clear sections (HONESTY, etc.) and no wasted sentences. It front-loads the main purpose. A touch verbose but justified by the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description explicitly declares the return shape ({ org, opportunities, _meta }) and covers edge cases (empty feed, errors, schema drift). This is complete for an agent to understand and use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters have schema descriptions, but the description adds critical context: org is from bonfire_list_organizations, limit is 1-200 with default 50, offset is 0-based, and these are client-side pagination over a complete RSS feed. This meaningfully augments the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool lists currently-OPEN solicitations on Bonfire via RSS. It specifies the source (Bonfire), the scope (open), and the method (keyless RSS), distinguishing it from other government opportunity tools like SAM.gov or Grants.gov.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states that the tool is keyless and requires an org slug from bonfire_list_organizations. It also clarifies that the RSS is the complete set and errors are thrown. However, it does not explicitly compare to sibling opportunity search tools like sam_search_opportunities or opengov_search_solicitations, which would help an agent choose between them.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint:true, but the description adds valuable behavioral context: it is keyless, returns specific fields like resourceId and datastoreActive, warns that datastoreActive:false resources are raw file blobs not in the datastore, and mentions the totalAvailable count. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise yet packed with all necessary information: purpose, inputs with examples, output format, and usage guidance. Each sentence serves a distinct purpose, and critical details are front-loaded. No extraneous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, no output schema), the description fully covers what the tool does, how to use it, and what the returned data means (including datastoreActive flag). It provides enough context for an agent to correctly invoke the tool and interpret results without additional documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, baseline is 3. The description adds extra value beyond the schema by providing example values for q (e.g., 'procurement'), clarifying the enum meanings for host (allowlisted .gov portals), and specifying the limit default (20) and maximum (100). It also notes 'keyless' operation, which is not in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Find CKAN datastore resource ids by keyword via package_search (keyless).' It distinguishes itself from the sibling tool ckan_query by indicating that results should be fed to ckan_query for actual data querying. Also, specific host enums and example keywords like 'procurement' and 'checkbook' make the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit input instructions for host, q, and limit, and advises to feed a datastoreActive:true result's resourceId to ckan_query. It implies when to use this tool (to discover datasets) and how to proceed, but does not explicitly compare with other sibling tools like socrata_discover_datasets. However, the guidance is sufficient for proper usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, openWorldHint), the description adds key behavioral details: API key requirement, that outages/4xx throw errors (never fake empty), and that query parameter is dropped. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense with information but remains single-paragraph and front-loaded with the main purpose. While efficient, a bit more structure (e.g., bullet points) could improve readability, but it is not overly long.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description thoroughly details the return format (bills array with fields + meta with totalAvailable) and error behavior (throws on outage/4xx). Also covers all parameters, key requirement, and pagination. Complete for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds significant value beyond schema: explains query is not applied, billType requires congress, ISO-8601 date format examples, limit max 250, default 20, and return structure. This fully compensates and enhances understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is for searching Congress.gov BILLS/legislation, specifying the resource (bills) and action (search). It also distinguishes from potential siblings (like congress_get_bill) by focusing on list/search functionality and noting limitations like no keyword search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides guidance on parameter usage, such as requiring congress for billType, explaining that query is not applied and suggesting alternatives (congress/billType/date filters). However, it does not explicitly mention when to use sibling tools like congress_get_bill for single bills.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses client-side filtering, throws on 5xx, handles schema drift, explains pagination and totalAvailable behavior. Adds value beyond readOnlyHint and openWorldHint annotations with honest verification.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-organized with core purpose first, then details, return format, and error handling. Slightly verbose but every sentence provides unique value; minor redundancy possible.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all essential aspects: input, filtering behavior, return structure, pagination, error modes, and connection to sibling tool. No output schema, but return format is documented inline.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Enriches every parameter beyond schema descriptions: default/max for limit, examples for query, client-side nature for agency, pagination hint for offset. Coverage is 100% and description adds concrete, actionable detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it lists the DOL Data API v4 dataset catalog, identifies it as the machine inventory of enforcement/statistics datasets, and distinguishes itself from dol_get_dataset by noting keyless access.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly describes when to use (catalog listing) and how to connect results to dol_get_dataset. Implicitly excludes other tools through sibling context, but lacks explicit 'when not to use' statements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds valuable context: 'never a fabricated report', output structure including _meta, and error behavior on bad RegistryID. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each with a clear role: purpose, input, output/behavior. No unnecessary words, front-loaded with the most critical information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read-only tool, the description covers purpose, input, output format, error behavior, and usage scenario. No missing elements given the simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a detailed description of registryId. The tool description adds context about source (echo_search_facilities rows), validation (all-digit, 9–12 digits), and error behavior, going beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Fetch the EPA ECHO Detailed Facility Report (DFR) for ONE facility by its FRS RegistryID', providing a specific verb, resource, and scope. It distinguishes from the sibling tool echo_search_facilities which is for searching facilities. No ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use: 'for competitor or acquisition-target due diligence', and clarifies input source: 'from echo_search_facilities rows'. It also describes behavior on bad input but does not explicitly state when not to use, though the unique purpose makes it clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes well beyond the annotations (readOnlyHint, openWorldHint) by detailing the fullHistory mechanics, shard fetching, honesty in totalAvailable (recent + all shard counts), cap/failure disclosure (PARTIAL-BY-CAP, PARTIAL-BY-FAILURE), and the shared EDGAR throttle gate. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but efficient, with no wasted words. It front-loads the purpose and input summary, then adds behavioral notes. However, it could benefit from minor structuring (e.g., listing parameters) to improve scanability for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, shard logic, throttle gate, completeness guarantees) and no output schema, the description covers all essential aspects: input, behavior, edge cases (partial responses), and return format (filings with archive URL). It provides sufficient detail for correct invocation and interpretation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 6 parameters have schema descriptions, but the tool description adds substantial value: explains the default for limit (20), maxShards (10), fullHistory (false), clarifies that offset applies to recent window, and describes the interplay between fullHistory and maxShards. It also defines keyless access and the source URL.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns a company's SEC filings from data.sec.gov, specifying inputs (cikOrTicker, forms, limit, offset, fullHistory, maxShards) and output (filings with real primary-document URL). It distinguishes itself from siblings like edgar_company_facts or edgar_full_text_search by focusing on filings retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use fullHistory (for complete history vs. recent window), how pagination works (offset vs. maxShards), and what to do if capped (raise maxShards). It also notes the EDGAR throttle gate and that CIK is used, not SAM UEI/DUNS. While it doesn't name alternative tools explicitly, the context is clear enough for an agent to decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond annotations by detailing honest data fetching (whole frame fetched, limit/offset is client-side), error handling (404 instead of fabricated zeros), stat behavior (null when count=0), and validation. This builds trust and sets correct expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is packed with essential information but is somewhat lengthy. It is front-loaded with the purpose and key details. Every sentence adds value, but it could be slightly more concise without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, no output schema), the description covers behavior, error scenarios, parameter details, and statistical output comprehensively. It leaves no major gaps for an agent to misuse the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds critical nuances: tag must be exact alphanumeric, period requires trailing I for instant concepts, limit/offset are client-side, includeStats details linear-interpolated percentiles and null handling. This clarifies meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: returning a complete cross-section of every filer's value for a single US-GAAP/DEI concept in one period for peer benchmarking. It distinguishes from sibling tools like edgar_company_concept by specifying it covers all filers, not just one company.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says to use this tool for cross-filer analysis and benchmarking, providing clear context. While it doesn't list when not to use it or name alternatives, the use case is well-defined, and the parameter descriptions guide correct invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant context beyond annotations: risk-flag honesty (tri-state vs false-CLEAR), empty results not implying clean audit, PII protection via hardcoded select-allowlist, totalAvailable behavior, error handling (400/403/5xx throw), and rate limiting for DEMO_KEY. No contradictions with annotations (readOnlyHint and openWorldHint are consistent).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with bullet points and emojis, packing a lot of information efficiently. It is somewhat lengthy, but every sentence adds essential detail. A slight reduction in verbosity could improve conciseness, but it remains effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of the tool (nuanced risk flags, empty results, PII, error handling) and the lack of an output schema, the description covers most critical aspects: purpose, parameters, behavior, limitations, and caveats. It partially describes the return structure (findings array with riskFlags). While more detail on output shape could help, it is sufficiently complete for proper usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by indicating that at least one of auditeeUei or reportId is required (schema says all optional), mapping field names (auditeeUei → auditee_uei, reportId → report_id), and specifying limit's maximum and default. This goes beyond the schema, justifying a score above baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Drill into' and identifies the resource as 'audit-RISK findings for an entity from the Federal Audit Clearinghouse.' It also distinguishes itself from sibling tools by noting it is 'the risk-detail step after fac_search_audits,' making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states the required parameters ('At least ONE of auditeeUei or reportId'), provides defaults and limits, and warns against using it for debarment determination. It also explains how to interpret empty results and suggests cross-referencing with fac_search_audits, giving clear guidance on when and how to use the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes far beyond the readOnlyHint annotation by detailing the meaning of depositsUSD (conversion from thousands, null handling), error behavior (server-side allowlist, only honest empty is meta.total:0), and data limitations (annual snapshot, no PII). It also discusses totalAvailable behavior, adding significant context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense and informative, but somewhat long. It is front-loaded with the purpose, then lists parameters, then provides behavioral notes. Every sentence adds value, but some details could be streamlined for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 7 parameters, no output schema, and no nested objects, the description is thorough: it covers all parameters, output structure, example rows, pagination, error handling, and data semantics. No important aspect is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the input schema has 100% coverage, the description adds substantial meaning: cert is the stable entity key, state uses C118 quoting, sortBy options are explained, and the returned fields (e.g., depositsUSD, institutionName) are described in context. This goes beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves FDIC branch-deposit footprints from the Summary of Deposits, specifying it provides annual June-30 branch-office deposit distribution. It uses specific verbs ('retrieve', 'footprint') and distinguishes itself from sibling tools like fdic_institution_financials by focusing on branch deposits.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that all filters are optional and recommends using at least one, provides guidance on pagination parameters (limit, offset) and sorting, and implicitly distinguishes from other FDIC tools by the data type. However, it does not explicitly state when not to use this tool or mention alternative tools for related data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes far beyond annotations by disclosing inlinecount behavior, exact total count, null handling, empty response format, and error throwing. It also notes filters are 'LIVE-VERIFIED', adding reliability context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but well-structured with a clear logical flow: purpose, filters, honesty notes. Some redundancy could be trimmed, but every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (11 parameters, no output schema), the description covers behavioral details, edge cases, authenticity, and error handling. It provides enough context for effective use without an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Even though schema coverage is 100%, the description adds significant meaning: mapping filters to OData fields, providing example values, explaining limit/offset in API terms, and indicating filters are module-built. This enriches understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches FEMA Public Assistance funded projects, specifies the exact dataset and version, and distinguishes it from sibling tools like fema_disaster_declarations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use the tool (searching PA projects) and details the structured filters. It implies alternatives exist (e.g., disaster declarations) but doesn't explicitly state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and openWorldHint=true. The description adds crucial behavioral details: missing values map to null not 0, error handling specifics (400 returns invalid_input with FRED message), pagination via hasMore/nextOffset, validation rules, and key placement. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-organized with bold emphasis and bullet points for key sections. Front-loads core action and prerequisites. Slightly verbose but every sentence adds value; could be tightened slightly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters, no output schema, and complex behavior (pagination, error handling, missing values), the description covers return format ({observations}), pagination metadata, error scenarios, and validation. Fully compensates for missing output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description enriches each parameter with examples (seriesId: 'GDP', 'CPIAUCSL'), default values (limit 100, max 100000), validation patterns, and additional context (startDate/endDate map to FRED observation_start/end). Goes beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches FRED series observations with specific verb 'Fetch' and resource 'FRED series' time series. It provides examples of series IDs and distinguishes from fred_search_series for discovery.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly requires FRED_API_KEY with warning about no keyless tier, advises using fred_search_series for ID discovery, and lists optional parameters with defaults and constraints. Does not explicitly state when not to use, but context makes it clear this is the only FRED data-fetching tool among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and openWorldHint=true. The description adds crucial context: the feed covers only ~25 items, results are incomplete (complete:false), and historical search requires a paid API. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is fairly concise given the complexity, with key info front-loaded. It includes an 'HONEST SCOPE' section that clearly states limitations without being verbose. Minor redundancy but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description covers usage, filtering, enrichment, and limitations. It explains the fields returned (protester, agency, outcome, etc.) and when to expect nulls. Sufficient for effective tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the baseline is 3. The description adds value beyond schema by explaining the limit's relation to feed size, the agency filter's scope, and bNumber's purpose to bypass the feed for aged-out decisions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves 'Recent GAO (Comptroller General) bid-protest decisions' from a specific RSS feed, enriched with details. It differentiates from unrelated sibling tools by focusing on GAO protests, with no overlap.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly notes when to use (recent feed) and when not (historical search is WAF-blocked). It advises using bNumber for aged-out decisions and clarifies that results are always marked complete:false, guiding the agent on appropriate scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and openWorldHint. The description adds: response structure with found:true/false, package object, and meta; that a nonexistent packageId returns found:false with HTTP 404; and that API keys in download links are stripped. This provides full transparency beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (three sentences) and front-loaded with the core action. Every sentence adds information: what it does, how to use it, and important edge-case behavior. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple fetch tool with one parameter and no output schema, the description is complete. It covers the response structure, error handling (404), and data cleaning (API key stripping). No further details are needed for correct invocation and understanding of results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a description for packageId. The tool description adds value by explaining the source of the ID (from govinfo_search_packages) and providing examples, which helps the agent understand the expected format. This goes beyond the schema's minimal description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it fetches a single GovInfo package's summary with metadata and download links. It specifies the required packageId and gives concrete examples. It distinguishes itself from sibling tool govinfo_search_packages by indicating that its input comes from that search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: after obtaining a packageId from govinfo_search_packages. It does not explicitly state when not to use it or mention alternatives, but for a fetch tool this is reasonably clear. The behavior on nonexistent ID (404) is explained.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and openWorldHint. The description adds critical behavioral details: returns distribution (min/median/max + escalated medians), match count saturation, and null totalAvailable for broad queries. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense paragraph that front-loads purpose and then provides essential details. It is efficient but could be slightly more structured with bullet points for readability. Still, every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description explains return distribution components (currentRate min/median/max + escalated medians). It covers key aspects like saturation and filtering, but could mention error states or define 'keyless' more clearly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. The description adds semantic value by explaining education level uses short codes, business size filter meaning, and context like 'keyless' and saturation effect on results, raising the score above baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'benchmarks' and resource 'GSA CALC labor rates', specifying it returns a distribution not a single price. It distinguishes from any sibling by focusing on labor rates, a unique domain among the listed tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance: rates are ceilling/catalog and fully burdened, warns against double-adding wrap, explains saturation at 10000 matches, and suggests filters to narrow queries. It covers both usage and limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes far beyond annotations: explains data provenance (ProPublica, not .gov), keyless access, null-vs-0 coercion, complete error mapping (404→not_found, 429→rate_limited, 5xx→upstream_unavailable, schema drift), and pagination (no pagination). Annotations already provide readOnlyHint and openWorldHint, but description adds rich behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, then efficiently structures details in logical order: provenance, input, return structure, data honesty, error handling, and meta. Every sentence is informative with no redundancy, achieving thoroughness without verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully explains return structure (organization fields and filings array with field meanings), error responses, pagination, and data source. It covers all essential aspects for an agent to correctly interpret results and handle errors.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds value by providing an example EIN ('530196605'), explaining validation pattern, and noting it rides the URL path. This extra context improves understanding beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the exact verb 'Fetch', resource 'nonprofit's IRS Form 990 profile + FINANCIALS', and input 'by EIN'. It clearly distinguishes from sibling tools like 'nonprofit_search' by focusing on a single EIN retrieval with detailed financial data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly conveys usage: use when you have an EIN and need financials. However, it lacks explicit guidance on when not to use it or direct references to alternatives (e.g., 'nonprofit_search' to find EINs). The context is clear but not exhaustive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes far beyond the annotations by disclosing that data is real-time, a live snapshot, not historical; that null values are never empty strings; that totalAvailable is exact; that empty results are not errors; that outages throw; and that schema drift is detected. It also confirms a descriptive User-Agent is sent. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but well-structured: it starts with the main purpose, then explains the lane context, lists filters, describes the alert object, and ends with behavioral notes. Every sentence adds value, though it could be slightly more condensed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, no output schema), the description is highly complete. It covers the tool's purpose, all filters, return object fields, behavioral nuances (null handling, error behavior), and usage context. It leaves no critical gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the description still adds significant value by explaining each parameter in detail, such as 'case-insensitive substring' for event, '2-letter code → server-side ?area=' for state, and pagination defaults (limit 50, max 500). It provides context beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List CURRENTLY-ACTIVE National Weather Service alerts' with specific verbs and resource. It distinguishes from sibling tools by noting it is the 'disaster/climate-readiness lane that pairs with the FEMA tools' and that it shows live alerts as opposed to historical data or other FEMA-related actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains each filter (state, event, severity, limit, offset) with usage details like 'omit for all US' and 'case-insensitive substring'. It provides context that the tool is for real-time alerts and pairs with FEMA tools, but does not explicitly state when not to use or list specific alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Exceeds annotations by detailing honesty contracts (exact-match count, null amounts, offset behavior), SSRF protection, schema drift handling, and data recency (only 3 fiscal years). No contradictions with readOnlyHint and openWorldHint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Information-dense but structured with bullet points. Could be slightly tighter but front-loads purpose and key details. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers input/output format, corner cases (misses, deep offsets), error handling (429/5xx), and data limitations. No output schema, but description compensates with return structure and honesty notes. Complete for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and description adds meaning for each parameter: exact-match behavior, example values, portal allowlist, page snapping, and default behaviors. Adds value beyond schema fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool is a row-level vendor-payment search for Socrata Open Checkbook portals, specifically the State of South Dakota example. Distinct from siblings which cover other data sources (USASpending, SAM, etc.) — unique verb+resource combination.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage for finding vendor payments from state checkbook portals, with explicit example (SD). No exclusions but context suggests it's for SLED spending data. Lacks explicit 'use when' vs alternatives like socrata_query.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description extensively covers behavioral traits beyond annotations: keyless operation, error handling (404→empty, 400→invalid_input, 5xx→throws, 200 non-JSON→schema_drift), honest pagination with totalAvailable exact, null-never-empty strings, and safe Lucene query construction. No contradiction with annotations (readOnlyHint=true, openWorldHint=true).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively long but well-structured with clear sections and bullet points. It front-loads the purpose and keyless info, then details parameters and error handling. Every sentence adds necessary information; minor room for trimming but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description fully documents the return structure (recalls array with fields, _meta with totalAvailable and pagination tokens) and all edge cases (empty response, errors). It is self-contained and complete for agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds significant value by explaining the mapping of filters to openFDA fields (e.g., firm→recalling_firm), the default category, safe injection-free Lucene string assembly, and validations (e.g., state format). This goes well beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches openFDA recall/enforcement records, listing specific categories (drug/device/food) and data fields. It distinguishes itself from sibling tools like openfda_device_clearances and openfda_drug_approvals by focusing on enforcement/recalls.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains how to use filters, pagination, keyless vs. keyed access, and error handling. It doesn't explicitly state when not to use this tool, but it's clear this is for enforcement data; alternatives are implied by sibling tool names. The honesty about rate limits and error cases is helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes far beyond the annotations (readOnlyHint, openWorldHint) by detailing pagination caps (40 pages, 10,000 records), the honesty of totalAvailable vs totalPages sentinel, the page[size] floor of 5 behavior, rate limits for DEMO_KEY vs API_KEY, and error handling (genuine-empty vs throws). No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph but is front-loaded with purpose and logically organized by parameters, honesty, rate limits, and error handling. It is dense but each sentence contributes essential information. Could be slightly more structured, but it is appropriate for the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 9 parameters, no output schema, and numerous siblings, the description is comprehensive: it covers how to use, edge cases (page cap, limit floor), behavior of meta fields, rate limits, and error conditions. It also describes the return shape sufficiently for an agent to interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the baseline is 3, but the description adds significant meaning: explains that 'query' and 'searchTerm' are aliases, gives example values like 'endangered species', describes filter mappings (e.g., filter[agencyId]), explains sort verification, and details the limit floor behavior. This adds value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'Search Regulations.gov DOCKETS' and explains that dockets are containers for documents and comments, clearly identifying the verb and resource. It distinguishes from siblings like regulations_search_documents and regulations_search_comments by specifying the object type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies API key requirements (DEMO_KEY vs DATA_GOV_API_KEY) and explains the pagination cap and the need to narrow filters to reach beyond. It notes that 'rin' is null in list rows and suggests using regulations_get_docket for that field, providing guidance on when to use an alternative. However, it does not explicitly contrast with other search tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behavioral traits beyond the readOnlyHint and openWorldHint annotations: pagination behavior (hard cap, ceiling note), honesty of totalAvailable vs capped totalPages, error handling (genuine-empty vs outage/4xx throws), and how to reach more records. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively long but every sentence earns its place by providing critical usage information. It is front-loaded with the core purpose and then systematically covers parameters, pagination, and error behavior. Minor redundancy (e.g., mentioning 'flagship' is not essential) could be trimmed, but overall it is well-structured and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explicitly documents the return structure (documents array with fields like id, documentType, title, etc.) and the meta object behavior (totalElements as exact total). It also covers all parameters, pagination limits, and error states (genuine-empty vs outage). This is comprehensive for a complex search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the baseline is 3, but this description adds significant value: it clarifies the relationship between query and searchTerm (aliases), explains sort options (default, live-verified set), describes pageNumber hard cap as 'HARD cap', details date format (YYYY-MM-DD), and interprets withinCommentPeriod as 'documents only'. This goes well beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'Search Regulations.gov rulemaking DOCUMENTS (rules, proposed rules, notices)' which uses a specific verb and resource, and immediately distinguishes from sibling tools like regulations_search_comments (for comments) and regulations_search_dockets (for dockets). The explicit enumeration of document types ensures clear purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use this tool (search for rulemaking documents) and provides important usage constraints: pageNumber hard cap at 40, pageSize range, and alternative strategies (narrow filters / seek by lastModifiedDate) when the ceiling is reached. It could be more explicit about when to prefer sibling tools, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Extensively discloses behavior: handles PDF via pdfjs and text/HTML, returns structure with key fields, handles errors (corrupt/encrypted PDF, DOCX/binary, fetch failures, 404), SSRF hygiene, and truncation disclosure. This goes far beyond the readOnlyHint annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single dense paragraph, front-loaded with purpose, no fluff. Every sentence adds essential information about behavior or constraints.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, description fully explains returned fields (format, text, pages, etc.) and error-handling behavior. Addresses edge cases and constraints (SSRF, truncation). Complete for a tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% parameter description coverage. Description adds important context: url must come from sam_get_opportunity → resourceLinks, maxChars default and max, and that truncation is disclosed. Adds modest value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it extracts text from a SAM notice attachment, specifies input type (download URL), and distinguishes from metadata-only tools like sam_get_opportunity. Verb 'Extract the TEXT' is specific and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Describes when to use: to read the real solicitation instead of metadata. Implies use after sam_get_opportunity. Does not explicitly mention when not to use or list alternatives, but context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond the 'readOnlyHint' and 'openWorldHint' annotations by detailing behavior: filters are applied server-side (state) or client-side (county) due to API limitations, and coverage 'dba' is normalized to 'dbra'. It explains the pagination defaults and the open-world nature of results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (4 sentences) with a front-loaded purpose sentence, followed by filter details and a crucial note. Every sentence adds value, no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 parameters and no output schema, the description covers all parameters, explains API limitations, and provides usage sequence (follow with sam_get_wage_rates). It is complete for an effective search tool, addressing potential confusion.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the baseline is 3. The description adds significant value by explaining the client-side vs server-side behavior for state and county, the normalization of 'dba' to 'dbra', and reinforcing that 'query' only matches WD number/title. This clarifies parameter usage beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it 'Find the Service Contract Act (SCA) or Davis-Bacon (DBA) wage determination(s) governing a locality (keyless SAM SGS).' It clearly defines the core action (searching wage determinations) and the specific resources (SCA/DBA). It distinguishes itself from the sibling tool 'sam_get_wage_rates' by noting the follow-up step.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use the tool (to find wage determinations by locality) and includes a critical note that 'query matches WD number/title only, NOT occupation', preventing misuse. It also directs to use 'sam_get_wage_rates' to read the rate table. However, it does not explicitly state when not to use this tool over alternative search methods, but the sibling list includes many unrelated tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes important behaviors beyond annotations: client-side pagination, no server pagination, trimmed strings with null for empty, formatted amounts, error handling (429/5xx/404/thrown, schema_drift for gated views), and SSRF safeguards. Annotations only provide readOnlyHint and openWorldHint; description adds rich detail without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Long but densely informative; front-loaded with purpose. Every sentence adds context, though some redundancy exists (e.g., repeated emphasis on SSRF). Could be slightly more concise, but remains effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Fully explains return format (view, columns, rows, _meta), error handling, honest pagination, and data integrity. No output schema, so description compensates thoroughly. Covers all likely agent questions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and description adds substantial context: view enum explained with example data and record count, limit/offset explained with meaning of totalAvailable (true row count) and client-side pagination. Goes well beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it fetches a complete CSV export from a Tableau Server Guest view, specifically for government transparency data. Provides an explicit example (mt_contracts_awarded) and distinguishes from sibling tools which focus on different data sources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explains the context (SLED transparency, keyless access) and when to use (fetching government contract data from Tableau). Lacks explicit when-not-to-use or direct alternatives, but the sibling list and clear scope make usage context clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. Description adds substantial value by detailing what signals are assembled (pctConsumed, mod count, etc.), that it emits pressureHints (never a composite score), and limits (at most 3 upstream calls). No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Every sentence earns its place. The description is dense but not verbose, front-loaded with core purpose, and structured to quickly convey scope, signals, limitations, and bounded behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description adequately explains the output by mentioning pressureHints, _meta.fieldsUnavailable, and the nature of returned data. It is complete for most use cases but could explicitly list the returned fields or structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds meaning beyond schema: explains generatedInternalId is 'the ONE award' and gives example sources, clarifies otherAwardsLimit as a cap with defaults, and states includeOtherAwards triggers a bounded recipient search with default true.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it performs 'per-award incumbent + PUBLIC recompete-pressure analysis for ONE award' using generatedInternalId. This specific verb-resource-scope combination distinguishes it from sibling tools like usas_get_award_detail (just details) or usas_search_recompetes (search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides context about bounded upstream calls, optional includeOtherAwards, and explicitly declares unavailable fields (CPARS, past performance). However, it does not explicitly state when to use this tool versus alternatives or when not to use it, missing a clear exclusion criterion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes well beyond the readOnlyHint and openWorldHint annotations by detailing null handling (number|null for amount/perCapita, real 0 stays 0, absent becomes null), pagination behavior (complete set, no pagination), and error handling (throws on 4xx). No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is thorough and well-organized, front-loading the core purpose and key constraints. It includes valuable notes on null handling and endpoint behavior, but could be slightly more concise; some details are repeated (e.g., defaults mentioned twice). Overall, efficient for the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description sufficiently outlines the output fields (name, code, amount, awardCount, population, perCapita) and explains null handling. It covers all parameters, default behaviors, and error states. The tool's complexity (3 params, 1 required, 2 enums) is fully addressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the schema covers all parameters (100% coverage), the description adds meaningful context: explains the role of defCodes (linked to usas_list_disaster_codes), spendingType (obligation vs outlay with a note about real outlays), and geoLayer (default values and levels). This enriches the parameter semantics significantly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: disaster spending by geography with DEFC tags, breaking out by state/county/district. It explicitly distinguishes from standard award search by emphasizing the geography axis and mentions it's a distinct endpoint not covered by other tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear guidance on required parameters (defCodes) and defaults for spendingType and geoLayer. It also suggests trying both obligation and outlay. However, it does not explicitly state when not to use this tool vs alternatives, only implying its distinct purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond annotations by listing specific return fields (period_of_performance, base_and_all_options, set-aside type, etc.) and explaining that it returns what the search endpoint omits. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that conveys purpose, parameter source, and returned fields efficiently. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature of the tool (one parameter, no output schema), the description is complete. It informs the agent what to expect in terms of return fields and parameter source.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter is well-described in both schema and description. The description adds value by specifying the source tool and example format, though the schema already provides a clear description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetch full detail'), the specific resource ('single award'), and identifies the identifier ('generatedInternalId') with its source. It distinguishes itself from the sibling search tool by listing fields it returns that the search omits.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool (after usas_search_individual_awards to get full details). It does not explicitly say when not to use it or provide alternatives, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, openWorldHint), the description adds that the tool returns the complete code set with no pagination, details the fields per code (group, title, publicLaw), and includes an honest note about null groups and exact totalAvailable. This provides comprehensive behavioral insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph that is well-structured and concise. Every sentence adds value: purpose, usage, return details, and honesty note. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description fully explains what is returned (code, group, title, publicLaw), the completeness of the set, and the context of DEFCs. It is sufficient for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the description correctly does not need to explain parameters. Per guidelines, baseline is 4. The description instead focuses on the return structure, adding value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Disaster Emergency Fund Codes (DEFC), specifies what they are (supplemental-appropriation tags), and explicitly differentiates from the sibling tool usas_disaster_spending by mentioning it filters on these codes. The verb 'list' and resource 'disaster codes' are precise.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use: 'Use this to discover the codes to pass to usas_disaster_spending.' This provides clear context for usage. It does not mention when not to use, but the guidance is strong for the intended use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes far beyond the readOnlyHint and openWorldHint annotations, detailing disclosure-suppression behavior (null vs 0), honesty measures (totalAvailable, HTTP 404 handling, schema drift protection), and the mixing of aggregation levels. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very long (multiple paragraphs) and includes extensive detail. While well-structured with bullet points and sections, it could be more concise for an AI agent. The length is justified by the API complexity but still reduces conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (10 parameters, no output schema), the description is highly complete. It explains the output structure, disclosure codes, error handling, and client-side pagination, leaving no critical gaps in understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description adds substantial context: format constraints (regex for area_fips, digit-only NAICS), that mode is a literal path segment, client-side pagination semantics for limit/offset, and the effect of hyphenated NAICS. This clarifies usage beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves BLS QCEW data (market size, employment, wages, location quotient) and distinguishes it from the rate-limited bls_timeseries API. It specifies the resource and the unique value proposition (un-rate-limited, keyless).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly provides when to use this tool (market-size/competition-density questions) and contrasts it with alternatives. It details required parameters (mode, year, quarter) and conditional parameters (area/industry), warns about hyphenated NAICS causing 404s, and explains client-side filters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond annotations (readOnlyHint, openWorldHint) by disclosing that the data is a curated, partial seed of 187 orgs, that the authoritative directory is auth-gated, and that the seed may be incomplete. It also describes the output format and pagination mechanism, providing full transparency about limitations and behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately concise, front-loading the purpose and then providing necessary detail. It could be slightly shorter, but every sentence serves a purpose (context, filtering, output, honesty note). Structure is logical with use cases and limitations clearly separated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description thoroughly defines the output format including the fields and pagination metadata. It also addresses the tool's limitations and provides instructions for extending the seed. The 4 parameters are fully explained in context. The description is complete for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
While the schema already describes each parameter (100% coverage), the description adds usage semantics: it clarifies that filters are applied client-side on the curated seed, specifies the range for limit, and mentions offset's relationship with pagination metadata. This adds practical meaning beyond the structural schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool lists US governments on the Bonfire platform and identifies itself as the directory for bonfire_search_opportunities. It uses a specific verb ('List'), a clear resource ('US governments on Bonfire'), and distinguishes from the sibling tool bonfire_search_opportunities by explaining the relationship.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: 'Feed a result's `org` to bonfire_search_opportunities' indicates when to use this tool first. It also explains that Bonfire has no keyless API, so this curated seed is the recommended starting point, and suggests an alternative method to extend the seed. This covers when to use and when not to rely solely on the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, openWorldHint), the description discloses many behaviors: honesty with countTotal=true, opaque cursor pagination, error handling (bad token throws 400, funderType invalid silently returns 0 but is rejected pre-fetch), AND-conjunctive multi-word queries, and the fact that leadSponsor.name is free text. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very long (approximately 500 words) and covers many details. While well-structured and front-loaded with the main purpose, it could be more concise without losing essential information. Some repetition (e.g., 'LIVE-CONFIRMED to narrow' appears multiple times) increases length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is highly complete for a complex search tool with 8 parameters and no output schema. It includes a pseudo-return schema, explains pagination behavior, error cases, and the honesty mechanism. It also references related tools (clinicaltrials_get_study, clinicaltrials_facet_counts) to complete the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, yet the description adds significant value: for 'sponsor,' it clarifies it's a fuzzy full-text name search (not a UEI); for 'funderType,' it explains the overlapping facet and the trap; for 'query.term,' it states AND-conjunctive behavior. These details are beyond the schema and aid correct parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches federally-registered clinical-research studies with entity enrichment, distinguishing it from clinicaltrials_get_study which returns full records. It specifies the resource (clinicaltrials.gov/api/v2/studies) and the scope (trial-registration axis). The verb 'search' and resource 'studies' are explicit, and it differentiates from related tools like clinicaltrials_get_study.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool versus alternatives, e.g., 'Feed a row's nctId to clinicaltrials_get_study for the full record + briefSummary.' It also states that the tool is for narrowing filters ('LIVE-CONFIRMED-narrowing filters ONLY') and explains that it is not for federal award data ('A registered trial is NOT a federal award'). This helps the agent choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint and openWorldHint. Description adds significant context: keyless API, honest counts (never faked), null handling, error categories, data vintage, aggregate nature. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is detailed but well-structured with sections, bullet points, and examples. While lengthy, it is front-loaded with essential info and each sentence adds value. Small gains in conciseness possible.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex tool with 6 parameters, no output schema, but rich constraints, the description covers input requirements, output format, pagination, edge cases, honesty policy, and dataset limitations comprehensively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with descriptions. Description adds validation patterns (\d{10}, ^[A-Za-z]{2}), reinforces at least one required, default size, and pagination details. Exceeds baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly defines the tool as looking up Medicare Part B provider utilization by NPI or state, listing specific fields and the CMS dataset. It distinguishes from sibling 'nppes_lookup_provider' as the demand-side complement. Verb+resource+scope are precise.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance: when to use (provider billing data, demand-side complement), constraints (at least one of npi/state required; providerType/hcpcsCode alone not enough), pagination, and honest error handling. Clearly differentiates from alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint and openWorldHint. The description goes far beyond by disclosing data provenance, the non-.gov nature, keyless access, honest pagination (cursor instead of offset), handling of missing fields (null vs ''), error responses (400, 429, 5xx), and SSRF protection. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Despite being long, every sentence is meaningful. The structure is logical: purpose, provenance, parameter details, honesty disclosures, error handling. Information is front-loaded and uses formatting (bold, capitalization) for emphasis.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but the description compensates by specifying the return structure (`{ opinions: [...] }`) and explaining error cases. It covers all 7 parameters, behavior, and edge cases, making it fully informative for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds significant value: explains mapping to API fields (e.g., `query` → q), validation rules, defaults (order: 'dateFiled desc'), usage of cursor as opaque token, and clarifies that natureOfSuit is not a dedicated filter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search US FEDERAL COURT OPINIONS (case law / litigation)' and specifies the resource (CourtListener). It provides a specific verb (search) and resource (opinions), with enough detail to distinguish from sibling tools like usas_search_awards or gao_protest_lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives extensive context: provenance, keyless access, optional token for rate limits, detailed parameter examples (e.g., court='uscfc' for contract claims), and notes on limitations (natureOfSuit folded into query). However, it does not explicitly state when not to use this tool or compare it to alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint and openWorldHint. Description adds extensive behavioral context: returns complete matching set, no fabricated totals, default date window, honest empty, data flattening, validation (date, recallNumber), and fixed host. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is thorough, covering purpose, parameters, return structure, error cases, and data handling. While lengthy, it is well-organized with sections (KEYLESS, HONESTY) and formatting (★). Every sentence adds necessary detail; no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 optional parameters, 100% schema coverage, no output schema, the description fully explains return structure, default behavior, error modes, and data processing. It is comprehensive and leaves no significant gaps for an agent to infer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (all 5 parameters documented). The description adds value by explaining CPSC field mapping (e.g., RecallDateStart), substring matching, and validation patterns beyond the schema. It goes beyond bare schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it looks up CPSC consumer-product recalls, listing specific data fields (title, hazard, remedy, etc.) and sources. It distinguishes itself from sibling tools like nhtsa_recalls (vehicles) and openfda (medical), establishing its unique domain.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use: consumer product recalls. Highlights keyless access, optional inputs, default 90-day window without filters, honest empty results, and error handling (invalid_input, schema_drift). Clearly distinguishes from alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint and openWorldHint annotations, the description details important behavioral traits: full-scan behavior, honesty about totalAvailable (exact match count, not page-limited), handling of 403 errors with multiple fallback scenarios (not-yet-disseminated vs genuine absence vs rate-limited), date validation pre-fetch, and normalization of dateFiled. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear paragraphs and bullet-like lists (e.g., the HONESTY section and date handling). It is relatively verbose but every sentence provides useful context. It could be slightly more succinct, but it earns its length through valuable detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (6 parameters, no output schema, integration with EDGAR's quirks), the description covers all essential aspects: data source, filtering, pagination behavior, error handling (403 scenarios), date validation, honesty about results, and normalization. It leaves no major gaps for an agent to misuse the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All six parameters are described in the input schema with 100% coverage. The description adds value by explaining how filters are applied (CLIENT-SIDE), that limit does not reduce download size, and that date validation occurs pre-fetch. While the schema already provides adequate descriptions, the tool description enhances understanding of behavior beyond syntax.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a per-day cross-filer SEC filing index, distinguishing itself from the sibling tool 'edgar_filing_index' by specifying it is ~30× smaller and reads one calendar day's index. It uses specific verbs like 'reads', 'FULL-SCANS', and 'returns' to clearly define the action and result.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly contrasts with the quarterly tool, stating it answers 'the monitoring/alerting question the quarterly tool cannot' and provides concrete examples like 'every 8-K filed on 2024-01-03' and 'watch a CIK day-by-day'. This gives clear guidance on when to use this tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds extensive behavioral details: full scan of the quarter, exact match count, handling of edge cases (future year, unpublished quarter, schema drift), and honesty about zero-match results. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but well-structured: purpose first, then details, then honesty notes, then error handling, then CIK vs. UEI distinction. Every sentence adds value, though some technical details (e.g., exact filename) could be trimmed slightly without loss of clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, no output schema), the description is highly complete. It explains the return structure (filings array fields), pagination, error handling, and edge cases. It compensates for the missing output schema by listing return fields and filingUrl. Sibling context is well-addressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds extra nuance beyond the schema for several parameters: year range and future year rejection, quarter future handling, formType exact match with no substring, companyContains as literal contiguous substring. This improves semantic understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads the entire SEC EDGAR filing index for a quarter and returns paginated results. It explicitly distinguishes itself from sibling tools like edgar_company_filings by noting it is the 'BULK-ENUMERATION primitive' that does not require a CIK.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool versus per-filer tools ('needs a CIK you already hold'). It includes use-case examples ('every 8-K in 2024 Q1') and clarifies error handling, such as HTTP 403 vs. empty results.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. Description goes beyond: reveals totalAvailable may be lower bound, 10000-result window, from rejection, and that 0 results with ciks/entityName require verification. Provides HONESTY note about SEC reporting limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured: front-loads core purpose, then lists parameters in order with clear syntax notes, followed by key behavioral notes. Every sentence adds value; no fluff. Efficiently packs parameter semantics and warnings without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex 7-parameter tool without output schema, the description is complete. It covers all parameters, pagination, result fields, behavioral quirks, and cross-references another tool (edgar_lookup_cik). Even notes key difference (CIK not SAM UEI/DUNS). Leaves no gaps for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Even though schema coverage is 100%, the description adds significant value: explains q exact-match syntax, ciks format and validation, from pagination limits, entityName fuzzy matching, and suggests combining ciks with entityName. Each parameter is enriched with non-obvious usage details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Full-text search across EDGAR filings, 2001-present' with specific verb and resource. While the purpose is obvious, it does not explicitly differentiate from sibling tools like edgar_company_filings or edgar_filing_index, leaving the agent to infer when to use this vs others.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Excellent guidance: explains when to use (full-text search with optional filters), how to use parameters (ciks vs entityName, from limits), and caveats (0 results not proof of absence, verify CIK via edgar_lookup_cik). Explicitly states page size is fixed at 100 and from > 9900 rejected.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses farOverhaulRisk caveat about codified FAR supersession, describes return fields (heading, revision date, kind, regulation, full text, prescribing section, ecfrUrl), and states that absent clauses return a not_found error. This goes well beyond the readOnlyHint and openWorldHint annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense and informative, front-loading the core purpose and key differentiator. It contains a useful caveat about farOverhaulRisk and error handling. While slightly long, every sentence adds value, so it earns a 4.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description fully enumerates return fields (heading, revision date, etc.) and error semantics. Given the tool's regulatory complexity, the description is complete and leaves no ambiguity about what the agent can expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions for all three parameters (clauseNumber, asOfDate, includePrescription). The description adds value by explaining the default behavior of includePrescription (true) and giving examples of clause formats. However, since schema already describes parameters, the description's incremental contribution is moderate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides authoritative FAR/DFARS clause text and its prescription (use condition). It explicitly distinguishes from the sibling ecfr_search by warning that ecfr_search mis-ranks exact clause numbers, so this tool is the correct one for exact lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance to use this tool instead of ecfr_search for exact clause numbers, with a concrete example of why (mis-ranking 52.212-4). Also notes keyless access and error behavior for absent clauses, providing clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes well beyond the readOnlyHint and openWorldHint annotations. It details how unresolved clauses are handled (404 vs errored buckets), deduping case-insensitively, gate flagging behavior, and the asOfDate parameter for point-in-time codification. It also notes 'Keyless' for authentication. This provides comprehensive behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively long but every sentence provides necessary detail. It is front-loaded with the main purpose. Some minor redundancy (e.g., 'TRUTHFUL by construction' could be integrated), but overall it is well-structured and efficient for the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (composing far_clause_lookup, error handling, gate flags, point-in-time) and the absence of an output schema, the description is remarkably complete. It explains each output field (clause text, prescription, regulation, gate flag) and the summary.total field. It covers edge cases like unresolved vs errored clauses and the purpose of each parameter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All four parameters have descriptions in the input schema (100% coverage), so the baseline is 3. The description adds extra context beyond the schema: it explains that clauses come from e.g., 52.252-2 lists, deduping is case-insensitive, defaults for boolean parameters (flagGates and includePrescription default true), and the asOfDate defaults to current up_to_date_as_of. This adds significant value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: 'Turn a solicitation's cited FAR/DFARS clause list into a proposal-ready compliance matrix.' It specifies the input (clause list) and output (matrix for Section L/M response). It distinguishes from siblings by noting it composes far_clause_lookup over multiple clauses, which is a distinct function from individual lookup tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool (have a list of clause numbers from a solicitation) and what it does not do: 'Does NOT parse the PDF solicitation to extract the clause list, and gives NO legal advice or compliance verdict.' It also notes 'for a Section L/M response,' providing context. While it doesn't directly compare to siblings, the purpose is self-contained.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. The description adds extensive behavioral context: roll-up honesty, that NIM is net interest income (not margin), no ratio fields, money in $thousands, counts unscaled, error handling (non-int year rejected, honest empty), and build-time disclosure. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is verbose (almost 500 words) and contains many details that could be streamlined. It is well-organized with bullet-like sections and a clear front-loaded summary, but could be more concise for an AI agent. Structure is good but length reduces conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 7 parameters, 100% schema coverage, good annotations, and no output schema, the description is exceptionally complete. It explains output structure, edge cases, roll-up behavior, and limitations thoroughly. An AI agent has all necessary context to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%. The description adds meaningful context beyond schema: for year, notes rejection of non-integers; for state, explains STALP vs PSTALP and roll-up codes; for charterClass, clarifies omission returns both rows; for sortBy/sortOrder, defines defaults. Adds value by explaining the meaning of enum values and constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides FDIC industry & state banking-sector annual aggregates, and distinguishes itself from the other four FDIC tools which are per-entity keyed on CERT. It uses specific verbs and resources: 'roll-ups', 'total assets, deposits, net income, equity & net interest income + structural counts'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool: to answer questions about the size of the US/state banking industry that entity tools cannot express without summing thousands of rows. Also provides alternatives: 'drill to institutions via fdic_search_institutions' and notes what the tool does not do (no name/city filter, no ratio fields).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations, describes data source, why name filter returns false empty, exact key filter behavior, and an honesty section detailing totalAvailable, changeDescription, date normalization, null vs 0, and error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Densely packed with useful information; front-loaded with main purpose. The honesty section is lengthy but necessary for behavioral trust, so not overly verbose for the value provided.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description fully explains return fields and edge cases (false empty, null vs 0, error handling). Very complete for a complex tool with 8 optional parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already covers all parameters with descriptions; the tool description adds extra context like cert being a stable key, state field differentiation (PSTALP vs STALP), and examples, but schema already does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is an event log for structural changes of FDIC-insured banks, listing specific event types and distinguishing from sibling tools like fdic_search_institutions and fdic_bank_failures.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use (e.g., for CERT-linked merger lineage) and when not to use (no name/city filter), and directs to resolve CERT via fdic_search_institutions first.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite annotations already providing readOnlyHint and openWorldHint, the description adds extensive behavioral details: fixed page size of 10, totalAvailable is a lower bound, deep-paging cap at ~200K, handling of genuine-empty vs ambiguous-empty pages, schema_drift detection, outage/error behavior, and amount representation. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but every sentence adds necessary information. It is front-loaded with the core purpose and authority, then filters, then output, then honesty section. No wasted words, though length could be slightly optimized for skimming.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description fully describes the return fields and content root (award or IDV). It covers edge cases, pagination guidance, and error handling. Given the tool's complexity and lack of output schema, the description is thorough and complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. However, the tool description adds significant context beyond the schema, such as how filters are combined (AND), the unreliability of offset beyond ~200K, and the meaning of PIID returning full base+mod chain. This added value justifies a score of 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies it searches FPDS-NG federal contract award actions, the authoritative system-of-record, and distinguishes itself from sibling tools like usas_* by stating it is the source for USAspending. It uses specific verbs and resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use structured filters only (NO raw query), requires at least one filter, explains AND-combined behavior, and advises preferring usas_* tools for rollups or sub-award graphs. Also includes pagination and deep-paging limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses all critical behaviors beyond annotations: off-by-default, honest error handling (no fake data), freshness meta, index warming, structured error messages, and 24h lag. Annotations already indicate readOnlyHint=true and openWorldHint=true, but the description adds substantial context about caching, failures, and return behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively long but well-structured with clear sections (BATCH, OFF BY DEFAULT, HONEST). Every sentence adds value, though some repetition could be trimmed. The length is justified by the complexity of the tool's behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (batch enrichment, caching, off-by-default), the description covers all necessary context: why it exists, how to enable, behavior when disabled, freshness, error handling, and limitations (24h lag). No output schema exists, but the description hints at returned fields. This is fully adequate for the agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'noticeIds' is fully described in the schema with 100% coverage, including constraints (1-100, 32-char hex). The description adds context about batch completion of a search page and the enrichment details, going beyond the schema. However, the schema already provides the essential constraints, so the description adds marginal value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that this tool is a batch enrichment for notice IDs from a CSV cache, completing fields that are null in sam_search_opportunities results. It explicitly distinguishes from sam_get_opportunity by noting it avoids one-per-notice calls. The verb 'BATCH-complete' and resource 'a sam_search_opportunities page' are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use (batch enrichment of a search page) and when not (real-time-critical fields should use sam_get_opportunity). It also details how to enable the tool (setting environment variables) and what happens when disabled. This clearly differentiates from siblings like sam_get_opportunity and sam_search_opportunities.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes keyless nature, default date range, and detailed behavior of excludeSummaryRows with server-side filter. Annotations (readOnlyHint, openWorldHint) are consistent and description adds significant behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph packed with essential information, front-loaded with purpose. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers return fields, parameter defaults, and critical behavioral nuance. No output schema, but the description sufficiently explains what the tool returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and description adds meaning: explains default startDate, clarifies excludeSummaryRows effect and server-side filter. No parameters lack clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides federal receipts, outlays, and deficit/surplus by month from the MTS table 1. It specifies return fields and distinguishes itself from siblings by being the highest-value budget-analysis tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly labels it as 'highest-value budget-analysis tool,' guiding usage. It does not explicitly list when not to use or alternatives, but the context of sibling tools implies its specific domain.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. The description adds behavioral context beyond annotations: it details the response structure (parent, hierarchy), active-contract count per code, and edge cases (nonexistent code returns parent:null, found:false). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with a clear flow from purpose to behavior to edge cases to example. It is slightly dense but efficient, earning a 4 for being informative without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single parameter and no output schema, the description is highly complete. It covers all input scenarios and edge cases. While it implicitly describes the response structure, it could explicitly mention the fields in hierarchy objects (code, title, contractCount, hasChildren) for full completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has one parameter with 100% description coverage. The description adds significant meaning: it explains how the parameter affects behavior (no filter vs. filter), and what the response contains for each case. This goes well beyond the schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: navigate the NAICS hierarchy (2→4→6 digit) with active-contract counts per code. It distinguishes from sibling tools like usas_autocomplete_naics by specifying hierarchy navigation and contract counts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool: to explore market scope, e.g., what's under NAICS 54. It provides precise usage guidance: no filter returns top-level sectors; with filter returns parent and direct children; includes drill-down instructions for hasChildren:true.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint and openWorldHint. The description adds extensive behavioral details: provenance (global, non-governmental), honesty about pagination, null handling, error conditions (429, 5xx, non-JSON). No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is detailed and well-structured with sections (provenance, honesty), but it is verbose. However, given the complexity of the tool and the need for trust posture clarification, the depth is justified. Could be slightly trimmed without losing value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description fully documents the return structure (datasets fields, _meta) and covers error handling, pagination, and trust posture. This provides complete guidance for agent invocation and interpretation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%. The description adds significant value beyond the schema by explaining the query constraint (≥2 chars), default behavior for openDataOnly, limit range, offset mapping to page[start], and the meaning of each parameter in API terms (→ q, filter[openData]).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Discover ArcGIS Hub datasets by keyword' and distinguishes it from sibling tools like Socrata and CKAN by specifying the coverage gap. It provides a specific verb and resource, making it easy for an agent to understand what it does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly defines when to use this tool (for ArcGIS Hub data not covered by others) and when not (global platform, not curated; mentions a planned row-query tool). It contrasts with socrata_query and gives clear prerequisites (query required, min length).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint and openWorldHint, but the description goes far beyond with a HONESTY section (H1-H4) detailing yearly snapshots, null handling for missing/suppressed data, no fabricated zeros, proper unit labeling, and error handling. This fully discloses the tool's behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, input details, HONESTY), but is quite lengthy. Some redundancy exists (e.g., area validation mentioned in both description and schema). However, every sentence adds value and the key info is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 params, no output schema), the description covers all necessary context: input validation, batch behavior, caps, error handling, output format, and relationship to siblings. It leaves no significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds critical semantics: the curated occupation enum with SOC mappings, SOC hyphen constraint, area formats (national/state/metro), datatype meanings, batch processing, and caps. This greatly enriches the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool benchmarks US occupational wages and employment from BLS OEWS, distinguishing it from sibling tools like gsa_benchmark_labor_rates and bls_timeseries. It specifies the data source, methodology, and purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use the tool (labor-rate benchmarking), names alternatives (gsa_benchmark_labor_rates, etc.), explains input requirements (at least one of occupation/soc), batch behavior, and caps. It also warns against common mistakes like using hyphens in SOC codes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description extensively discloses behavioral traits beyond the readOnlyHint and openWorldHint annotations: it details the API method (POST/JSON batch), keyless vs. keyed access, rate limits (v1 ~25/day, v2 ~500/day), data gap handling (null for unavailable, never 0), error throwing for non-success statuses, and tier disclosure. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is thorough and well-structured, with purpose front-loaded. While slightly verbose, every sentence serves a purpose (explaining usage, nuances, error handling). Minor redundancy could be trimmed, but overall high value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully explains the return format (series array with fields, observations with valueUnavailable, footnotes, etc.), covers edge cases (empty data, ambiguous raw IDs, error scenarios), and discloses tier information. It is complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the description adds significant meaning: it explains each enum value's meaning and units, warns that eci_total_comp/eci_wages are 12-month percent changes (not indices), clarifies raw seriesId charclass and behavior, and details startYear/endYear defaults and clamping.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches BLS time series for pricing/escalation, with specific examples like CPI-U, PPI, ECI. It distinguishes from sibling tools such as gsa_benchmark_labor_rates and sam wage determinations, providing clear context for use.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance: for federal contract escalation, EPA clauses, materials pricing, labor-rate context. It names alternatives (gsa_benchmark_labor_rates, sam wage determinations) and specifies input requirements (at least one of series/seriesId required, both combinable).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes far beyond the annotations (readOnly, openWorld) by detailing suppressed data handling (negative sentinels map to null), error behavior (missing key → invalid_input, 5xx → throws), return format, and pagination (complete results). This adds substantial context for safe usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is thorough but well-structured: purpose first, then key requirement, parameters, return format, honesty notes, error cases. While slightly long, every sentence contributes value. Front-loading the main purpose makes it efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (5 params, no output schema), the description is remarkably complete. It covers return structure, suppression behavior, error modes, key requirement, and pagination. Nothing essential is missing for a data query tool with readOnly and openWorld hints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 5 parameters have schema descriptions (100% coverage), and the description adds significant extra meaning: explains defaults (year='2023'), validations (naics ^\d{2,6}$), required combinations (state for county), and the client-side nature of limit. This enhances the schema's information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Market sizing by NAICS × geography — establishments, employment, and annual payroll from the US Census County Business Patterns (CBP) API'. It identifies the specific resource, verb, and dimensions, distinguishing it from sibling tools like geocoding or FRED queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is provided: requires a free CENSUS_API_KEY, parameters are explained (naics, geography, state, year, limit), and it instructs users to call api_key_status to check key requirements. It also clarifies when not to use (e.g., no key throws error) and mentions alternatives implicitly by focusing on this dataset.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, openWorldHint), the description details genuine empty returns, multiple matches, historical vintage behavior, HTTP 400 throws, and mandatory caveats. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with front-loaded purpose, parameter details, return shape, edge cases, and caveats. Slightly long but every sentence adds value; could be slightly more organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description fully covers return structure (matches with fields) and all behavioral aspects. Thoroughly compensates for missing schema given tool complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds meaning beyond schema: examples for address, explains default/compatibility matrix for vintage and benchmark, behavior for incompatible pairs. Schema coverage is 100% but description enriches understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it resolves a one-line US address to matched addresses and Census geographies for set-aside/place-of-performance analysis. It specifies the domain and distinguishes itself from siblings, none of which are geocoding tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use (resolving addresses for geographies) and when not (not authoritative for HUBZone/OZ determinations, requires SBA map/Treasury list). Provides guidance on handling empty results, multiple matches, and invalid inputs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes far beyond the annotations (readOnlyHint, openWorldHint) by detailing honesty checks (typeof validation, schema drift), the truncated invariant, overlapping behavior for Phase, missingStudiesCount caveat, error handling (invalid_input pre-fetch, throws for 4xx/5xx), and mandatory caveats. All disclosed behaviors are consistent with the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is comprehensive but long (over 500 words), making it somewhat verbose. However, it is well-structured with a clear hierarchy: purpose, input/output, honesty, error handling, caveats. The front-loading of the main purpose and key distinctions helps agents quickly grasp the tool's role.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of the tool and the lack of an output schema, the description provides a complete picture: input constraints, exact output structure (facets array and _meta), error scenarios, and caveats about data interpretation. It references the sibling tool for filtered counts, ensuring agents understand the broader context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the schema by explaining deduping, module-built comma-joining, the unique semantics of LeadSponsorClass (distinct from the search tool's funderType), and the effect of unlisted fields (invalid_input). It also clarifies that fields must be from the whitelisted ENUM list, complementing the schema's enum definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly defines the tool as an aggregate/statistical view providing exact per-value study counts over the entire ClinicalTrials.gov registry for whitelisted ENUM fields. It distinguishes itself from the sibling tool clinicaltrials_search_studies by calling itself the "DISTRIBUTION sibling" that gives whole-registry counts versus filtered totals.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool (for whole-registry distributions) versus the search tool (for filtered totals) and notes that these counts are not filterable. It cross-links the search tool for filtered counts, providing clear guidance on alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses honest count behavior, error handling for 4xx, 5xx, and schema drift, pagination details, numeric-string conversion, naming conventions, and vintage. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-organized with clear sections and front-loaded key info; slightly long but every sentence adds value given the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers return structure, _meta , error handling, data source limitations, and all aspects needed for agent usage despite no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and description adds clarity on required combination, validation patterns, defaults, and pagination behavior beyond schema definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Look up Medicare DMEPOS SUPPLIERS' with specific verb and resource, and distinguishes itself from sibling cms_medicare_provider_services.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly specifies required parameters (at least one of npi or state), optional size/offset, and provides context on when to use (supplier-level aggregate figures) and when not (no patient identifiers, not fraud determination). References sibling tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes far beyond the readOnlyHint and openWorldHint annotations, detailing exact behavior of count (exact grand total), conditions (server-side, self-policing, no silent drop), limit (hard cap 500, error on exceed), error handling (400, 404, HTML, 5xx, timeout, throw), the results mode, SSRF validation, PII disclosure, and the reach cap. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but well-structured with clear sections (main purpose, honesty details, results mode, error handling, SSRF, PII, caveat). Bold and emoji highlights aid readability. Every sentence provides unique, essential information, but could be slightly more concise without losing value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (7 parameters, no output schema), the description is fully complete. It covers all return fields (datasetid, index, results mode, fields, rows, _meta), error modes, constraints, security, disclaimers, and provides a concrete example. It leaves no behavioral gaps for an AI agent to infer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the baseline is 3, but the description adds substantial context: index default 0 and path interpolation, limit hard cap and rejection, offset policy cap, results mode explanation, datasetId SSRF validation and example, conditions limit and error behavior, properties optional. These details significantly enhance parameter understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool queries a CMS Open Payments DKAN datastore distribution by datasetId and index, specifies the exact API endpoint, and gives a concrete example dataset. It clearly distinguishes itself from sibling tools like 'treasury_query_dataset' by naming the specific data source and use case (healthcare financial relationships, conflict-of-interest vetting).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use context (healthcare industry-financial-relationship, COI-vetting, market intelligence not answerable by NPPES) and when-not-to (not a conflict-of-interest finding, fitness determination, exclusion determination). It recommends cross-checking with SAM, OFAC, OIG-LEIE, and states the reach cap of offset≤2000 as a deliberate targeted-lookup boundary, offering clear alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description provides extensive behavioral details beyond annotations: key requirement, error handling for various status codes (401/403, 400, empty, 429, 5xx, 200 non-JSON), pagination (offset, hasMore, nextOffset), honesty about totalAvailable, and verbatim data return. Annotations only provide readOnlyHint and openWorldHint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is lengthy but every sentence adds value. It uses bold for emphasis and organizes information logically (purpose, key requirement, parameters, error handling). Could be slightly more concise but justified given complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description explains return format, pagination, error responses, and dependency on dol_list_datasets. Complete for a data-fetching tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds meaningful context: required fields from dol_list_datasets, regex validation, paired filterField/filterValue as equality filter, default and max for limit, best-effort column selection for fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Fetch records from ONE US DOL dataset', specifying the verb and resource. It distinguishes from sibling tools by noting the dependency on dol_list_datasets for discovering datasets and agencies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use: to fetch records from a DOL dataset. Details prerequisites (requires DOL_API_KEY) and that without the key it throws an error. Also notes that dol_list_datasets and agency list stay keyless, providing guidance on alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses data source authenticity (de-XMLed, no fabrication), error modes (not_found, invalid_input, throws on outage), and issue date disclosure. Annotations already provide readOnly and openWorld hints, but description adds valuable behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is front-loaded with core purpose but contains multiple examples and error conditions. A bit lengthy but every sentence adds value. Slightly above average conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description explicitly states return fields (citation, alternateReference, heading, fullText, issueDate, ecfrUrl). Covers error cases. Complete for a single-section retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage, and description adds examples (e.g., '200.1' for grants, '52.204-21' for FAR), context for titleNumber (2=grants, 29=Labor), and date format validation. Adds meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verb 'Get' and resource 'FULL in-force text of ONE CFR section by citation.' It distinguishes itself from siblings ecfr_search (snippets) and far_clause_lookup (title 48).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (other 49 titles) and when not (FAR/DFARS prefer far_clause_lookup). Also explains optional date parameter default behavior.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, openWorldHint), the description discloses many behavioral traits: two-step pagination with ephemeral QueryID, honest totalAvailable (not page size), error handling (invalid inputs throw, outages throw, never fake empty), and the fact that naics filter is dropped upstream. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is quite long but densely packed with useful information. It is front-loaded with the main purpose. Could be slightly more structured (e.g., bullet points for parameters) but remains clear and efficient given the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 params, one required, special pagination, error modes, relationship to another tool), the description is remarkably complete. It covers return structure (state, facilities, summary, _meta), honesty guarantees, and all edge cases. No output schema, but description compensates by outlining the response fields.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds significant context: state enum is also SSRF/silent-zero guard; offset must be multiple of limit; facilityName typo silent zero; naics is best-effort and dropped; majorOnly/federalOnly are straightforward. Description enriches understanding far beyond schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: searching EPA-regulated facilities by US state with compliance/enforcement fields. It specifies the main resource (facilities) and action (search), and distinguishes it from sibling echo_facility_report by mentioning that tool as a follow-up.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance: state is required and also serves as SSRF guard; sic is a real filter while naics is best-effort and may be dropped; facilityName typos silently return 0; pagination details (limit/offset multiples, max 1000); and mentions feeding results to echo_facility_report for more detail.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint and openWorldHint. The description goes far beyond by detailing period identity, revision detection, null vs. 0 handling, error behaviors (404 vs. 5xx vs. throw), validation, injection prevention, and the 'canonicalOnly' dedup logic. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is comprehensive but verbose. It is front-loaded with purpose and relationship, then dives into extensive 'HONESTY' details. While every sentence adds value, the length could be slightly reduced for quicker parsing. However, given complexity, the structure is logical.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the full return structure, error handling, client-side filtering, period identity, and revision semantics. It addresses edge cases and provides sufficient detail for an agent to invoke the tool correctly, even without an output schema. All 9 parameters are well-documented in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds substantial context: explains how each parameter interacts with the upstream API (e.g., 'unit' as client-side filter, 'canonicalOnly' deduplication), clarifies edge cases (unit not present yields empty result with note), and enriches understanding of parameters like 'fy' and 'form' as client-side filters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as fetching a complete time-series for one filer and one XBRL concept. It explicitly distinguishes itself from siblings `edgar_company_facts` and `edgar_xbrl_frames` by positioning as a focused primitive for tracking trends and revisions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage context: 'track THIS filer's Assets/Revenues/NetIncomeLoss OVER TIME, and was it ever revised?' It also clarifies the middle position between its two sibling tools, implying when to use this vs. the others. It includes detailed behavioral notes that serve as guidelines for interpreting results.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses critical behaviors beyond annotations: deduplication logic, truthful error handling (throws on outage, no fake zero results), marking of non-current versions, and the farOverhaulRisk caveat. No contradiction with readOnlyHint annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is detailed but front-loaded with the core purpose; every sentence adds value. Slightly verbose due to comprehensive disclosure, but no unnecessary content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description thoroughly explains return fields (list, distinctSections, effectiveOn, isCurrent, etc.) and behavioral traits. Given tool complexity (5 params) and lack of output schema, this is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the description adds substantial meaning: explains that scope excludes GSAM/agency supplements, dedupeVersions collapses historical versions, partsOnly restricts to specific parts, and query is a semantic search. This enriches the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs semantic search over FAR/DFARS regulations, explicitly distinguishes itself from sibling tools like ecfr_search by highlighting compliance fixes, and positions itself as the front-door to far_clause_lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool (topic-based search) and contrasts with ecfr_search and far_clause_lookup, including details on scope options (far, dfars, both) and deduplication behavior.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes far beyond annotations by detailing data normalization (dates to ISO, financials to USD), handling of zeros and negatives, error behavior (throws on non-200), and disclosure of snapshot build time. All annotations (readOnlyHint, openWorldHint) are respected and expanded.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Long but well-structured with clear sections; front-loads purpose and use. Every sentence is informative, though some internal detail (e.g., HONESTY block) could be slightly condensed without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Fully covers return shape, pagination, sorting, filtering limitations, data integrity, and cross-tool linking. Lacks output schema but description provides return field list. Handles complexity of 7 parameters and many siblings comprehensively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds significant meaning beyond the schema: explains field name mappings (PSTALP vs STALP, FAILYR), provides examples for failYear, clarifies that sortBy unknown fields are rejected, and notes bounds for limit/offset. Schema coverage is 100%, but description still adds value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly identifies the tool as returning historical FDIC-insured bank failures and assistance transactions, with specific verb 'returns' and resource. Distinguishes from sibling FDIC tools by noting CERT links to fdic_search_institutions and fdic_institution_financials.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use (due diligence on failed institutions), how to filter (exact-key filters for state, failYear, cert), and what not to do (no name/city filter; alternative: resolve CERT via fdic_search_institutions). Includes defaults, limits, and examples.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint and openWorldHint. The description adds critical behavioral context: docs are pre-publication, no FR citation/page, may change/withdraw, returns leadDays and filing_type (special vs regular). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Concisely front-loads the core concept (leading indicator, ~1-to-several days ahead). Each sentence serves a purpose: mode explanation, return fields, limitations, cross-references. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description explains key return fields (leadDays, filing_type, agencies). It covers prerequisites (agency slugs via fed_register_list_agencies) and cautions on authoritative status. Complete for the tool's complexity and sibling context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% so baseline is 3. The description adds significant meaning: explains modes in depth, conditionality of date, notes that date rides conditions[available_on], and describes specialOnly filter as a stronger signal. This goes beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool accesses Federal Register Public Inspection documents (filed but not yet published), a pre-publication leading indicator. It distinguishes three modes (current, date, search) and contrasts with the authoritative fed_register_get_document, ensuring the agent understands its unique role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly explains when to use the tool (for early signals before official publication) and when not to (do not treat as authoritative; may change/withdraw). Recommends cross-checking with fed_register_get_document after publication and references fed_register_list_agencies for agency-slug resolution.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses read-only nature, real data (no fake empties), exact total count, opaque cursor, and upstream API behavior. Describes error handling and that nextPage URL is not surfaced. Goes well beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense and informative, but slightly long. However, every sentence serves a purpose, and it is well-organized with clear sections (parameters, returns, notes). No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, but the description fully documents the return structure (collection, packages fields, _meta cursor). Covers empty results, errors, and alternative tool routing. Complete for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds critical context: collection validation against live catalog, date filter meaning (lastModified vs dateIssued), opaque cursor explanation, and pagination limits. Adds value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches GovInfo packages in a collection with a date filter. It distinguishes from siblings by mentioning govinfo_list_collections and routing to ecfr_*/fed_register_* for specific collections.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Extensive guidance on when to use, parameter usage, pagination mechanics, error behavior, and alternatives for CFR/ECFR/FR collections. Includes explicit notes on correct pagination and date semantics.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and openWorldHint=true. The description adds extensive behavioral detail: client-side Luhn validation, filter dropping disclosure, honesty about active status interpretation, null handling (epochs), lower bound on total matches, rate limits (skip/limit policy), error handling (throws for invalid input or errors), and disclosure that personal addresses may be returned. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is thorough but very long; every sentence adds value but could benefit from better structuring (e.g., sections for modes, parameters, caveats). It is front-loaded with purpose but then dense. While not overly verbose for the complexity, it could be more scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (two modes, 11 parameters, no output schema), the description is remarkably complete. It explains return format, error handling, pagination constraints, and key caveats (e.g., totalIsLowerBound, practice locations separate from addresses). It also addresses what the tool does not cover (exclusions, sanctions), ensuring the agent uses it appropriately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, but the description adds significant meaning beyond schema: Luhn validation for `number`, wildcard rules for name fields, refiner-only behavior for `state` and `enumeration_type`, pagination policy for `skip` and `limit`, and exact-mode behavior for `number` (drops other filters). This enriches the agent's understanding of each parameter's role.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a keyless CMS/HHS NPPES NPI Registry lookup for healthcare provider validation, with specific verb 'lookup' and resource 'NPI Registry'. It distinguishes between exact NPI mode and search mode, and specifies the intended use case (due-diligence) and what it is not for (exclusions/sanctions).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use exact mode vs search mode, what parameters are required vs refiners (e.g., state and enumeration_type are refiners only), and how mode is inferred from the `number` parameter. Warns about filter dropping in exact mode and recommends cross-checking with SAM exclusions and OFAC for fitness determinations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description extensively discloses behavioral traits beyond annotations: NSF caps retrieval at 10,000 records (totalIsLowerBound), OR-tokenization of keywords, strict date format with silent mis-parsing, SSRF guard on state code, funds as strings, error handling (serviceNotification, schema_drift, outages). No contradiction with annotations (readOnlyHint, openWorldHint).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but highly information-dense. It is front-loaded with purpose and uses bold for key terms. Every sentence earns its place, but it could be more streamlined. Minor verbose phrases like 'LIVE-CONFIRMED-narrowing filters ONLY' could be simplified without losing meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully details the return structure (awards array with fields, _meta, error conditions, saturation behavior, and link to nsf_get_award). It covers limitations (10k cap), data types (strings to numbers), and edge cases (genuine empty vs. bad param). It is as complete as needed for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 100% schema coverage, the description adds substantial meaning: for keyword, it explains OR-tokenization and recommends single words; for offset, it explains the hard cap and invariant; for dateStart/dateEnd, it warns about format foot-gun; for ueiNumber, it clarifies exact SAM join. Each parameter's description provides practical context and edge cases beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches awarded NSF research-grant awards, explicitly distinguishes it from sibling tools (nih_reporter_search_projects for grants, nsf_get_award for full records), and provides the specific API endpoint. The verb 'search' and resource 'NSF research-grant awards' are precise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit when-to-use guidance: it is the grant counterpart of nih_reporter_search_projects; when to use narrowing filters to avoid the 10,000 cap; warns against multi-word keyword OR-tokenization; advises feeding a row's id to nsf_get_award for abstracts; and explains limitations like the silent-zero guard on state codes. It helps the agent decide between this and alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint=true annotation, the description details the integrityFlag values ('excluded' vs 'review_fapiis'), that fapiisRecords is always null with a _meta.fieldsUnavailable field, and that upstream failure surfaces as an error, not a fake clearance.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise yet comprehensive, front-loading the core purpose and parameter requirements, then systematically explaining return values and caveats. Every sentence adds necessary information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the absence of an output schema, the description fully documents the return object structure including nested fields, edge cases (null records, error handling), and the meaning of integrityFlag. This makes the tool's behavior completely transparent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage with descriptions for each parameter. The tool description adds value by noting that uei is preferred and that name drives an exclusions text search, providing practical guidance beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly defines the tool as a 'Keyless ONE-CALL integrity screen' that checks for exclusion verdicts and provides a pointer to FAPIIS records. It distinguishes itself from siblings by specifying it composes sam_check_exclusions and never returns a false 'clear'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states required parameters (at least one of uei/cage/name, with uei preferred) and explains when to use it (integrity screening). It also clarifies limitations: never returns 'clear' keylessly, and FAPIIS records are unavailable without a key.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, openWorldHint), the description discloses keyless limits: missing fields in list rows, client-side date filtering, and true server-side count. It also explains how responseDeadline windows are applied, providing valuable behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but well-structured, starting with purpose, then key behavioral notes, parameter details, and limits. While slightly verbose given the tool's complexity, it is efficient and front-loaded with essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description covers all critical output fields (noticeTypeCode, postedDate, responseDeadline, daysUntilResponse, uiLink) and edge cases (null deadlines). It also explains data.totalRecords and how to obtain full details via sam_get_opportunity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although input schema covers 100% of parameters, the description adds critical context: default noticeType (['r','p','s']), opt-in codes, and client-side filtering behavior for organizationName and responseDeadline. This significantly aids correct parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: it surfaces pre-solicitation notices (Sources Sought, Presolicitation, Special Notices) before an RFP exists. It uses specific verbs ('surfaces', 'catch') and distinguishes itself from paid feeds and sibling tools like sam_search_opportunities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance (pre-solicitation shaping) and when-not-to (when NAICS/setAside/placeOfPerformance needed, use sam_get_opportunity). It also explains client-side filtering for responseDeadline and organizationName, offering clear alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, openWorldHint), the description explains that the tool is keyless, uses a specific API, returns structured data with fields, and notes the limitation that not all allowlisted hosts are indexed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is information-dense and front-loaded with the main purpose, but the single paragraph structure could be slightly improved for readability; still concise and effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains return format (list of fields plus totalAvailable) and caveats about federated catalog, making it complete for a search tool with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context to all three parameters: q provides examples, domain explains scoping and limitation, limit gives range and default. Schema coverage is 100% and description adds value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool finds Socrata dataset 4x4 ids by keyword, distinguishing from the sibling socrata_query tool by noting that discovered ids can be fed to socrata_query.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies required input q, optional domain and limit, and provides explicit guidance on when to use socrata_query instead (when federated catalog does not index a host).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses behavior beyond annotations: it states that per-recipient award counts are null (not 0) and only obligated $ is returned. This adds context to the readOnlyHint and openWorldHint, without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences efficiently cover purpose, limitation, alternatives, and use case. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately explains what is returned (top recipients by obligated $) and what is not (counts). It also provides a concrete use case, making the tool's scope and limitations clear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is low (25%: only agency described). The description adds meaning by tying parameters to the use case (agency × NAICS × fiscal year) and implies their role in filtering. However, it does not detail the setAside parameter format or values, which would have enhanced clarity further.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it aggregates share-of-wallet on USAspending, specifying inputs (agency, NAICS, fiscal year) and output (top recipients by total obligated $). It distinguishes from sibling tools by noting that per-recipient award counts are not returned, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use the tool (e.g., 'who wins at VA in 541512?') and when not to (when counts are needed), directing to alternatives like usas_search_awards_by_recipient or usas_get_recipient_profile. This provides clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. Description extends with units (percent vs dollars, scaling), null handling (null vs 0, CBLR mapping), response structure, error behavior (throws on non-standard responses), and disclosure of no recomputation. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Despite length, every sentence earns its place. Structured logically: purpose, parameters, units, nulls, CBLR, honesty, disclaimer. Front-loaded with main purpose. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 6 parameters, no output schema, but high schema coverage, the description is exceptionally complete. It explains response structure (ratios array with fields), error handling, units, null behavior, and relationship to sibling tools. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds significant value: explains cert's relation to fdic_search_institutions, reportDate format and effect, sortBy enum meaning and default, sortOrder default, limit/offset constraints. Every parameter is enriched beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves FDIC counterparty risk ratios for one institution by certificate number, using specific verbs (get, express) and resource (risk ratios). It distinguishes itself from sibling balance-sheet tools by calling itself the 'soundness lane' they cannot express.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use this tool for risk ratios and contrasts with balance-sheet tools. Provides prerequisite: input cert from fdic_search_institutions. Also notes it is not a soundness rating or failure prediction, guiding appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses source provenance (OSCAL catalog from github.com/usnistgov/oscal-content), version handling (live from moving main branch), behavior for withdrawn controls (statement null, incorporatedInto), client-side filtering (no query API), and error handling (throws on download failure or truncated catalog). Annotations already declare readOnlyHint and openWorldHint, but description adds substantial behavioral context beyond those.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with purpose in first sentence. All sentences add value: parameter usage, output details, honesty section. No fluff; length is appropriate for the tool's complexity. Well-structured with clear sections.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, description fully covers return fields including id, family, title, status, statement, guidance, incorporatedInto, and enhancements. Addresses edge cases (withdrawn controls, client-side filtering, error behavior). Complements sibling tools and provides complete context for usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and description adds significant meaning: explains controlId exact matching (case-insensitive, zero-padding normalized), family accepts code or name substring, keyword is case-insensitive substring over title+statement, limit/offset for pagination. Also details output structure for each parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool looks up NIST SP 800-53 Rev 5 security and privacy controls, identifies it as keyless requirement backbone for FedRAMP/CMMC/RMF, and distinguishes from sibling tools cve_lookup and cisa_kev_lookup by specifying it covers the control/requirement side versus the vulnerability side.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance on when to use: searching by controlId, family, keyword with pagination. Provides alternatives (cve_lookup, cisa_kev_lookup) for vulnerability side. Clearly states limitations: requirement text only, not applicability encoding, and that the catalog is from a moving branch so version can shift.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, openWorldHint), the description discloses extensive behavioral traits: result structure, alias matching mechanism, behavior on failure (throws), minMatchQuality/type/program as post-filters, and snapshot freshness in _meta. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is detailed but compact, front-loading the key purpose and legal context. Every sentence adds value, using structured sections like safety notes to organize information efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description fully explains the return format and edge cases (potential_matches vs no_name_match, never 'clear'). It covers all aspects needed for correct usage, including failure scenarios and caveats about transliterations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the description adds significant context beyond field names: e.g., name trimming/rejection, list loading behavior, type inference, program local filtering, and minMatchQuality only affecting returned matches. Each parameter's behavior is clarified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it screens a name against OFAC's SDN and Consolidated lists, highlighting its unique coverage (including AKAs) and distinguishing it from SAM exclusions. This leaves no ambiguity about the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly explains when to use this tool (for OFAC checks) and provides crucial safety guidelines (no_name_match is not clearance, results require human review, failures throw). It addresses alternatives by noting what SAM exclusions do not cover.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![mcp-sam-gov MCP server](https://glama.ai/mcp/servers/cliwant/mcp-sam-gov/badges/card.svg)](https://glama.ai/mcp/servers/cliwant/mcp-sam-gov)

Score Badge

Copy to your README.md:

[![mcp-sam-gov MCP server](https://glama.ai/mcp/servers/cliwant/mcp-sam-gov/badges/score.svg)](https://glama.ai/mcp/servers/cliwant/mcp-sam-gov)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/cliwant/mcp-sam-gov'

If you have feedback or need assistance with the MCP directory API, please join our Discord server