Verilex Data

Server Quality Checklist

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Latest release: v0.3.3
Disambiguation2/5
Many tools have overlapping purposes, causing ambiguity. For example, multiple tools handle changes (e.g., dex_changes, econ_changes, holder_changes) or statistics (e.g., dex_stats, econ_stats, holder_stats) across different datasets, making it easy to confuse which tool to use for a specific data type. While descriptions help, the sheer number of similar tools increases misselection risk.
Naming Consistency3/5
Naming conventions are mixed but generally readable. Some tools follow a verb_noun pattern (e.g., get_sec_filing, lookup_patent), while others use noun_verb (e.g., dex_changes, holder_stats) or query_ prefix (e.g., query_indicators, query_holders). This inconsistency is noticeable but not chaotic, as most names are descriptive enough to infer function.
Tool Count2/5
With 75 tools, the count is excessive for a single server, making it feel heavy and overwhelming. While the server covers multiple domains (e.g., crypto, economic data, legal records), the tool surface could be consolidated (e.g., generic 'get_changes' or 'get_stats' with parameters) to reduce complexity and improve usability.
Completeness4/5
The tool set is highly complete, covering CRUD-like operations across diverse datasets such as crypto, economic indicators, legal records, and weather. Each domain includes lookup, search, statistics, and change-tracking tools, with few obvious gaps. Minor gaps might exist in update/delete operations, but the surface supports comprehensive data retrieval and analysis workflows.
Average 3.7/5 across 75 of 75 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on March 18, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
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?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only states cost and source, missing details on side effects, response structure, or any destructive behavior. The read-only nature is implied but not explicit.
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 at two sentences plus a cost/source note. It avoids redundancy and is front-loaded with the core purpose, though it lacks structured formatting for readability.
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, the description should explain what the returned changes look like (e.g., data format, fields). It does not, leaving significant ambiguity about the tool's output, which is critical for an agent to use it 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?
The input schema has 100% coverage with descriptions for both parameters. The tool description adds no further semantic value beyond what the schema already provides, so a baseline score of 3 is appropriate.
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 retrieves recent changes to Polymarket microstructure data since a timestamp, specifying the resource and action. However, it does not distinguish from sibling tools like pm_changes or pm_micro_stats, which may have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions a timestamp and source but lacks context on prerequisites, exclusions, or comparison to similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden of behavioral disclosure. It indicates a read operation ('Get current values') and notes a cost, but does not mention rate limits, authentication requirements, or any side effects.
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 two sentences, front-loading the purpose and listing examples. It is concise and well-structured, though the inclusion of cost and sources adds value without unnecessary verbosity.
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 names data sources (FRED, BLS, BEA) and cost, which provides useful context. However, lack of output schema and details about the response format leaves the agent uncertain about return values. For a query tool, this 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?
Input schema coverage is 100%, so the baseline is 3. The description adds context that series uses FRED series IDs and that category, frequency, and limit are filters, but this largely echoes the schema descriptions. It does not significantly enhance parameter understanding.
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 retrieves current values for economic indicators, listing examples like CPI, GDP, and unemployment. It is specific and distinguishes the tool from generic 'get' tools, though it does not explicitly differentiate from similar economic tools like econ_stats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions a cost of $0.01 per query, which is a usage guideline, but it does not specify when to use this tool versus alternatives, nor does it provide any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses cost and source but does not explain what 'changes' exactly means (e.g., whether it's incremental additions or full diffs) or any rate limits. More behavioral context is needed.
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 wasted words. The purpose is front-loaded, and additional info (cost, source) is compactly provided.
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 tool with two parameters and no output schema, the description covers purpose, cost, and source but does not explain what the output looks like or how 'changes' are represented. It is adequate but leaves some gaps.
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 both parameters have clear descriptions in the schema (ISO 8601 for 'since', min/max for 'limit'). The description adds no additional parameter information beyond the schema, so baseline score of 3 applies.
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 'Get recent changes to DEX trade data since a given timestamp' with a specific verb and resource. It distinguishes itself from sibling tools like dex_stats or query_dex_trades by focusing on 'changes' but does not explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description only mentions cost per query, which is a usage hint but does not specify when to use this tool versus alternatives or any when-not-to-use criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must cover behavioral traits. It mentions cost and source but lacks details on data freshness, rate limits, error handling, or what happens with invalid tokens. For a data-fetching tool, this is insufficient.
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, no fluff. Front-loaded with main purpose and outputs, followed by cost and source. Every sentence adds value.
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?
Lists key output metrics but does not cover return format, pagination, or error handling. Without output schema, description could be more descriptive, but it provides moderate completeness for a simple data 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 coverage is 100% and describes both parameters (token and chain) adequately. Description adds no extra meaning beyond schema, so baseline score of 3 is appropriate.
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 gets Gini coefficient and distribution metrics for a token, listing specific outputs like top-10/top-50 percentages and supply distribution buckets. It is specific to concentration analysis, but does not explicitly distinguish from sibling tools like holder_stats or query_holders.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description provides cost ($0.02 per query) and source, but no guidance on when to use this tool versus alternatives such as holder_stats or holder_changes. No when-not or explicit context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description must carry the full burden. It mentions cost ($0.01 per query) and data source (on-chain), but does not disclose read-only nature, rate limits, pagination, or data freshness. A read hint is absent, which is critical 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise: three short sentences with clear front-loading of purpose. No extraneous text; every sentence adds value (purpose, cost, source).
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 tool is simple (2 parameters, no output schema), so the description covers basic aspects. However, it lacks details on what 'changes' means, output format, and pagination behavior (limit parameter mentioned only in schema). Some gaps remain.
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%, with both parameters described adequately. The description adds minimal extra meaning beyond the schema (e.g., 'since a given timestamp' matches the parameter description). Baseline 3 is appropriate.
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 retrieves recent changes to Polymarket data since a timestamp, using a specific verb and resource. However, it does not differentiate this from sibling tools like pm_arb_changes or pm_micro_changes, which also retrieve changes for Polymarket.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks any 'when to use' or 'when not to use' context, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavioral traits. It mentions cost ($0.03/query) and data source (USAspending.gov), but lacks details on rate limits, error handling, 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?
Three sentences clearly stating purpose, output, and cost/source. No unnecessary words, and the key action is front-loaded.
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, the description gives a partial picture of return data (agency, total awards, contract counts). However, it omits other possible fields, result format, and behavior for empty results, making it moderately complete.
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 three parameters (agency, period, limit). The description adds no additional semantic context beyond the schema, meeting the baseline for high 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?
The description clearly states the tool retrieves vendor rankings by total award value and lists output fields (agency, total awards, contract counts). However, it does not differentiate from sibling tools like 'contract_stats' or 'search_contracts', which could also provide government spending data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or situations where other tools might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full burden. Only mentions cost and source, but omits whether operation is read-only, any side effects, rate limits, or exact nature of 'changes'.
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?
Two sentences with no fluff. Efficient but could include more detail without being verbose.
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?
Output schema absent; description does not explain return format or field types. Lacks details to distinguish from similar tools 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%, so baseline is 3. Description adds no extra meaning beyond schema; cost mention is per query, not per 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?
Clearly states verb 'Get', resource 'recent changes to whale wallet data', and scope 'since a given timestamp'. Distinct from sibling 'changes' tools through specific resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 vs alternatives like holder_changes or whale_movements. Mentions cost and source but not context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It only notes cost and a vague 'significant' threshold, but fails to define 'whale', describe data sorting, pagination, or rate limits. Minimal insight beyond the basic purpose.
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?
Two clear sentences plus a cost/source note. Information is front-loaded and efficient. However, the cost detail, while useful, could be considered extraneous as it is not standard for tool descriptions.
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?
Given no output schema and no annotations, the description is too sparse. It does not explain what a 'whale wallet' is, whether results are sorted, or how pagination works. For a tool with 5 parameters, this leaves significant gaps.
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%, so the description adds little beyond what the schema already provides. The term 'large' loosely relates to min_usd, but no new constraints or examples are given. Baseline score 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 'large balance changes across whale wallets' and describes the type of data (inflows, outflows, transfers). It distinguishes from sibling tools like whale_changes and whale_stats by specifying 'large' and 'whale wallets'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 the many sibling whale-related tools (e.g., whale_changes, whale_stats). It mentions cost and source but no decision criteria or exclusions.
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?
With no annotations, the description carries the full burden. It discloses the cost ($0.01 per query) and source (on-chain data), which adds transparency. However, it does not mention whether the operation is read-only, any pagination, rate limits, or what happens with empty results. The behavioral coverage is adequate but not thorough.
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 very concise – two sentences plus cost and source. The main action (get recent position changes) is front-loaded, and every sentence is relevant. No wasted words.
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?
Given the lack of an output schema, the description should explain return values but only vaguely says 'shows buys, sells, and position size changes.' It omits the structure of results, pagination details, ordering, and default behavior. The tool has four optional parameters and no required ones, but the returned data format is not 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 input schema has 100% parameter description coverage, so the baseline is 3. The description does not add new meaning to the parameters beyond what the schema provides (e.g., market_id, wallet, hours, limit). It only hints at output content, not parameter behavior.
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 it retrieves recent position changes by whale wallets on Polymarket, including buys, sells, and position size changes. It distinguishes itself from siblings like pm_whales or pm_stats, but could be more explicit about how it differs from similar tools like pm_changes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives. It mentions cost and source but lacks context on when to prefer this over pm_changes, pm_arb_changes, or other related tools. No exclusions or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must cover behavioral traits. It mentions 'real-time telemetry' and that it provides 'early warning', but does not state read-only nature, data latency, rate limits, or any constraints. Some transparency but significant gaps.
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 key information. Every word serves a purpose, no redundancy. Highly concise and well-structured.
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, description provides good overview of return fields (populations by tier, entry/exit rates, velocity). Also includes data source. Complete enough for a query tool with well-defined 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 covers all 3 parameters with descriptions, and description adds no further meaning beyond what is in the schema. Baseline 3 for high 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?
The description clearly states the tool retrieves near-liquidation cohort signals with specific metrics (health factor tiers, entry/exit rates, velocity). It differentiates by mentioning 'Liquidationbot real-time telemetry' as source, but does not explicitly contrast with siblings like query_protocol_risk or query_network_stress.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 over alternatives. Implies use for early warning on critical health factor entries, but no exclusions, prerequisites, or comparisons to other query tools in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only mentions cost and sources. It does not disclose whether the operation is read-only, rate limits, or other behavioral traits. Significant gap given the lack of annotation coverage.
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, front-loaded with the verb, and includes essential details without redundancy. 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?
For a simple query tool with three optional parameters and no output schema, the description adequately covers what data is returned and mentions sources and cost. Minor omission: could note default values for days and limit.
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%, so baseline is 3. The description adds no additional meaning beyond the schema descriptions. It implies date-range filtering via 'upcoming' but doesn't elaborate on format or defaults.
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 verb 'Get upcoming economic data releases' and specifies resources (dates, impact, prior values, forecasts). While it distinguishes from generic siblings, it does not explicitly differentiate from closely related tools like 'query_surprises' or 'econ_stats'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description includes cost and data sources, but provides no guidance on when to use this tool versus alternatives. With many economically themed siblings, explicit when-to-use/when-not-to-use information is missing.
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?
With no annotations provided, the description adds useful behavioral context: cost per query, source freshness (daily updates), and return type (matching entries with scores). However, it does not state whether the tool is read-only or if it has any side effects.
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 (3 sentences) with no filler. It front-loads the purpose and includes key details like cost and update frequency.
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 covers return values (matching entries with scores) but misses error handling, limits, or pagination. It is adequate for a straightforward screening 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 coverage is 100%, so description does not need to add much. The description does not elaborate on parameters beyond what the schema already provides, so baseline score of 3 is appropriate.
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 action (screen), the resource (address/name/entity against sanctions lists), and lists specific lists (OFAC SDN, EU, UN, UK). It distinguishes from siblings like search_sanctions by focusing on screening versus searching.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives like search_sanctions or screen_companies. The description provides context (cost, source) but lacks when-to-use or when-not-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must cover behavioral traits. It adds cost ($0.005 per query) and source, but omits critical details: data freshness, rate limits, pagination behavior (though limit parameter hints), whether the tool is read-only, or what constitutes a 'change'. The bare minimum is provided; more context is needed for safe invocation.
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 zero fluff. First sentence states purpose and core behavior; second adds cost and source. Front-loaded and efficient. Every clause 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?
Tool is simple (2 params, no output schema, no nested objects). The description covers purpose, cost, and source. However, it lacks explanation of output structure, data freshness, or what 'changes' entails (e.g., incremental updates vs full diff). Without an output schema, the agent lacks expectations on return format, making it less complete than ideal.
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% (both parameters have descriptions). The description adds no extra meaning beyond the schema. The 'since' parameter is detailed with an example format, and 'limit' has min/max/default. Baseline 3 is appropriate as the 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 the tool retrieves recent changes to Polymarket arbitrage data since a given timestamp. The verb 'Get', resource 'recent changes to Polymarket arbitrage data', and scope 'since a given timestamp' are explicit. It effectively distinguishes from sibling tools like pm_arb_opportunities (which likely lists current opportunities) and pm_arb_stats (aggregate statistics).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. With numerous Polymarket-related siblings (e.g., pm_arb_opportunities, pm_arb_stats, pm_changes), the description does not clarify the specific scenario for using 'changes' versus other tools. No exclusion or context about prerequisites or limitations is 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?
With no annotations, the description carries full burden. It discloses cost ($0.01 per query) and source, adding some behavioral context. However, it omits whether the tool is read-only, caching, rate limits, or error handling, which is necessary for safe invocation.
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 short sentences that are front-loaded with the main purpose. Every sentence adds value (action, output description, cost, source). 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?
The tool is relatively simple with only optional params. However, without an output schema, the description should hint at the output structure (e.g., list of opportunities with fields). It mentions what it shows but not the format, leaving some incompleteness.
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 100% of parameters with descriptions. The description adds no additional parameter semantics beyond what the schema provides, so baseline 3 is appropriate.
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 fetches cross-market arbitrage opportunities on Polymarket, specifying the resource and action. However, it does not explicitly differentiate this tool from siblings like pm_arb_changes or pm_arb_stats, preventing a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions cost and source but does not address use cases, prerequisites, or exclude scenarios, leaving the agent without clear decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden for behavioral disclosure. It only mentions the data source and update frequency but does not state that the tool is read-only, whether it returns a list of patents, or any pagination behavior. Key behavioral traits like authentication needs or rate limits are 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 two sentences, front-loading the purpose and listing key capabilities. It is efficient with no wasted words, making it easily scannable for an AI agent.
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 provides source and update frequency, but lacks details about the output format (e.g., list of patents, fields returned, pagination). For a search tool with no output schema, this gap limits the agent's ability to interpret results 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?
All 8 parameters are fully described in the input schema (100% coverage), so the description adds no extra meaning beyond the schema. The listed filter fields in the description are redundant with schema. Baseline score 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 searches US patents from a specific database (USPTO PatentsView) and lists the filterable fields such as patent title, assignee, inventor, etc. It distinguishes from siblings like lookup_patent (which likely retrieves by ID) and patent_stats (which provides statistics), 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus sibling tools like lookup_patent or patent_stats. It does not specify prerequisites or conditions under which the search is appropriate, nor does it mention alternative tools for different use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description only discloses cost and sources. It does not address behavioral traits like idempotency, data freshness, or any side effects, leaving the agent without crucial operational 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?
Two sentences convey purpose, key features, cost, and sources. No wasted words, and critical information is front-loaded.
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 purpose and cost are clear, the description omits output format, error conditions, and behavioral constraints. Given three optional parameters and no output schema or annotations, more completeness is needed for reliable agent 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?
All three parameters have descriptions in the input schema (100% coverage). The description adds no additional parameter-specific meaning beyond what the schema already provides, 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?
Description clearly states the tool returns actual vs consensus comparison for economic releases, including beat/miss magnitude, patterns, and market impact. It distinguishes from siblings like query_releases by specifying the focus on surprises.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as query_releases, econ_stats, or econ_changes. The description mentions cost and sources but lacks explicit context for selection.
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?
No annotations exist, so the description carries the full burden. It discloses search scope, fields, ranking, cost, and data sources. Absent are details on pagination, rate limits, or idempotency, but the core behavior is adequately communicated.
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?
Extremely concise: three short sentences covering purpose, searchable fields, cost, and sources. Front-loaded with key action 'Full-text search'. Every sentence adds value without redundancy.
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 search tool with a simple schema and no output schema, the description is moderately complete. It explains input and sources but omits output format, ranking details, and ties to sibling tools. Could be improved by noting when 'screen_sanctions' might be preferred.
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%, so baseline is 3. The description adds examples of valid search inputs (name, alias, etc.), which is helpful but not extensive. While it clarifies the 'q' parameter's intent, it does not significantly extend beyond schema descriptions.
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 over sanctions entries, specifying searchable fields and ranking. However, it does not explicitly differentiate from sibling tools like 'screen_sanctions' or 'sanctions_stats', so it loses a point for lack of distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs. alternatives, nor any conditions or limitations. The cost information is useful but does not replace usage direction. This is a significant gap given the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions the tool is 'premium' and 'cross-dataset,' implying aggregation and potential cost, but it does not detail authentication requirements, rate limits, or any side effects. This leaves significant gaps for an AI agent.
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 wasted words. It front-loads the purpose and concisely lists the output types in the second sentence. Every sentence adds value, and the structure makes the tool's capability immediately clear.
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 annotations and no output schema, the description adequately covers the input and expected outputs. It lists multiple data types returned. However, it lacks details about the response format, pagination, or limitations, which would be helpful for a premium endpoint. Still, for a single-parameter tool, it is mostly complete.
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 single parameter 'identifier' is fully described in the input schema with examples (ticker, CIK, name). The description confirms these possibilities but adds no additional semantic value beyond what the schema already provides. With 100% 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: 'Get a unified company profile across all Verilex datasets.' It specifies the input types (ticker, CIK, name) and lists the output categories (SEC filings, OTC data, patents, trademarks, court cases), distinguishing it from sibling tools that focus on individual data types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Sibling tools like lookup_otc_ticker, lookup_patent, and get_sec_filing offer individual lookups, but the description does not explain when the unified profile is preferable or when to use specific tools instead.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses data sources and a 'coming soon' note, but does not detail limitations, update frequency, or error conditions. The note about availability may confuse agents.
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?
Three concise sentences cover purpose, input, output, and source. Information is front-loaded with the action and returns. The 'coming soon' note is placed last and is relevant.
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 tool, the description covers location input and returned fields. However, it lacks explanation of parameter selection trade-offs, output format details, and the 'coming soon' status is ambiguous. Sibling tools exist but are not cross-referenced.
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 parameter descriptions. The description adds that lat/lon or ZIP can be used, but this is already implicit in the schema. No new parameter-level meaning is provided.
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 'Get' and resource 'current weather conditions'. The term 'current' distinguishes it from sibling tools like get_weather_forecast and get_weather_history, and the specific fields returned are listed.
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 current weather is needed, but does not explicitly mention alternatives or when not to use this tool. Sibling tools exist but are not referenced, leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. It only says it's a paid query and from on-chain analytics, but does not mention rate limits, authentication, or any side effects. For a read operation, minimal disclosure.
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 action and resource. Cost and source are useful and succinctly stated. No unnecessary words.
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, so description should hint at the response format. It does not mention what fields are in a 'change' or how results are structured. Incomplete for a tool that returns data.
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%, so the description does not need to add much. It adds no extra meaning beyond the schema, which already describes 'since' and 'limit' with formats and defaults. 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?
Description clearly states 'Get recent changes to token holder data' with a specific time constraint ('since a given timestamp'). Differentiates from siblings like holder_concentration and holder_stats which focus on snapshots or aggregates.
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?
Description implies usage (when you need recent holder changes) and mentions cost and source, but does not explicitly state when to avoid this tool or list alternatives. No comparison with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, description carries full burden for behavioral disclosure. It only mentions cost ($0.005 per query) and source (on-chain analytics), but omits critical details like rate limits, data freshness, or read-only nature. No confirmation that operation is non-destructive.
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?
Two sentences efficiently convey purpose and cost/source. Information is front-loaded with the main action. Could be slightly more concise by merging the cost sentence, but overall clear and compact.
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?
Description lists metrics included but does not specify the output structure or field names, which is important since no output schema is provided. With four parameters and no return format details, the description is adequate but incomplete for full contextual understanding.
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 has 100% description coverage; each parameter is already documented with examples and enums. The tool description adds no additional semantic value beyond what the schema provides, earning the baseline score of 3 for high 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?
Description clearly states the tool retrieves volume statistics for DEX trading pairs, listing specific metrics (24h volume, 7d volume, trade count, volume trends) and sourcing. It distinguishes from sibling tools like query_dex_pairs and query_dex_trades by focusing solely on volume 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?
Description implies usage for DEX volume queries but provides no explicit when-to-use or when-not-to-use guidance compared to alternatives. It mentions cost and source but lacks directives on suitable contexts or exclusions.
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?
No annotations are provided, so the description carries full burden. It discloses cost and data source, but does not mention side effects, authentication, rate limits, or that the tool is read-only. The behavioral info is adequate but not comprehensive.
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, no filler. Cost and source are efficiently appended. 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?
Given no output schema, the description adequately covers return fields, cost, and source. However, it omits default values for chain (ethereum) and limit (25) which are in the schema but not explicitly stated. Still mostly complete for a straightforward query 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?
Input schema has 100% description coverage, so the schema already documents parameters. The description does not add semantic meaning beyond the schema; it only reinforces the token parameter's purpose. Baseline 3 is appropriate.
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 verb 'Get' and the resource 'top holders for a token contract address', and lists returned fields. However, it does not explicitly differentiate from sibling tools like holder_changes or holder_concentration, though the focus on 'top holders' is distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions cost per query but provides no guidance on when to use this tool versus alternatives (e.g., holder_stats for summary data, holder_changes for changes). No context on prerequisites or best use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. It states it's 'free' but does not mention authentication, rate limits, or data freshness. The read-only nature is implied, but not explicitly stated.
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 communicates purpose and scope. No unnecessary 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?
Given zero parameters, no output schema, and no annotations, the description is adequate but minimal. It covers the basics but could improve by specifying the return format (e.g., JSON) or any limitations.
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, baseline is 4. The description adds value by listing the specific statistics returned (series, categories, date range, data source), which enhances understanding beyond the empty 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 'Get statistics about the economic indicators dataset' with specific outputs (total series, categories, date range, data source). It distinguishes from siblings like crypto_stats or contract_stats by specifying 'economic indicators'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. 'Free endpoint' is mentioned but does not help in decision-making. No exclusions or context for 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. It mentions cost ($0.005 per query) and that it 'Shows markets below a liquidity threshold with spread metrics,' implying a read operation. However, it does not detail side effects, rate limits, or how results are returned.
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 convey purpose, function, cost, and source. No fluff; every sentence adds useful 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?
With 2 parameters and no output schema, the description covers the tool's function adequately. It mentions output includes 'spread metrics' and cost. Lacks details on error states or result format, but acceptable for a straightforward 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 descriptions for both parameters. Description adds value by mentioning 'spread metrics' and cost, contextualizing the output beyond the 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?
Description clearly states it 'Detect markets with thin order books' and mentions liquidity threshold and spread metrics. However, it does not explicitly differentiate from sibling tools like pm_micro_depth or pm_micro_stats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Context signals list many similar tools (e.g., pm_micro_depth, pm_micro_stats) but the description provides no comparison or selection criteria.
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?
With no annotations, the description carries full burden. It discloses cost and data source, but does not mention rate limits, data freshness, or potential errors. The read-only nature is implied but not explicit.
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, front-loaded with the main action. Every sentence adds value: action, output fields, cost, and source. No unnecessary text.
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 three optional parameters and no output schema, the description covers the output fields and cost adequately. However, it lacks details on pagination or ordering defaults beyond the schema.
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 parameters have schema descriptions (100% coverage). The description adds value by explaining the output fields (wallet address, PnL, win rate, active markets), which is not in the 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 retrieves top Polymarket wallets ranked by PnL, volume, or position size, and lists the output fields. It is specific but does not explicitly differentiate from sibling tools like pm_signals or pm_changes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions cost and data source but provides no guidance on when to use this tool versus alternatives. No when-not-to-use or alternative recommendations are 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?
With no annotations, the description provides some transparency by noting the data source (USPTO TSDR and bulk XML) and weekly updates. However, it does not disclose behavior like pagination, rate limits, or read-only nature.
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 core action, followed by filter list and source. 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?
Given 7 optional parameters and no output schema, the description provides adequate context for a search tool but lacks details on return format, sorting, or default behavior.
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 description adds only a summary of filter fields. It does not add new meaning beyond the schema, but it consolidates the parameters concisely.
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 it searches US trademarks from the USPTO and lists filterable fields, making the purpose obvious. However, it does not explicitly differentiate from sibling tool lookup_trademark, which likely retrieves 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching trademarks with filters, but lacks guidance on when to use versus alternatives (e.g., lookup_trademark for specific records). No exclusions or prerequisites are mentioned.
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?
No annotations provided, so description carries full burden. It discloses cost ($0.005 per query) and source (Consolidated sanctions lists), but lacks details on rate limits, pagination, side effects, or how results are ordered. Basic transparency but incomplete.
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 short sentences: first states purpose, second clarifies output type, third adds cost and source. No fluff, front-loaded, 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?
No output schema, so description should explain return structure. It only mentions 'additions, removals, modifications' but not fields within each. No pagination or rate limit info. Adequate for a simple list tool but leaves gaps.
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%; both parameters are well-described in the schema. The description adds no new meaning beyond the schema (mentions ISO 8601 format for 'since' which is already in schema, and default 50 for limit). Baseline 3 applies.
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 starts with 'Get recent changes to sanctions lists since a given timestamp', clearly specifying the verb (get), resource (changes to sanctions lists), and scope (since timestamp). It further explains it shows additions, removals, modifications, which distinguishes it from siblings like search_sanctions or sanctions_stats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. It does not mention exclusions, prerequisites, or compare to other tools like search_sanctions. The cost mention is a minor hint but not explicit usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description does not disclose behavioral traits beyond listing output fields. With no annotations, the full burden falls on the description, which lacks details on rate limits, data freshness, error responses, or performance considerations.
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 with no redundant information. Every word contributes value: 'statistics about the Polymarket arbitrage dataset' followed by a scoped list of outputs and a note on cost.
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 input parameters and no output schema, the description names the output fields (total opportunities, etc.), which is mostly sufficient. However, it could mention the response format or update frequency for a stats endpoint, though 'last updated' covers staleness.
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?
Input schema has zero parameters (100% coverage), so the description does not need to add parameter details. The baseline for 0 parameters is 4, and the description correctly omits param info.
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 aggregate statistics for the Polymarket arbitrage dataset, listing specific data points (total opportunities, average spread, markets analyzed, last updated). This distinguishes it from siblings like pm_arb_opportunities (likely listing individual opportunities) and pm_arb_changes (tracking changes).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Among many sibling tools (e.g., pm_stats, pm_arb_changes), there is no contextual hint for selecting this specific endpoint. The description only notes it's a 'free endpoint', which is insufficient context.
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 no annotations, the description adds useful behavioral details: cost per query, source (on-chain analytics), and update frequency (hourly). It implies a read-only operation. 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 clear sentences plus cost and source info. All information is relevant and front-loaded. No wasted 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?
The description covers return fields (address, balance, token holdings, last activity), cost, and source. It omits default sort and pagination details, but the input schema handles those. Without an output schema, this is fairly complete.
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 each parameter already has a description. The description repeats the filter categories but adds no additional meaning beyond the schema. Baseline 3 is appropriate.
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 lists whale wallets with specific filters (blockchain, min balance, token, activity). It provides a clear verb-resource pair, but does not explicitly differentiate from sibling tools like lookup_whale or whale_changes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., lookup_whale for individual whales). The description lists filters but does not specify context or exclusions.
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?
No annotations provided. The description adds cost per query and data sources (FRED, BLS, BEA) but lacks details on side effects, rate limits, or pagination. It adequately discloses that it is a paid read operation.
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: purpose, cost, sources. No fluff, every sentence adds value.
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 purpose, cost, and sources but lacks information about the output format or return structure. Given no output schema, the description should ideally mention what the response looks like. It is adequate for a simple tool but not fully complete.
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 has 100% coverage with descriptions for both parameters. The description does not add any additional information about parameters beyond what the schema provides, so baseline 3 applies.
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 changes to economic data, using a specific verb (Get) and resource (recent changes). It distinguishes from siblings like econ_stats, dex_changes, holder_changes, etc.
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 cost and data sources but does not explicitly state when to use this tool vs alternatives or provide exclusions. Usage is implied but not guided.
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?
With no annotations, the description carries full responsibility. It discloses the data source (NOAA ISD) and return format (hourly observations), but does not mention authentication, rate limits, or whether zip/lat/lon are all required or optional. The 'coming soon' note provides partial transparency about availability.
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 plus a note, front-loaded with core purpose and return fields. Every part is informative and unnecessary words are avoided.
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 covers return data and source, it lacks details on parameter combinations (e.g., location flexibility) and potential constraints. The 'coming soon' note is important for context but does not fully compensate for missing output schema or parameter behavior.
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 does not add extra meaning to parameters, such as explaining the relationship between zip, lat, and lon (e.g., whether any one is sufficient or all required).
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 historical weather data and lists the returned data fields (hourly observations of temperature, humidity, wind, precipitation, pressure). It distinguishes from sibling tools like get_current_weather and get_weather_forecast by specifying 'historical' and 'date range'.
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 past weather data but does not explicitly compare to siblings or state when-not to use. It includes a note 'coming soon' which may indicate current unavailability, but lacks 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool retrieves statistics (a read operation), but does not disclose any behavioral traits such as response format, caching behavior, rate limits, or authentication needs. For a simple tool with no parameters, the description is minimally 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 that are tightly packed with relevant information: the action, resource, and specific metrics. Every word earns its place, and the structure is front-loaded with the core purpose.
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 the tool has no parameters, no output schema, and is a straightforward stats endpoint, the description provides a reasonable overview. However, it omits details about the output data structure (e.g., whether values are numbers or strings, if there are nested objects). For full completeness, the description should list all expected fields.
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 baseline score is 4 per the rubric. The schema coverage is 100%, and the description adds value by enumerating the types of statistics returned, which helps the agent understand what to expect.
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 'Get statistics about the OTC company dataset' and lists key metrics (total companies, financials, shell risk score, timestamp, data source). It clearly distinguishes from sibling tools that target other datasets like contract_stats or crypto_stats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The only usage guidance is 'Free endpoint', which indicates no cost but does not clarify when to use this tool over sibling stats tools (e.g., company_profile, contract_stats). No context on when not to use or alternatives is 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?
No annotations provided, so description carries full burden. It mentions cost per query and on-chain source but lacks details on data freshness, rate limits, or interpretation of confidence scores. Behavioral traits are partially disclosed but not comprehensively.
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 with three sentences: purpose, aggregation detail, and cost/source. No redundant information, each sentence adds value. Front-loaded with the main action.
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 should explain return values, but it only mentions 'directional signals per market' without specifying fields or structure. It is adequate for a simple query tool but incomplete regarding output format. Parameters are well-covered.
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 has 100% description coverage for all three parameters, each with clear descriptions. The tool description does not add additional meaning beyond what the schema already provides, 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?
Description clearly states the tool provides smart money flow signals showing top trader positioning, with a specific verb 'Get' and resource 'signals'. It distinguishes from siblings like pm_whales and pm_stats by focusing on aggregated directional signals per market.
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 cost and source but does not provide explicit guidance on when to use this tool versus alternatives. Sibling tools exist (pm_whales, pm_stats, etc.) but no when-to-use or when-not-to-use context 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?
Without annotations, the description carries the transparency burden. It states the data source (Liquidationbot real-time telemetry) but does not disclose behavioral traits like side effects, permissions, or computational cost.
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 front-loaded sentences with no extraneous words, efficiently conveying purpose, outputs, and coverage.
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 lists output metrics and coverage but lacks details on return structure (e.g., array format), which would be ideal given no output schema.
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%, so the baseline is 3. The description adds context about protocols and chains covered but does not enhance parameter understanding beyond the schema's own 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 liquidation pressure and stress scores for DeFi lending protocols, listing specific metrics, protocols, and chains, which distinguishes it from sibling tools like query_network_stress.
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 DeFi protocol risk monitoring but lacks explicit guidance on when to use alternatives or when not to use this tool, such as for non-lending or network-level stress.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It mentions cross-referencing datasets but does not disclose behavior like result format (list vs. details), pagination, or performance characteristics. The limit parameter is the only behavioral hint.
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 action, no fluff. Each sentence adds value: first defines the high-level purpose, second enumerates filter groups and data sources.
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 14 parameters and multi-dataset cross-referencing, the description covers the filter options and sources well. However, with no output schema, it fails to hint at the response structure (e.g., list of tickers or full profiles), leaving a completeness 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 coverage is 100%, so baseline is 3. The description adds context by grouping filter types (financial, IP, litigation) and listing data sources, but does not add detailed semantics beyond what the schema's descriptions already provide.
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 companies using financial, industry, IP, and litigation filters, and cross-references multiple datasets. The verb 'screen' and specific filter types distinguish it from other search tools like search_sec_companies.
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 effectively implies this tool is for multi-criteria screening of companies. It does not explicitly state when not to use it or name alternatives, but the context of sibling tools suggests other lookup options for specific queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It states 'Get statistics' implying a read-only operation, but does not disclose potential rate limits, authentication requirements, data freshness, or caching behavior. For a zero-parameter endpoint, this is a minimal disclosure.
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: the first lists the data returned, the second identifies the endpoint as free. No wasted words, front-loaded with purpose.
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 outputs but lacks details on how statistics are computed, any limitations (e.g., data update frequency), or error handling. Given no output schema, additional context would help agents understand robustness.
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 has zero properties (100% schema description coverage), so the baseline is 4. The description does not add parameter information because there are none, 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 the verb 'Get' and the resource 'statistics about the trademark dataset', listing specific data items (total trademarks, status breakdown, etc.). It distinguishes from sibling tools like 'lookup_trademark' which is for individual queries, and 'query_trademarks' which likely returns full records.
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 aggregated stats but does not explicitly mention when to use this tool versus alternatives like 'lookup_trademark' or 'query_trademarks'. The 'Free endpoint' note is a minor guideline but lacks when-not-to-use or context-specific guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral traits. It only notes 'Free endpoint,' which addresses cost but not side effects, safety, or whether the tool modifies data. A read-only query is assumed, but not explicitly confirmed. This is insufficient for full transparency.
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 front-loads the key purpose and specifics. Every word is necessary and informative. No wasted or redundant text.
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 (no parameters, no output schema, no annotations), the description is fairly complete. It lists the types of statistics returned (total awards, agencies, date range, data source), which is sufficient for an agent to assess relevance. Lacks mention of data freshness or formatting, but this is minor for a stats-only 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?
The input schema has no parameters (0 params), so the baseline score is 4 per the rubric. The description does not need to add parameter semantics, and it correctly does not add any superfluous 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 it gets statistics about the government contracts dataset and lists specific details (total awards, agencies, date range, data source). The verb 'Get' and the resource 'government contracts dataset' are specific, and the tool name and title reinforce this. Siblings like 'crypto_stats' or 'dex_stats' are for different datasets, so it is well-distinguished.
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 'Free endpoint' which is a usage guideline (cost), but it does not explicitly state when to use this tool versus alternatives like 'search_contracts' or 'top_vendors'. The sibling tools are for different datasets, so usage context is implied, but lacking explicit when-not 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?
With no annotations, the description carries the burden. It discloses that the tool is free and the data source (Liquidationbot multi-chain telemetry), which adds behavioral context. However, it omits details like update frequency, caching, or error behavior, leaving gaps for the agent.
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 redundant information. It front-loads the purpose and includes essential details (metrics list, free, source). Every word earns its place, achieving high conciseness.
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 zero parameters and no output schema, the description provides a solid overview of what the tool returns. It lists the core metrics and mentions the data source. It could be slightly more complete by indicating the output format, but the listed metrics give sufficient context for an agent to understand the tool's value.
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?
There are zero parameters, and the schema coverage is 100% (empty object). Per guidelines, baseline is 3. The description does not need to add parameter information, but it also does not clarify any implicit inputs that might be expected.
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 statistics about the crypto intelligence dataset, listing specific metrics (total signals, executions, networks, protocols, date range). The verb 'Get' and explicit resource differentiate it from sibling stats tools like 'dex_stats' which focus on different domains.
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 'Free endpoint', implying no cost, but does not provide explicit guidance on when to use this tool vs. alternatives or any exclusions. The usage context is minimal, leaving the agent to infer applicability.
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?
No annotations are provided, so the description carries the full burden. The term 'Get' implies a read-only operation, and a stat endpoint with no parameters is inherently low risk. However, the description does not explicitly state that no data is mutated, nor does it discuss rate limits or authentication. It is adequate but lacks explicit assurances.
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 front-loads the key purpose (statistics about DEX dataset) and includes specific details. No unnecessary words or repetitions; every phrase 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?
For a simple stat tool with no parameters and no output schema, the description provides a reasonable list of what the response includes (total trades, pairs tracked, etc.). It does not specify the response format or structure, but given the simplicity, it is mostly complete. Adding a note about the response type (e.g., JSON object) would elevate it to a 5.
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?
There are no parameters, so the input schema is effectively fully covered. The description does not need to explain parameters beyond what the schema shows. With zero parameters, a baseline of 4 is appropriate, and the description adds no misleading 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 retrieves statistics about the DEX trading dataset, listing specific items (total trades, pairs tracked, etc.), and includes the qualifier 'Free endpoint'. This verb ('Get') and resource ('statistics about the DEX trading dataset') are precise, and the context differentiates it from sibling stats tools like contract_stats or crypto_stats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as dex_changes or query_dex_trades. The only extra note is 'Free endpoint', which addresses cost but not usage context or conditions. An agent has no way to distinguish when to call this tool over similar stat 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?
No annotations are provided, so the description must carry the full burden. It discloses that the tool returns metadata and document URLs, which is adequate for a simple read operation, but lacks details on error handling or permissions.
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 are highly concise, with the first stating the core action and resource, and the second listing return contents. No extraneous text.
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 retrieval tool with one parameter and no output schema, the description is sufficiently complete. It explains what the tool does and the kind of data returned, though it omits error cases or format specifics.
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 covers the parameter description (100% coverage), but the tool description adds context about what the retrieved metadata includes (company info, form type, etc.), providing additional 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 action ('Retrieve') and resource ('SEC filing') with the specific identifier ('accession number'), and differentiates from sibling tools like search_sec_filings by emphasizing 'single' filing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives such as search_sec_filings or other related tools. The conditions for use are implied but not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only adds that this is a 'Free endpoint', hinting at no cost, but fails to disclose other behavioral traits like read-only nature, required authentication, rate limits, or data freshness beyond the 'last updated' field. The minimal disclosure leaves significant gaps for agent decision-making.
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 clear sentence that front-loads the purpose and outputs. Every element serves a purpose, with no redundant 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?
Given no output schema, the description lists the returned fields, which equips an agent with essential information. However, it lacks mention of the response format (e.g., a JSON object with those fields) and any edge-case behavior. Still, for a simple endpoint, it is mostly 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?
The input schema has zero parameters (100% coverage), so the description does not need to explain parameters. The description adds value by stating what the endpoint returns, but does not go beyond that. Baseline score of 4 is justified.
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 gets statistics about the token holder dataset, listing specific items (total tokens, total holder records, chains covered, last updated). It effectively distinguishes from sibling tools like holder_changes and holder_concentration by focusing on aggregate counts rather than changes or concentration metrics.
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 by listing what the endpoint returns, but it does not explicitly state when to use this tool over alternatives (e.g., for overview vs. detailed changes). Given the many sibling tools, a brief note on use cases or selection criteria would improve clarity.
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?
With no annotations, the description adds behavioral context: cost, data source, and what details are returned. However, it does not mention side effects, permissions, or error handling, leaving some behavioral aspects unclear.
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, front-loaded with the primary action, and every sentence adds value (purpose, return details, cost, source). No wasted 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?
Given no output schema, the description adequately explains return content (modifications, sub-awards, performance history) and provides cost and source. It is missing information on error scenarios (e.g., invalid ID), but overall is sufficiently complete for a single-parameter lookup.
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% for the single parameter. The description adds slight context by specifying 'federal contract award ID', but does not significantly enhance understanding beyond the schema's 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 looks up a single federal contract award by ID, and differentiates from sibling tools like search_contracts which would search multiple records. It specifies the resource and action unambiguously.
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 a known ID but does not explicitly state when to use this tool vs alternatives like search_contracts. It mentions cost per query, which indirectly guides usage, but lacks explicit when-not or alternative comparisons.
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?
With no annotations provided, the description carries full burden. It mentions cost per query ($0.009) and source (on-chain intelligence), which are useful behavioral traits. However, it does not disclose rate limits, authentication requirements, or what happens if the address is not found.
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 extremely concise: two sentences plus cost and source. Every sentence adds value—purpose, return data, cost, and provenance. No wasted 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?
The description covers the tool's purpose, return data, cost, and source. It lacks mention of error handling or data freshness, but for a simple lookup tool with no output schema, it provides sufficient context 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter (address) and its description. The tool description adds no additional meaning beyond what the schema already provides (e.g., example address). 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 verb 'look up', the resource 'cryptocurrency address', and the returned data (label, risk score, entity name, category, risk flags, compliance tags). It distinguishes itself from sibling tools like lookup_contract (smart contracts) and lookup_npi (medical providers) by specifying the domain.
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 does not explicitly state when to use this tool versus alternatives like lookup_contract for contract addresses or lookup_whale for whale addresses. It only provides cost information and source, implying but not stating that it is specifically for address labels.
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?
No annotations exist, so description carries full burden. It discloses the source and lists returned fields, but does not mention side effects, rate limits, or authentication needs. For a simple read operation, this is adequate but not comprehensive.
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, no redundancy. First sentence states core purpose, second lists return fields. Efficient and well-structured.
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 (one required param, no output schema), the description covers the essential context: what the tool does, what it returns, and the data source. Missing error handling or format details, but overall complete for a straightforward lookup.
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% for the single parameter 'serial', which includes pattern and description. Description reinforces the purpose but adds no new semantic meaning beyond the schema. 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?
Description clearly states the action (look up), resource (US trademark), and identifier (USPTO serial number). It distinguishes itself from sibling tools like 'query_trademarks' which imply batch queries.
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?
Implicitly, it's for a single trademark when you have a serial number, but no explicit when-to-use or alternative guidance is provided. Siblings like 'query_trademarks' suggest broader searches, but the description does not clarify this.
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?
With no annotations provided, the description carries full burden. It discloses that the tool retrieves and displays order book data (read-only behavior) and notes cost and source. However, it does not mention rate limits, data freshness, or any side effects (though presumably none). Basic transparency adequate for a simple query tool.
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 front-loaded with the core purpose, followed by details of output and cost. No redundant or irrelevant information. Every sentence serves a clear role in defining 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 tool has 3 parameters, no output schema, and no annotations, the description provides a solid overview of what it does and includes cost information. It explains the types of outputs (order book depth, spread width, liquidity at various price levels). However, it could be more complete by specifying the granularity of price levels or whether pagination applies, but overall it is sufficiently informative for a straightforward query 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 coverage is 100% with each parameter described in the schema (market_id, min_liquidity, limit). The tool description does not add additional meaning beyond these descriptions; it repeats 'liquidity' but not parameter specifics. Thus, baseline score 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?
Description clearly states the tool retrieves market depth and bid-ask spread analysis for Polymarket markets, with specific outputs like order book depth, spread width, and liquidity at various price levels. The verb 'Get' and resource are explicit, and the tool is well-distinguished from siblings like pm_micro_thin by its focus on depth analysis.
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 market depth queries but provides no explicit guidance on when to use this tool versus alternatives like pm_micro_stats or pm_micro_thin. It does mention cost ($0.003 per query) as a usage consideration, but lacks when-not-to-use or alternative tool referrals.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry behavioral disclosure. It only mentions 'free endpoint' and 'last updated,' missing details on rate limits, data freshness, or authentication needs. Minimal transparency.
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, no wasted words. The first sentence states the action and content, the second clarifies it is free. 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?
Given no parameters and no output schema, the description is fairly complete. It covers the main purpose and key data points, though it could mention format or update frequency.
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 schema coverage is 100%. The description adds value by listing the specific statistics returned, which 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 the tool provides statistics about the Polymarket resolution dataset, listing specific metrics (total markets tracked, upcoming resolutions, resolution sources, last updated). It distinguishes from siblings like pm_resolution_calendar and pm_stats.
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 notes it is a free endpoint, implying no cost, but does not specify when to use this tool versus alternatives like pm_resolution_calendar or pm_resolution_lookup. Usage context is implied but not explicit.
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?
Discloses cost ($0.001 per query) and source (on-chain DEX analytics), but with no annotations, it misses other common behavioral traits like idempotency, permissions, or side effects. Implies read-only.
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 clear front-loading: purpose, filters, and output plus cost/source. No unnecessary 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?
Given no output schema, describes return fields (liquidity, volume) and includes source and cost. Could mention pagination or ordering but adequately covers basics for a listing 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 descriptions cover 100% of parameters, and the description adds minimal new param info beyond reiterating the filters. The extra context (cost, source) is not parameter-specific.
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 lists available trading pairs on DEXs and specifies filtering by chain, base/quote token. Distinguishes from siblings like query_dex_trades by mentioning returns of pair details with liquidity and volume.
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 for listing DEX pairs, but no explicit when-to-use vs alternatives or exclusions. Does not mention sibling tools like query_dex_trades for trades.
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?
Without annotations, the description covers cost ($0.003) and source (on-chain analytics), but lacks details on data freshness, pagination, or rate limits. It is adequate but not comprehensive.
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, front-loaded with purpose, then filters, then cost/source. No unnecessary 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?
Covers purpose, filters, output fields, cost, and source. Missing explicit time range for 'recent', but limit default is in schema. Fairly complete for a query 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 coverage is 100%, so baseline is 3. The description lists filters already in schema and adds output field names but no additional parameter semantics 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 'recent swap transactions' with specific filters (pair, chain, min size, DEX). It distinguishes from sibling tools like query_dex_pairs and query_dex_volume by focusing on individual trades.
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 recent trade queries but does not explicitly mention when to use alternatives or provide exclusion criteria. No reference to sibling tools or 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It mentions the data source (Liquidationbot real-time telemetry) but does not clarify whether the operation is read-only, idempotent, or any potential side effects. This lack of transparency leaves ambiguity for the agent.
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, each serving a distinct purpose: the first states the tool's action and composition, the second provides use case and source. No wasted words, efficiently communicating 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?
While the description gives the core output (0-100 composite score), it lacks details on the response structure (e.g., single object or array per network). Given the optional network filter and no output schema, a bit more structure would improve completeness, but it is still functional for a simple query 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 coverage is 100%, with both parameters described in the schema. The description adds a high-level understanding of the output (stress score) but does not elaborate on parameter behavior beyond the schema. Achieves baseline without enhancing.
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 retrieves network-level market stress indices, combining liquidation intensity, gas costs, and failure rates. It specifies the output is a 0-100 composite score per blockchain, distinguishing it from sibling tools that focus on other metrics.
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 'useful for macro risk assessment across DeFi lending,' providing a clear context. However, it does not explicitly mention when not to use or compare to alternatives like query_protocol_risk, missing some guidance for tool selection.
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?
No annotations are present, so the description carries the full burden. It discloses cost and data source but omits details on authentication, rate limits, pagination, or error handling. The read-only nature is implied but not stated.
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 clear front-loading of purpose. Every sentence contributes essential information (search criteria, return details, cost, source). 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?
With no output schema, the description partially covers return fields but lacks structure details. It addresses cost and source adequately. Minor gaps in pagination and error handling, but sufficient for a search tool with 6 optional 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 coverage is 100%, so the baseline is 3. The description only lists filter options without adding meaning beyond the schema, such as how parameters interact or formatting details.
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 federal contract awards by multiple criteria (agency, vendor, NAICS, keyword) and returns specific details. It distinguishes itself from sibling tools like 'lookup_contract' by emphasizing broad search capabilities.
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 through listing search options and mentions cost and source, but lacks explicit guidance on when to use this tool versus alternatives like 'lookup_contract' 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It explains that it scans all Verilex datasets with a configurable lookback, but omits details like auth needs, rate limits, or result handling.
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 with clear front-loading: purpose, signal list, and scanning scope. No redundant 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?
For a tool with 3 fully described parameters and no output schema, the description adequately covers purpose and scope. Minor gap: output format not hinted.
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 description adds little beyond repeating parameter names and listing signal types already in the schema enum.
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 ('Get') and resource ('alpha signals') and lists six concrete signal types, clearly distinguishing it from siblings like pm_signals by mentioning Verilex datasets.
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 alpha signals but provides no explicit guidance on when to use this tool versus alternatives like pm_signals, nor any when-not-to-use conditions.
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?
With no annotations, the description carries full burden. It states 'Free endpoint' and lists returned data, but omits behavioral details like read-only nature, rate limits, or error handling. Adequate but not comprehensive.
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 are clear and front-loaded. No wasted words; every sentence provides 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?
Given no output schema, the description adequately lists the statistics returned. It could benefit from mentioning output format or whether results are paginated, but for a simple stats endpoint, it is sufficiently 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?
No parameters exist, so schema coverage is effectively 100%. The description adds no parameter details, which is appropriate. Baseline score of 4 is justified.
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 statistics about the Weather dataset, listing specific elements (stations covered, date range, data sources, last updated). This clearly distinguishes it from sibling tools like get_current_weather, get_weather_forecast, and get_weather_history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description only mentions 'Free endpoint,' but does not specify context, prerequisites, or scenarios for usage.
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?
With no annotations, the description carries the full burden. It discloses that this is a read operation returning provider details but does not mention any limitations, required permissions, or side effects. The behavior is straightforward, so a middle score is appropriate.
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 clearly states the purpose and return value. Every word provides value 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?
Given the simple single-parameter tool with no output schema, the description sufficiently covers what the tool returns (name, address, specialty, enumeration date). No additional context is needed for an agent to use this 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?
Schema description coverage is 100% for the single parameter npi, which already includes a regex pattern and description. The tool description adds no additional semantic meaning 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 clearly states it looks up a single healthcare provider by their 10-digit NPI number and specifies the returned details (name, address, specialty, enumeration date). It uniquely distinguishes this tool from siblings like lookup_contract or query_npi_providers.
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 an NPI number is available but does not explicitly state when to use this tool versus alternatives such as query_npi_providers for bulk lookups. No when-not-to-use or exclusions are provided.
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?
No annotations are present, so the description bears full responsibility. It discloses a key behavioral trait: 'Cost: $0.02 per query,' which is valuable for agent planning. The verb 'look up' implies a read-only operation, but this could be more explicit. Overall, it provides useful transparency beyond just functionality.
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 (3 sentences) and front-loaded with the primary action. It efficiently conveys purpose, outputs, cost, and source without unnecessary words. Slightly more structure could improve readability, but it is well within acceptable bounds.
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 compensates by listing the types of information returned (oracle, rules, sources, timeline). It also covers cost and source. However, it does not address error scenarios or pagination behavior related to the 'limit' parameter, leaving a minor gap in completeness.
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, the parameters are already described in the schema. The description does not add further semantic detail about how the parameters interact (e.g., whether market_id and query are alternatives) or provide examples. It stays at the 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 tool's function: 'Look up the resolution source and criteria for a Polymarket market.' It specifies concrete outputs (oracle, rules, data sources, timeline) and includes cost and source, distinguishing it from sibling tools like pm_changes or pm_stats.
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 viewing resolution details but does not explicitly state when to use this tool versus alternatives (e.g., pm_resolution_calendar or pm_resolution_stats). No 'when not to use' guidance is provided.
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 no annotations, the description discloses derived analytics, source, update frequency, and dataset size, providing good transparency.
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?
Four sentences front-loading the purpose, then filters, analytics, and source/size. No redundant information.
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, filters, analytics, source, and update frequency. Lacks output structure details like pagination or sorting, but is adequate for a search tool without output schema.
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%, so baseline is 3. The description adds context about derived analytics but does not enhance parameter meanings 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 searches OTC-traded companies from SEC EDGAR and lists filtering options, distinguishing it from simpler lookups like lookup_otc_ticker.
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 lists filtering capabilities but does not explicitly contrast with sibling tools or provide when-to-use/not-use 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?
With no annotations provided, the description carries the full burden. It discloses the data source (NOAA GFS model) and output contents (hourly/daily data for specific variables). The note about the dataset being 'coming soon' is a key behavioral disclosure, indicating potential unavailability. However, it does not specify what happens if called now (e.g., error or empty response).
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 long, front-loaded with the core purpose, followed by output details and source/availability note. No redundant information or filler; 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?
Given no output schema, the description adequately covers the return data (variables, granularity). It includes source and availability warning. However, it omits units (e.g., temperature scale) and does not specify location parameter priority (e.g., if both lat/lon and zip are provided). The completeness is good but leaves minor gaps.
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% description coverage for all three parameters (lat, lon, zip). The description adds 'for a location' but does not clarify how the parameters relate (e.g., lat/lon vs zip) or provide guidance on selection. Baseline 3 is appropriate since the schema already explains 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 retrieves weather forecasts for a location, with specific details on forecast range (up to 16 days), data granularity (hourly or daily), and included variables (temperature, humidity, wind, precipitation probability). This distinguishes it from sibling tools like get_current_weather and get_weather_history by focusing on future predictions.
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 the tool is for obtaining forecast data but does not explicitly state when to use it versus alternatives like get_current_weather or get_weather_history. The note 'This dataset is coming soon' warns about availability, but no direct comparisons or exclusions are 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?
With no annotations, description bears full burden. It reveals it's a free endpoint but omits other behavioral traits (e.g., read-only, idempotency, rate limits). Adequate but not rich.
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-loaded with action and enumerating outputs, with zero wasted 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?
Lists all return components explicitly, compensating for lack of output schema. Could add format or ordering details, but sufficient for an agent.
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 has 0 parameters with 100% coverage, so baseline 3 is appropriate; description adds no parameter information as none exist.
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 explicitly states the tool gets patent dataset statistics and lists specific outputs (total patents, type breakdown, etc.), clearly differentiating from sibling tools focused on 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?
Mentions 'Free endpoint' as a usage consideration, and the sibling tools list indicates this is for patent stats vs. individual patent lookup or other dataset stats, though no explicit when-not-to-use is given.
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 no annotations, the description carries the burden. It discloses cost ($0.02 per query) and source, adding transparency beyond mere purpose. However, it does not mention authentication or rate limits, but for a simple read tool 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?
Two concise sentences plus cost and source. Front-loaded with the action verb 'Get'. Every sentence adds value 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?
For a simple two-parameter tool with no output schema, the description adequately explains the return fields (resolution dates, sources, prices). It covers purpose, cost, and source, leaving few gaps given the tool's low complexity.
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 100% of parameters with descriptions. The description adds minimal extra meaning, only associating 'days' with 'within a given timeframe'. Baseline 3 applies as schema 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 'Get upcoming market resolution events' and specifies the output includes resolution dates, sources, and current prices. It distinguishes from sibling tools like pm_resolution_lookup and pm_resolution_stats by focusing on upcoming events within a timeframe.
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 viewing upcoming resolutions but does not explicitly state when to use this tool versus alternatives or when not to use it. The context is clear, but no exclusions or alternative references are 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?
With no annotations, the description must convey all behavioral traits. It notes 'Free endpoint' and lists output fields, but omits details like authentication requirements, data freshness, or latency. Basic transparency is provided but incomplete.
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 with no superfluous words. Every element earns its place by defining the tool's purpose and key outputs.
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 simplicity (no parameters, no output schema), the description adequately covers what it returns and that it is free. It could briefly contrast with sibling tools, but for an aggregate stats endpoint, it is sufficiently 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?
There are no parameters, so the schema coverage is 100%. The description adds value by specifying exactly what statistics are included (markets, wallets, volume, timestamp), which the empty schema does not convey.
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 'Get statistics about the Polymarket dataset' and lists specific metrics (total markets, wallets tracked, volume, last updated). This distinguishes it from sibling tools like pm_changes or pm_micro_stats, which focus on changes or micro 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?
No explicit guidance on when to use this tool versus alternatives. The description implies it is for aggregate overviews, but does not mention when not to use it or provide comparisons to related 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?
With no annotations, the description provides useful behavioral details: returns up to 100 results, source is CMS NPPES updated weekly, and covers ~7.2 million providers. Could add pagination or rate limit info, but current details are above average.
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 action and filters, second adds source and scale. 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?
Given no output schema, the description lacks explicit return value details, but the tool's purpose (search) implies a list of providers. The source and size info add context. Could mention typical response fields, but still adequate.
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. The description adds minor value by noting 'partial match' for name parameter, but other filters are already clear from schema. No major additional meaning 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 tool searches the NPI registry for healthcare providers with specific filters (state, specialty, name, city, ZIP). This distinguishes it from siblings like lookup_npi (single lookup) and npi_stats (statistics).
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 searching providers with filters, but does not explicitly state when to use this over alternatives like lookup_npi or when not to use it. No exclusions or context for when this tool is appropriate.
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?
With no annotations, the description adds some value by stating it is a free endpoint and listing returned data. However, it does not disclose other behavioral traits such as rate limits, idempotency, or whether authentication is needed.
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 deliver the purpose and a key behavioral note (free endpoint) with no unnecessary words. Information is front-loaded and easy to parse.
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 no-parameter tool, the description is largely complete. It covers the main outputs and notes it is free. Missing details could include data freshness or access restrictions, but these are minor given the tool's 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?
The input schema has no parameters, so the description's role shifts to clarifying the output. It effectively explains what statistics are returned (total entries, lists, last updated, data source), adding meaning beyond the empty 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 retrieves statistics about the sanctions dataset, listing specific fields like total entries and lists covered. This distinguishes it from sibling tools like 'sanctions_changes' and 'search_sanctions', which focus on changes and searching respectively.
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 obtaining aggregate stats and notes it is a 'free endpoint', but lacks explicit guidance on when to prefer this tool over alternatives like 'search_sanctions' or 'sanctions_changes'.
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?
No annotations are present, so the description carries the full burden. It states the tool returns CIK numbers, company names, and filing counts, but does not disclose pagination, rate limits, result limits, or error handling. This is a moderate gap.
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 consists of two concise sentences. The first states the action and outputs, the second provides a use case. No unnecessary words or repetition.
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 search tool with one parameter and no output schema, the description covers purpose, output content, and a typical use case. It could mention the format of results (e.g., list of matches) or behavior on no results, but it is largely complete.
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% for the single required 'search' parameter, with its description already explaining it takes a company name (min 2 chars). The tool description adds only 'by name', which is redundant. Baseline 3 applies.
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 for SEC-registered companies by name and returns CIK numbers, company names, and filing counts. It distinguishes from sibling tools like search_sec_filings by explicitly noting it is for finding a CIK before searching filings.
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 a specific use case (finding CIK before searching filings), implying when to use it. However, it does not explicitly state when not to use it or compare with alternatives like lookup_otc_ticker.
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?
With no annotations, the description should disclose more behavioral traits (e.g., read-only nature). It includes source and update frequency but lacks explicit safety cues.
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: first states purpose and parameter, second lists return fields and source. 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?
Given the simple one-parameter tool and no output schema, the description adequately covers input, output, and data source.
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 description merely reinforces the parameter's purpose without adding new details 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 a single federal court case by case ID, lists the returned metadata fields, and differentiates from sibling tools like search_pacer_cases.
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 use when a specific case ID is known and metadata is needed, but does not explicitly mention when not to use or suggest 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?
Lists specific fields returned and source (USPTO PatentsView), providing useful behavioral context. No annotations exist, so description carries burden adequately.
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 clear purpose followed by a concise list of returned fields and source. 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?
For a simple single-lookup tool with one parameter and no output schema, the description fully explains what it does and what it returns.
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 a description and pattern; the tool description adds an example already present in schema, so little extra 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 states the tool looks up a single US patent by number, with a specific verb and resource. Differentiates from sibling tools like patent_stats and query_patents.
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?
States context (look up a single patent by number) but does not explicitly provide when-not-to-use or alternatives among siblings.
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?
With no annotations provided, the description must convey behavior. It discloses source (PACER), update frequency (daily), and the note that data may be empty (coming soon). However, it does not explicitly state read-only nature or that it returns a list of results (though implied). Adequate but not comprehensive.
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 plus a brief note. No redundant information. Every sentence adds value: what it does, how to filter, what it returns, source, and update cadence, plus an important caveat.
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 explains return fields (title, parties, court, filing date) and provides source, update frequency, and the important 'coming soon' note. For a search tool with 6 parameters and no output schema, this is complete enough for agent 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?
Input schema has 100% parameter description coverage. The description lists filters (party, court, case type, date range) which overlaps with schema. No additional semantic detail beyond what schema provides. Baseline score 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?
Description uses specific verb 'Search' and resource 'federal court case records from PACER', lists filters, and mentions return fields. Clearly distinguishes from sibling tools like get_pacer_case (retrieve single case) and pacer_stats (aggregated stats).
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?
Clearly states the tool is for searching PACER cases with multiple filters. Does not explicitly exclude use cases or compare to alternatives, but the note about data being 'coming soon' provides important context. Implicitly different from get_pacer_case and pacer_stats.
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?
No annotations provided, description only states it returns statistics and is free. Does not discuss rate limits, data freshness, or error conditions. Adequate for a simple stats endpoint but could be more transparent.
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-loads purpose and includes practical info about being free. 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?
Given no parameters and no output schema, description adequately lists what statistics are returned (total filings, form breakdown, date range, timestamp). Serves its purpose for a simple stats endpoint.
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?
No parameters exist, so baseline is 4. Description adds meaning by explaining what the output contains, which is sufficient for parameter semantics.
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 provides statistics about SEC filings dataset including specific items (total filings, form type breakdown, date range, timestamp). Distinguishes from siblings like search_sec_filings and get_sec_filing which are for individual filings.
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?
Mentions it's a free endpoint with no payment required, but does not explicitly state when to use compared to other SEC tools or when not to use. The usage is implied as a quick overview tool.
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?
No annotations provided; description adds 'Free endpoint' but does not disclose read-only behavior, rate limits, or side effects. For a simple stats endpoint, the gap is small but present.
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 that directly states purpose and key data points, no excess 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 stats tool with no output schema, the description fully explains what is returned (three specific metrics), making it complete for its 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?
No parameters in input schema; description adds no parameter info but lists returned fields, which is helpful. Baseline for 0 params is high, and the output context is 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?
Clearly states it gets statistics about the whale wallet dataset, listing specific data points (wallets tracked, chains, timestamp), distinguishing it from sibling stats tools for other datasets.
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?
Mentions 'Free endpoint' implying no authentication cost, but does not explicitly state when to use this tool versus alternative stats tools for other datasets.
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?
Without annotations, the description adds cost ($0.005 per query) and source (on-chain intelligence), which is useful. It does not mention rate limits, data freshness, or pagination, but the read-only nature is implied.
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 plus cost and source line, all relevant and front-loaded with the action. No wasted 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?
For a simple retrieval tool with two parameters and no output schema, the description covers purpose, output types, cost, and source. Missing potential details like time range limits or default behavior, but overall sufficient.
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%, so parameters are well-documented in the schema. The description adds no extra meaning beyond 'since a given timestamp' and the cost note, which is already present in schema descriptions for 'since' and 'limit'.
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 'Get' and resource 'recent changes to address labels', clearly distinguishing from sibling tools like 'label_stats' (aggregated stats) and 'lookup_label' (current label). It specifies the output: newly labeled addresses, risk score updates, and category changes.
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 when needing label changes since a timestamp, but does not explicitly state when not to use it or mention alternatives like 'holder_changes' or 'dex_changes'. However, the context of address labels 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?
No annotations are provided, so the description carries the full burden. It mentions the tool is free and returns statistics, but does not disclose potential behaviors like rate limits, response size, or whether the data is cached. This is minimal transparency for a simple read operation.
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 concisely conveys the tool's purpose and output. No superfluous 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 parameterless stats endpoint, the description covers the key return values. However, it omits any mention of potential limitations (e.g., data staleness, max results) or output format, which could be useful for 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?
The input schema has no parameters, so schema coverage is 100%. The description adds value by enumerating the specific statistics returned (total labeled addresses, categories, timestamp), which goes beyond the empty 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 gets statistics for the address label dataset and lists specific metrics (total labeled addresses, categories covered, last updated timestamp). This differentiates it from sibling stat tools like contract_stats or dex_stats which operate on different datasets.
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 what the tool does and notes it is a 'free endpoint', giving insight into usage. However, it lacks explicit guidance on when to use this tool versus alternatives, though the specificity of the dataset makes it straightforward.
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?
No annotations provided, so description carries full burden; it lists returned fields (CIK, SIC, financials, short interest, shell risk, filing recency) and sources, but lacks details on error handling, 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: first states purpose, second enumerates returned fields and sources. No fluff, front-loaded.
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?
No output schema; description lists key fields but may omit minor ones. Given moderate complexity and clear scope, it provides sufficient context for an 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?
Schema has 100% coverage for ticker parameter with pattern and description; description adds context that the ticker is for an OTC company and lists what is returned, adding 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 action 'look up a single OTC-traded company by ticker symbol' and distinguishes from sibling tools like lookup_contract or lookup_label by specifying OTC domain and SEC/FINRA source.
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?
Implies use for single company lookup by ticker, but does not explicitly state when to use vs alternatives like query_otc_companies or how it differs from search_sec_companies.
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 no annotations, the description provides behavioral context: cost ($0.02 per query) and data source (on-chain analytics). It omits read-only hint but the operation is clearly a read query.
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 that efficiently deliver purpose, return data, cost, and source. No fluff; 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?
The description lists return fields and cost, adequate for a simple lookup. It could mention potential rate limits or authentication needs but is generally complete given the single 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?
Schema coverage is 100% and the parameter description in the schema is clear. The tool description does not add further semantics beyond the schema, earning a baseline score 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 clearly specifies the verb 'Get full detail', the resource 'single whale wallet', and enumerates the returned data (balance history, token holdings, recent transactions, PnL metrics). This distinguishes it from siblings like 'whale_stats' or 'whale_changes'.
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 when a detailed single-wallet view is needed and mentions a cost factor. However, it lacks explicit guidance on when not to use or alternatives among sibling whale 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?
No annotations provided, so description carries the burden. It discloses it's free and what data it returns, but does not mention any behavioral traits like read-only, rate limits, or auth requirements. Adequate for a simple stats retrieval but not comprehensive.
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. Front-loaded with core purpose, then adds the free usage note. Efficiently conveys all necessary 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?
No output schema, but description lists the returned fields (record count, number of states, last updated, data source). For a simple stats endpoint, this is sufficient context. Could mention format or pagination but not required.
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?
Input schema has zero parameters with 100% coverage. According to rules, 0 params baseline is 4. The description correctly implies no inputs 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?
States it gets statistics about the NPI dataset with specific items: total record count, number of states, last updated timestamp, data source info. Clearly distinguishes from sibling stats tools like contract_stats or crypto_stats.
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 notes it's a free endpoint with no payment required, which is a usage guideline. However, it does not explicitly state when to use this tool versus alternatives like lookup_npi for individual provider details.
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?
Discloses source (SEC EDGAR), update frequency (every 15 minutes), and return type (metadata). No annotations provided, but description covers essential behavioral traits for a read-only search tool.
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 states parameters and action, second states returns and source. 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?
Given 6 parameters, no output schema, and no annotations, the description covers the search purpose, input fields, and return format adequately. Lacks explanation of edge cases or error handling, but sufficient for a straightforward search 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 has 100% description coverage for all 6 parameters. Description mentions parameters in narrative but does not add significant meaning beyond what schema provides. Baseline score of 3 applies.
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 searches SEC EDGAR filings by CIK, form type, company name, and date range, and returns metadata. It distinguishes itself from siblings like 'get_sec_filing' and 'search_sec_companies' by specifying the search 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?
Provides clear context on what parameters can be used, but does not explicitly state when to use this tool versus alternatives like 'get_sec_filing' for a specific filing. No exclusions or when-not-to scenarios are mentioned.
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?
No annotations provided, but the description explicitly states 'Free endpoint', indicating no cost. Since the tool has no parameters and is read-only, no additional behavioral disclosure is needed beyond what's described.
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-loading the key information about what stats are returned, then adding a note about being free. 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?
For a simple stateless tool with no parameters and no output schema, the description fully covers what the tool does and what it returns. No gaps remain.
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 does not need to add parameter meaning. The schema covers 100% of parameters (none), and a baseline of 4 is appropriate for no 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 returns statistics about the PACER dataset, listing specific fields (total cases, courts, date range, last updated). It uniquely identifies its target dataset, distinguishing it from sibling stats tools for other datasets.
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 context (getting dataset-level stats) but does not explicitly exclude alternatives or state when not to use. However, given the tool's simplicity and zero parameters, the guidance is adequate.
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?
No annotations provided, so the description carries the burden. It correctly indicates a read-only query and includes a 'Free endpoint' disclosure. However, it does not specify rate limits, data freshness, or other behavioral details.
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 plus a brief note. Front-loaded with key information, no filler. Extremely 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 zero parameters and no output schema, the description sufficiently explains the tool's output and free status. Complete for a statistics endpoint.
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?
Input schema is empty (0 parameters, 100% coverage), so baseline is 3. The description adds value by enumerating output statistics, compensating for the lack of output schema. Provides meaningful context 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 retrieves statistics about the Polymarket microstructure dataset, listing specific metrics (total markets analyzed, average spread, thin book count, last updated). This distinctively separates it from sibling tools like pm_micro_depth or pm_stats.
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 context for aggregated stats, but lacks explicit guidance on when to use vs. alternatives like pm_micro_depth or pm_micro_thin. The 'Free endpoint' note adds value but does not fully address comparative selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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