Govparse Government Data Gateway

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Given no annotations, the description discloses that results are public records, name/address-matched, and include match tiers and confidence. It also lists data sources and states it's not a consumer report. Missing details on rate limits or empty results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-organized and front-loaded with a clear question and answer. It could be slightly shorter but effectively conveys all necessary information without wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 2-parameter tool with no output schema, the description adequately describes the return: canonical identity, per-source sections, match tiers, and confidence. It also mentions pricing, making it contextually complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for both parameters. The description adds normalization details for the name parameter but little for state. The description's mention of 'by name + state' is redundant with the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool produces a flagship employer dossier by name and state across multiple federal datasets. It distinguishes itself from sibling tools like 'firmstanding_company_search' by specifying it aggregates records from all datasets at once.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for comprehensive company lookups and includes a disclaimer about FCRA use. However, it does not explicitly contrast with sibling tools or state when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description bears full burden. It discloses the returned data (aggregates) and cost ($0.001/call), suggesting a safe, read-only operation. However, it does not explicitly state that it is non-destructive or requires no authorization.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences with no wasted words. The first sentence poses a natural language question, and the second enumerates key outputs. Ideal length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

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 fully explains the tool's return value (headline aggregates) with specific metrics. It is complete for a stats tool that requires no inputs and provides a clear summary.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters; schema coverage is 100% trivially. Per guidelines, 0 params baseline is 4, and the description adds no parameter info since none exist.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns headline aggregates about the FirmStanding employer entity graph, listing specific metrics like resolved entities, sources, states, and record links. It distinguishes itself from sibling tools (e.g., company_search, screen_*) which focus on individual entities or specific data, while this provides overall stats.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use when wanting overall statistics, but does not explicitly state when not to use it or provide alternative tools. It gives a price note but lacks explicit guidance on selection context compared to siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses pagination behavior (cursor, up to 1000/page), filtering capabilities, and pricing ($0.05/call). It does not mention rate limits, data freshness, or read-only nature, but the 'feed' terminology implies a read operation. Sufficient for most use cases.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured paragraph of three sentences. It front-loads the main purpose, lists key fields, then covers pagination, filters, and price. No redundant or wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 5 parameters, no output schema, and no annotations, the description covers the main behavioral aspects: data fields, pagination, filters, and cost. It lacks explicit mention of error handling or data update frequency, but provides enough context for an agent to select and use the tool appropriately.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

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 summarizes the filtering options and pagination, but the input schema already provides detailed parameter descriptions. The description adds value by explaining the cursor usage and default limit, but does not significantly extend beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it provides the full FMCSA carrier census in a bulk analytics feed, listing specific data fields (legal/DBA name, operating status, etc.) and distinguishing it from sibling tools like fmcsa_carrier_search or fmcsa_carrier360 which focus on individual carriers.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description specifies the feed is for bulk analytics, with filtering options (state, fleet size, census add date) and cursor pagination. It implies usage for large-scale data retrieval rather than single carrier lookup, but does not explicitly state when not to use or mention alternative tools for specific queries.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 clearly indicates this is a search/read operation (non-destructive) and includes a pricing note ($0.02/call), which is a behavioral disclosure. It does not mention rate limits or result formatting, but overall it gives a good sense of what the tool does and its cost.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the purpose with a question, then enumerates parameters efficiently, and ends with use cases. Every part adds value; there is no wasted text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (13 parameters), no output schema, and no annotations, the description provides adequate context: it names the data source (USAspending), award types (contracts and assistance), and parameter categories. It covers what the tool does and when to use it, though it could mention that results are paginated (implied by offset/limit) or that the response format is a list.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% (all 13 parameters have descriptions and examples in the schema). The description text itself adds no additional parameter-level detail beyond summarizing the categories (recipient, agency, NAICS, etc.). Per the rubric, when schema coverage is high, the baseline is 3, which is appropriate here.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a clear, evocative question ('Who has the government actually paid, for what, and how much?') and immediately specifies the tool's function: searching USAspending federal award history by multiple criteria. It also lists concrete use cases (competitor award research, incumbent lookup, grant-winner analysis), effectively distinguishing it from sibling tools like govcon_opportunity_search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implicitly guides usage by listing relevant scenarios (competitor research, incumbent lookup, grant-winner analysis). It does not explicitly state when not to use this tool or point to alternatives, but the sibling tool names (e.g., govcon_opportunity_search) provide context. The guidance is clear enough for an AI agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, but the description lists all returned fields (solicitation number, type, set-aside, etc.) and mentions cost ($0.01/call). It does not explicitly state read-only behavior or auth requirements, but the nature is clear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences: first states the action, second lists the fields and cost. It is front-loaded, concise, and contains no extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given one parameter, no nested objects, no output schema, and clear sibling tools, the description fully covers what the tool does, what it returns, and its cost. No gaps are apparent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'noticeId' has 100% schema description coverage. The description adds no extra meaning beyond the schema's own description, meeting the baseline for full coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'What are the full details of this federal opportunity?' and specifies it returns a complete record for one SAM.gov or Grants.gov notice, distinguishing it from sibling search and award tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied (when full details of a single opportunity are needed) but no explicit when-to-use or when-not-to-use guidance is provided. Alternatives like govcon_opportunity_search are not mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.