US federal contract awards by company, agency spending, top vendors. USAspending.gov data.
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Average 4.6/5 across 3 of 3 tools scored.
Each tool targets a clear, distinct query axis: get_agency_spend looks at agency spending by vendor/industry, search_awards_by_company looks at a company's awards and agencies, and get_expiring_contracts identifies contracts expiring by NAICS. No two tools have overlapping purposes.
All three tools use a consistent verb_noun pattern in snake_case: get_agency_spend, get_expiring_contracts, search_awards_by_company. The verbs 'get' and 'search' both indicate retrieval and fit the context.
Three tools sit within the ideal 3-15 range and each covers a distinct dimension (agency, company, and time-based pipeline). The count is well-scoped for a focused federal contract intelligence server.
The tool surface lacks direct contract lookup by ID or keyword, and cannot filter awards by date besides the expiring-contracts window. The get_expiring_contracts tool is also not yet functional, making the set incomplete for full contract intelligence.
get_agency_spendGet agency contract spendAWhere one federal agency's contract dollars went in a fiscal year: its top vendors and its top NAICS industries, both ranked by obligated amount. Use it to answer who sells to an agency and what that agency buys. The agency argument must resolve to a single toptier agency — use the full name ("Department of Veterans Affairs") or the official abbreviation ("VA"); an ambiguous fragment matching several agencies returns no match rather than a guess. Fiscal years run 1 October to 30 September and are named for the ending calendar year, so FY2026 starts 2025-10-01; omit fiscalYear for the current one. Source: USAspending.gov prime contract awards (public domain, no login). Civilian agency awards are roughly 4 days fresh; Department of Defense awards are withheld about 90 days, so recent defense activity looks sparser than it is. Amounts are obligated dollars in USD.
| Name | Required | Description | Default |
|---|---|---|---|
| agency | Yes | Toptier agency name or abbreviation, e.g. "Department of Homeland Security" or "GSA". | |
| fiscalYear | No | US federal fiscal year, e.g. 2026. Defaults to the current fiscal year. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that ambiguous agency fragments return no match, defines fiscal year boundaries, notes data freshness for civilian vs DoD, and states amounts are in USD. This goes well beyond the readOnlyHint/openWorldHint annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four focused sentences, front-loaded with purpose, then usage, then data context. No 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?
Though no output schema, the description specifies the return content (top vendors, top NAICS industries) and gives sufficient context on source, freshness, and units. Complete for a read-only, 2-param tool.
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 already covers both parameters; description adds the rule that agency must resolve to a single toptier agency and explains fiscal year default and naming conventions, providing extra clarity beyond 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?
Clearly states it returns top vendors and top NAICS industries by obligated amount for a federal agency, using specific verbs (who sells, what buys). Distinct from siblings (expiring contracts, awards by company).
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?
Explicitly says 'Use it to answer who sells to an agency and what that agency buys,' and provides constraints on agency naming and fiscal year. Does not explicitly name alternatives or when-not-to-use, so a 4.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_expiring_contractsGet expiring contractsAFederal contracts whose period of performance ends inside a chosen window for one NAICS industry — the recompete pipeline, useful for finding work that is about to be rebid. This tool needs SAM.gov contract-awards access, which is not enabled yet; until then it returns a short coming-soon notice instead of data. The other FedTally tools are unaffected.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Days ahead to look for expiring periods of performance. Defaults to 180. | |
| naics | Yes | NAICS industry code, 2 to 6 digits, e.g. "541511" for custom computer programming. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, and the description adds important behavioral context: the tool requires SAM.gov contract-awards access which is not enabled yet, so it currently returns a coming-soon notice instead of data. This goes beyond what annotations convey and sets proper expectations.
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 three sentences, front-loaded with the core purpose, followed by a critical limitation and a reassuring note that other tools are unaffected. Every sentence earns its place with no waste.
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 simple two-parameter schema, no output schema, and the current non-functional state, the description fully covers the essential information: purpose, current behavior, and impact. It is complete for an agent to decide whether and how to invoke the tool.
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 schema provides 100% coverage with descriptions for both parameters (naics and days), including examples and constraints. The description does not add additional parameter semantics, so the baseline score of 3 applies.
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's function: returning federal contracts with periods of performance ending inside a chosen window for one NAICS industry. It uses specific language ('recompete pipeline') and distinguishes itself from sibling tools by focusing on expiring contracts rather than agency spend or company 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?
Provides clear context for when to use the tool (finding work about to be rebid) and explicitly notes the current limitation (requires SAM.gov access that is not enabled, so returns a coming-soon notice). It does not name alternative tools or provide explicit when-not-to-use guidance, but the use case is well implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_awards_by_companySearch federal awards by companyATop US federal prime contract awards won by a company, largest award amount first. Use it to size a contractor's federal business, see which agencies buy from it, or pull its biggest named contracts. Matching is full-text on the recipient name, so pass the company's common or legal name ("Booz Allen", "Lockheed Martin") rather than a ticker or internal abbreviation; a name that is too specific returns nothing. Returns up to 25 awards per page with award ID, recipient, awarding agency, amount, period of performance, NAICS code, and description; page through with the page argument while hasNext is true. Source: USAspending.gov prime contract awards (public domain, no login). Civilian agency awards are roughly 4 days fresh; Department of Defense awards are withheld about 90 days, so recent defense activity looks sparser than it is. Amounts are obligated dollars in USD.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page of 25 awards, sorted by amount descending. Defaults to 1. | |
| query | Yes | Company name to match against federal award recipients, e.g. "Booz Allen". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint, but the description adds substantial behavioral context: full-text matching behavior, data freshness (civilian vs DoD 90-day withholding), source (USAspending.gov), and return fields including pagination via hasNext. It explains why recent defense data looks sparse, which is beyond annotation scope.
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 dense paragraph, but it is front-loaded with purpose and flows logically through matching, output fields, and data caveats. Every sentence adds useful information; however, it could be slightly tightened without losing meaning.
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 lack of an output schema, the description comprehensively covers return fields, pagination, and data source nuances. The tool's complexity (paging, freshness, matching) is fully addressed, making it complete for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters descriptively, but the description adds value: explains ordering (largest amount first), page size (25), and provides concrete examples ('Booz Allen', 'Lockheed Martin'), plus clarifies that over-specific queries return nothing. This is far beyond the schema's baseline.
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 uses a specific verb and resource: 'Top US federal prime contract awards won by a company, largest award amount first.' It clearly distinguishes from sibling tools (get_agency_spend, get_expiring_contracts) by focusing on company-specific award lookup and explicitly states use cases like sizing a contractor's business.
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?
Provides strong context: says when to use it ('size a contractor's federal business, see which agencies buy from it'), gives explicit matching guidance (use common/legal name, not ticker), and warns about overly specific names returning nothing. However, it does not directly name alternatives or describe when not to use this tool versus siblings.
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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