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govcon_fetch_vendor_contract_history

Read-onlyIdempotent

Fetch the complete federal contract award history for a specific vendor. Read-only. No side effects. Idempotent. vendor_name: Company or organisation name e.g. Booz Allen Hamilton. Required. Fuzzy match used. jurisdiction: One of US, EU, or UK. Optional. Default US. Returns total award value, top awarding agencies, contract types, and recent awards with amounts and dates. Use this when researching a specific company's government contracting history. Use govcon_search_contract_awards instead when exploring a topic area without a specific vendor. Verified source: USASpending.gov. 4-hour cache. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="govcon_fetch_vendor_contract_history", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vendor_nameYesVendor or company name to search e.g. Booz Allen Hamilton. Required.
jurisdictionNoJurisdiction: US, EU, or UK. Default US. Optional.US

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description reinforces these with 'Read-only. No side effects. Idempotent.' and adds further details: fuzzy matching, cache duration, verified source. No contradictions.

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

Conciseness4/5

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

The description is comprehensive but not overly verbose. It front-loads the core purpose and groups information logically (purpose, safety, parameters, usage, source, cache, fallback). A slightly tighter structure could remove redundancy, but it remains effective.

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

Completeness5/5

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

Despite having an output schema (not shown), the description lists key return fields. It covers safety, parameters, usage, alternatives, source, cache, and even error handling via report_feedback. For a two-parameter tool with rich annotations, this is fully complete.

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

Parameters4/5

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

Schema description coverage is 100% (both parameters have descriptions). The description adds value by noting 'Fuzzy match used' for vendor_name, which goes beyond the schema. With high baseline, the addition earns a score above 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 states the tool fetches 'complete federal contract award history for a specific vendor' — a specific verb and resource. It distinguishes from the sibling tool 'govcon_search_contract_awards' by specifying when to use each, ensuring clear differentiation.

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

Usage Guidelines5/5

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

Explicitly tells when to use ('when researching a specific company's government contracting history') and when not to use ('use govcon_search_contract_awards instead when exploring a topic area without a specific vendor'). Provides clear context and alternatives.

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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TDQS

A4.1/5.0
Disambiguation4/5

Tools are grouped into clear domain prefixes (compliance, domain, frontend_security, etc.) with distinct purposes. Minor overlap exists between frontend_security_detect_typosquatting and security_detect_typosquatting, but descriptions clarify the different scope.

Naming Consistency4/5

Most tools follow a consistent verb_noun pattern with snake_case. Irregularities like 'fetch' vs 'audit' and two 'detect_typosquatting' tools exist, but overall naming is predictable within domains.

Tool Count3/5

55 tools is high for a single server given the breadth of domains. Some redundancy (e.g., two typosquatting tools) suggests possible trimming, but the count is justified by the wide coverage.

Completeness4/5

The tool surface covers key operations across domains like compliance, domain, security, legal, and nonprofit. Minor gaps exist, such as limited frontend audit beyond package.json and no general-purpose code scanning.

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