Score federal contract awards against a service keyword, agency, or company domain. Returns incumbents, agencies, amounts, and pursuit notes.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| agency | No | ||
| keyword | No | ||
| company_domain | No |
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 returns data but does not disclose whether it has side effects, requires authentication, or has rate limits. The description is too brief for a mutation-aware agent.
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 sentence that efficiently communicates purpose and outputs, but could be more structured by explicitly listing parameters or usage tips.
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 output schema, empty annotations, and four undocumented parameters, the description is incomplete. It does not explain the 'limit' parameter, how parameters interact, or what the output format is beyond a vague 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 0% and the description only vaguely mentions inputs ('service keyword, agency, or company domain') without linking to the schema properties (keyword, agency, company_domain, limit). It fails to explain the 'limit' parameter or any constraints.
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 'Score' and names the resource 'federal contract awards', clearly distinguishing it from sibling tools like 'federal_contracts' that might simply list contracts. It also lists return fields (incumbents, agencies, amounts, pursuit notes).
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 for scoring contract fit but does not provide explicit when-to-use or when-not-to-use guidance. No alternatives are mentioned, though siblings exist (e.g., federal_contracts, federal_spending).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tools cover very diverse domains (weather, FDA, legal, crypto, etc.), so cross-domain confusion is low. However, within domains there is notable overlap: multiple food recall tools (food_recall_check, food_safety), multiple weather tools (weather_current_global, weather_forecast_grid, weather_alerts, weather_bias), and several Polymarket-related tools. This can cause agent misselection.
Naming is inconsistent: some tools use verb_noun (search_arxiv, scrape, validate_agent_manifest), others use noun phrases (smart_money, space_weather, tide_data), and some are long descriptive phrases (cross_platform_arb_scan, polymarket_event_scan). No single pattern is followed, making predictions difficult.
95 tools is excessively high for any coherent purpose. The server appears to be a random aggregation of APIs with no clear scope. Such a large catalog overwhelms agents and dilutes utility; most tools could be split into specialized servers.
Although many domains are touched, each is covered only shallowly. For example, weather lacks historical data, legal lacks case details beyond court opinions, and financial lacks stock prices. There are obvious gaps like no user authentication or data persistence. The tool set feels like a collection of endpoints rather than a cohesive service.