demand_reportFREE, no payment. The aggregate of what agents have told us they are looking for, most-requested first, with the categories nothing available yet serves.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Window in days, default 30, max 90. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral disclosure burden. It usefully states that the tool is 'FREE, no payment' and that results are aggregated and ordered most-requested first, implying a read-only report. However, it does not disclose data freshness, rate limits, or the precise meaning of 'categories nothing available yet serves.'
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 very short and front-loads the key selling point ('FREE, no payment'). However, the sentence 'with the categories nothing available yet serves' is confusing and poorly structured, which undermines clarity despite the brevity.
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 simple one-parameter report, the description conveys the core output and ordering, and the schema covers the parameter. But it leaves important context unstated: what exactly 'categories nothing available yet serves' means, how days changes the report, and what fields each entry contains. Without an output schema, more explicit return-format detail would help.
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 fully documents the only parameter (days with default 30 and max 90), so the description does not need to repeat it. Still, the description adds no information about how the days window affects the aggregation or output. Baseline 3 is appropriate because schema coverage is 100%.
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 identifies a clear resource: an aggregate of what agents have asked for, ranked most-requested first, and scoped to categories 'nothing available yet serves.' This distinguishes it from package-specific siblings like package_info and package_vulnerabilities. It loses the top score because the phrasing 'with the categories nothing available yet serves' is grammatically awkward and slightly ambiguous.
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?
No guidance is given about when to use this tool versus alternatives such as request_data. The description does not state conditions, exclusions, or a preferred alternative for more detailed or individual request data. An agent must infer usage from the title and sibling names.
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.
Each tool has a clearly distinct purpose: demand_report and request_data handle market demand and data procurement, while package_info, package_vulnerabilities, and package_audit cover package details, known advisories, and a combined safety verdict. The audit tool's relationship to the other two is explicitly clarified by recommending it over separate calls, removing any ambiguity.
All tool names follow the same snake_case pattern of a subject noun followed by a focus noun (demand_report, package_audit, package_info, package_vulnerabilities, request_data). This consistent convention makes the set predictable and easy to navigate.
With 5 tools, the server is well-scoped for its dual purpose of package intelligence (info, vulnerabilities, audit) and data market signals (demand report, data request). Each tool serves a distinct need without excess or deficiency, falling within the ideal 3–15 range.
The surface covers the full workflow for package safety checks (look up info, check vulnerabilities, get a combined verdict) and data procurement (see market demand, request specific data). No obvious gaps exist for the stated purpose of providing dev package intelligence and a data marketplace.