tracker_vendor_matrixQuery the 45-vendor counter-UAS competitive matrix. Filter by layer or US-procurement eligibility. Requires a tracker licence token.
| Name | Required | Description | Default |
|---|---|---|---|
| layer | No | Substring match, e.g. "Detect", "Defeat", "Integrate" | |
| us_procurement | No | Substring match, e.g. "NDAA", "Allied", "restricted" |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It discloses a key behavioral requirement (license token) and implies a read-only query, but it does not specify return format, pagination, error behavior, or whether any side effects exist. It adds some context but not a full behavioral profile.
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?
Two sentences, front-loaded with the core purpose, and every sentence adds value. The structure is efficient and free of redundant wording.
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?
The tool is a simple query with two optional string parameters and no output schema, so the description covers the essential context: what it queries, how to narrow results, and an authentication requirement. It lacks details like return shape or result limits, but for this complexity level it is reasonably 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%, so the schema already documents both parameters with substring-match examples. The tool description adds only that these filters relate to 'layer' and 'US-procurement eligibility', which is a minor semantic clarification but does not significantly go 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?
The description uses a specific verb ('Query') and a concrete resource ('the 45-vendor counter-UAS competitive matrix'), clearly distinguishing it from sibling tools like get_company_profile or compare_companies. It also scopes the tool precisely with the vendor count and domain.
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?
It provides clear context on what the tool does and what filters are available ('Filter by layer or US-procurement eligibility'), and mentions a prerequisite ('Requires a tracker licence token'). However, it does not explicitly state when to use this tool over alternatives, nor does it mention exclusion scenarios.
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 targets a distinct resource or operation. Content tools (get_briefing, get_company_profile, get_intelligence_page, compare_companies) are clearly separated by content type, while tracker_* tools each serve a unique data query function. There is no ambiguity between content retrieval and tracker analysis.
Content tools follow a verb_noun pattern (get_*, compare_companies, list_catalogue, search_content), but tracker_* tools use a noun-prefix style (tracker_aggregate, tracker_awards, tracker_capital_ledger). This mixed convention is internally consistent within each group but not throughout the server.
12 tools is well-scoped for a server covering both content access and a tracker dataset. Each tool has a clear purpose, and the number aligns with the guideline of 3-15 tools.
The tool surface covers all announced content types (briefing, intelligence page, company profile, comparison) with get/compare operations, plus catalogue listing and cross-type search. The tracker tools provide comprehensive querying and metadata access, with no obvious missing operations.