tracker_capital_ledgerThe tracker's capital and acquisition ledger: where the money behind the counter-UAS vendors is being raised. Requires a tracker licence token.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It only discloses the token requirement, but fails to mention side effects, return format, or whether the operation is read-only. This is minimal and insufficient.
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 extremely concise, with two short sentences, no redundant phrasing, and the key information (what it is and the token requirement) front-loaded. Every word earns its place.
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?
With no output schema, the description should clarify what the tool returns, but it only describes the ledger's subject matter. It is adequate for a vaguely defined data source but leaves gaps about return type or content granularity.
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 tool has zero parameters, so the baseline is 4. There is nothing for the description to add beyond what is already vacuously covered by 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 identifies a specific resource—the capital and acquisition ledger for counter-UAS vendors—but lacks a clear verb indicating the action (e.g., 'lists', 'retrieves'). It adds context beyond the title but remains vague about what the tool actually does.
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 provided on when to use this tool versus sibling tools. The only usage-related note is the licensing requirement, which is a prerequisite rather than a context for selection.
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.