List Market Trackers datasets

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 discloses both list-mode returns (row count, freshness, years, searchable flag) and detail-mode returns (field roster, filterable paths, caveats, per-year coverage, source health, dump URLs). It implies read-only operation but does not discuss output structure, rate limits, or auth; for a catalog/list tool this is a minor gap.

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 dense paragraph with the core purpose front-loaded and no filler. The dataset enumeration partly overlaps with the schema enum, but it expands terse enum labels into understandable categories, so it earns its place; still, it could be tightened slightly.

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 one optional enum parameter, no annotations, and no output schema, the description fully covers what the agent needs: what the tool lists, what each mode returns, and how to use it as a prerequisite for trackers_query. No critical invocation detail is missing.

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 already fully covers the enum and says 'omit to list all', so the baseline is 3. The description adds meaning beyond the schema by explaining that passing dataset yields the full field roster, filterable paths, caveats, per-year coverage, source health, and dump URLs, and by tying this to trackers_query filter composition.

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 the tool as the 'Market Trackers catalog' and states exactly what it returns (row count, freshness, year coverage, ticker-searchability), making the listing purpose unmistakable. It differentiates from query siblings by positioning itself as the catalog to consult before composing trackers_query filters. This is more than just the title.

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 gives explicit context: call without dataset to list all and pass a dataset for the detailed view, and instructs the agent to read it before composing trackers_query filters. It only names trackers_query as an alternative and does not contrast with trackers_latest or trackers_ticker, so it lacks full exclusion coverage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.