corpus_status

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description carries the burden of behavioral disclosure. It explains the significance of an absent source (degraded grounding) and advises how to respond, which is valuable context. It does not explicitly state read-only behavior, but the nature of a status query is implied.

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, well-structured sentence with a colon-separated list of the exact aspects covered. It is concise, front-loaded with the purpose, and contains no filler.

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 output schema exists, the description does not need to explain return values. It covers all key aspects: what the index covers, where it came from, resolution status, passage counts, build time, and how to handle absent sources—linking to fetch_corpus as a follow-up.

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, and the schema coverage is 100% (no params). The baseline for a zero-parameter tool is 4; the description correctly focuses on behavior rather than parameter details.

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 explicitly states what the tool reports: the grounding index's coverage (logical sources), resolution state (local checkout, fetched cache, absent), passage counts, and build time. This specific enumeration distinguishes it from sibling tools like fetch_corpus, which modify state.

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 provides clear usage guidance: if a source is absent, say grounding is degraded rather than answering from partial knowledge, and use fetch_corpus() to fill the gap. This explicitly names the alternative and the condition for using it.

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