llm_status

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It does not state whether the operation is read-only, mentions side effects, auth requirements, or return format beyond the listed fields. It is a status tool, but the lack of explicit safety or behavioral notes weakens transparency.

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 sentence that front-loads the key purpose and lists the specific outputs. It is concise with no redundant or vague wording, making it efficient and easy to parse.

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 status tool with one optional parameter and no output schema, the description adequately covers what the tool returns (model, install state, counts). It does not explain the effect of the worktree parameter, but the schema covers that, so completeness is reasonable.

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 coverage is 100%, so the worktree parameter is fully described in the schema. The description adds no extra semantic detail about the parameter beyond what the schema already provides, earning the baseline score.

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 clearly states the tool reports embedding status, including model, install state, and counts of embedded/missing/skipped chunks. It uses specific context (local vs remote/Ollama) that distinguishes it from sibling status tools like index_status or papertrail_sync_status.

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 implies usage for checking embedding status but does not explicitly state when to use this tool versus alternatives like index_status or papertrail_sync_status. No exclusions or alternative references are provided.

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