suggest_entries

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

Explains the scoring mechanism (splits task into terms, scores by term matches) and ranking. Lacks explicit mention of non-destructive nature or idempotency, but overall reasonable given no annotations.

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?

Concise, front-loaded, every sentence adds value. Structured with main purpose, then usage, then parameters. No unnecessary text.

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 an output schema exists, the description doesn't need to explain return values. It covers behavior, parameters, and use cases adequately for the tool's complexity.

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?

With 0% schema description coverage, the description fully explains each parameter: 'task' as natural language description, 'type' as optional filter, 'limit' with default. Adds meaning 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 clearly states the tool suggests registry entries relevant to a natural language task description. It distinguishes itself from the sibling 'search_entries' by specifying it's for natural language queries vs. exact keyword matching.

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?

Provides explicit guidance: use for natural language queries like 'I need to review architecture' and for exact keyword matching use 'search_entries' instead.

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