lbm_list_competitors

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral context: the default output is a compact CSV with competitor name, mention count, and frequency %, and the option to get full JSON via include_all_fields. This clarifies the response format beyond what annotations provide.

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 at four sentences, with clear labels (WHEN TO USE, REQUIRES, RETURNS). Every sentence adds essential information without redundancy, making it easy to parse quickly.

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 5 parameters and no output schema, the description covers return format (CSV vs JSON fields) and defaults (limit 20). It mentions offset but not pagination behavior or error cases. Still, it provides enough context for typical use, and annotations cover safety.

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%, but the description adds practical guidance: setting include_all_fields=true for full JSON, and 'Pass higher limit only if user explicitly asks for more.' This helps the agent make informed decisions about parameter values, enhancing the bare schema descriptions.

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's function: 'To see which competitor brands were mentioned by LLMs in responses to this project's prompts.' It specifies the scope (competitor brands, from LLM responses) and distinguishes it from sibling tools, which focus on scans, projects, or models, making its purpose unambiguous.

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 includes a 'WHEN TO USE' section that directly states its context, and explicitly requires 'project_id from lbm_list_projects,' indicating a prerequisite. However, it does not mention when not to use the tool or suggest alternatives, though no obvious alternative exists among siblings.

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