lbm_list_results

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

Beyond annotations (readOnlyHint, idempotentHint), the description discloses return format (Compact CSV with specific fields), default limit (20), and the option for full JSON via include_all_fields. No contradictions with 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?

The description is compact, uses clear uppercase labels (WHEN TO USE, REQUIRES, RETURNS, NEXT STEP), and is front-loaded with essential info. Every sentence adds value without waste.

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 7 parameters (fully described in schema) and no output schema, the description covers all critical aspects: when to use, prerequisites, return format, default behavior, and next step. It adequately supports the agent in invoking the tool correctly.

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 context beyond parameter descriptions, such as the overall return format and the recommendation for compact CSV. It reinforces the meaning of include_all_fields and the default limit, though some parameter details are redundant with 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 'To get monitoring results for a project — how LLMs responded to brand monitoring prompts.' This uses a specific verb ('get') and resource, distinguishing it from siblings like lbm_list_projects (lists projects) and lbm_get_transcript (gets full transcript).

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?

Explicitly starts with 'WHEN TO USE' and provides prerequisite ('project_id from lbm_list_projects'), plus a 'NEXT STEP' to use lbm_get_transcript for full text, guiding the agent on when and after to use this tool.

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