llm_team_report

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

No annotations provided, so description carries full burden. Reveals auto-detection of user (git email) and project (git remote), and that it displays reports. Does not disclose read-only nature, caching, or other behavioral traits beyond what is described.

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?

Extremely concise: one sentence describing purpose, a bullet list of content, and a clean Args section. No redundant words, well-structured.

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 single parameter, presence of output schema, and simple report function, the description adequately covers behavior (auto-detection, content breakdown) and parameter usage. No gaps.

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?

Input schema has 0% description coverage; parameter 'period' only has type and default. Description's 'Args' section explicitly lists permitted values ('today', 'week', 'month', 'all'), adding essential 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?

Clearly states verb 'Show' and resource 'team savings report' with specific content (call counts, cost savings, free-tier usage, top models). Lacks explicit differentiation from siblings like llm_savings or llm_usage, but purpose is well-defined.

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?

No guidance on when to use this tool versus alternatives. Does not specify prerequisites, scenarios, or when not to use. The description only explains functionality.

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