faf_readme

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

Annotations declare readOnlyHint=false and destructiveHint=false, but the description adds minimal behavioral detail beyond 'Smart pattern matching'. It does not disclose session context side effects (though the schema describes path's effect), nor does it explain what happens to existing human_context values or the preview vs apply behavior.

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 concise sentence (15 words) that conveys the core action and scope. It is front-loaded and efficient, though it could benefit from a brief note on parameter behavior.

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 tool with three boolean parameters and no output schema, the description covers the primary function but omits context on what 'human_context' is, how 'Smart pattern matching' works, and what the return format looks like. It leaves some gaps for an AI agent to infer.

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% with clear parameter descriptions. The description adds no additional parameter meaning beyond what the schema provides, so baseline score 3 is appropriate.

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 purpose: 'Extract 6 Ws (Who/What/Why/Where/When/How) from README.md into human_context'. It uses a specific verb ('Extract') and resources ('README.md', 'human_context'), and the mention of 'Smart pattern matching' adds differentiation from siblings like faf_read or faf_context.

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 provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, limitations, or contrast with other faf_* tools, leaving the AI agent to infer usage context from the name alone.

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