faf_score

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

Description aligns with readOnlyHint annotation and adds details on return structure (percentage, tier, optional slot-by-slot breakdown with suggestions). No contradictions.

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?

Two concise sentences, front-loaded with action and output, each sentence serves a clear purpose.

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?

Schema is fully covered, no output schema needed as description explains return object, readOnlyHint covers safety, and all aspects (purpose, usage, parameters, output) are addressed.

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%, description adds value by explaining 'details' as providing 'slot-by-slot breakdown with improvement suggestions' and 'path' as setting session context.

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?

Description clearly states verb 'calculate', resource 'AI-readiness score', and scope. Distinguishes from siblings like faf_context and faf_check.

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 says 'Use this to measure how complete the AI context is and what to fill next', providing clear when-to-use guidance. Lacks explicit exclusions but purpose sufficiently contrasts alternatives.

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