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

The description adds valuable behavioral detail beyond annotations: it is deterministic, involves no LLM, takes 2-90 seconds, clones a repository, and redacts secret evidence. These details inform agent expectations about latency, execution model, and output safety. There is no contradiction with the 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 dense but well-structured: action first, then scan scope, then output format, then behavioral traits. Every sentence adds useful information without fluff or redundancy.

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 single-parameter read-only tool, this description is complete: it explains input constraints, scan coverage, output structure, runtime expectation, and determinism. Even without an output schema, the agent can predict the return format.

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?

The schema already fully documents the single url parameter with acceptable host formats, so the description does not need to repeat it. The description contributes context about what the scan does, but not additional parameter-level semantics 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?

The description clearly states the tool's action: clone a public git repository and run feldspar-scan, then lists the exact scan categories and output. This goes well beyond the tool name and distinguishes it from the sibling audit_pricing.

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 clear context: it is for scanning public git repositories and returns dependency advisories, secret findings, and lint results. It does not explicitly name audit_pricing as an alternative or state when not to use it, but the context is sufficiently clear.

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