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

Annotations already declare readOnly, idempotent, non-destructive, and openWorld, so the safety profile is covered. The description usefully adds what data sources are inspected and the validate-vs-flag outcome, but omits practically relevant traits for a GitHub-scraping tool such as unauthenticated rate limits or failure behavior on private/missing accounts.

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 sentences, front-loaded with the inspection scope and closed by the behavioral outcome. Every clause earns its place with no redundancy or filler.

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?

An output schema exists, so return values need no explanation, and annotations cover the safety profile for a read-only tool. The description is nearly complete; only operational caveats like GitHub rate limiting or behavior on unresolvable usernames are missing.

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 description coverage is 100%, so both parameters (technical_claims, candidate_github_or_resume) are already fully documented by the schema. The description adds no parameter-level meaning such as accepted username vs URL vs resume formats, so the baseline 3 applies.

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?

Specific verbs (inspect, fact-check, validate, flag) applied to a concrete resource (public GitHub repositories, languages, commits, stars, forks). An agent understands exactly what the tool examines, but the description never distinguishes it from close siblings such as evidence_validator or huggingface_proofer, leaving the routing decision to inference.

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 phrase 'fact-check candidate technical claims' implies the usage context, and the second sentence implies the outcome (validating vs flagging). There is no explicit when-to-use, no exclusion, and no named alternative among the seven siblings, so the agent must infer when this is preferred over evidence_validator.

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