Fetch CodeFactor Issues

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

No annotations are provided, so the description must fully disclose behavior, but it only mentions fetching and normalization. It omits authentication, rate limits, error handling, pagination, and other behavioral traits, leaving significant gaps.

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, front-loaded with the core action. It is efficient but could be slightly more informative without becoming verbose, hence a 4.

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?

With eight parameters, no output schema, and no annotations, the description is insufficient. It fails to explain how parameters interact (e.g., maxPages with allPages), what 'normalized issue data' means, or provide an overall workflow context.

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 input schema has 100% description coverage, so the baseline is 3. The description adds no extra parameter context beyond the schema, which already documents all eight parameters with descriptions.

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 verb 'Fetch', the resource 'CodeFactor repository issues', and includes 'normalized issue data', distinguishing it from sibling tools like build_codefactor_prompt, parse_codefactor_html, and summarize_codefactor_issues.

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 implies usage as a fetch tool but provides no explicit guidance on when to use it versus alternatives, nor does it mention prerequisites or when not to use it.

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