check_duplicate_issue

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

With no annotations, the description carries the behavioral burden. It discloses that the tool retrieves open issues and performs 'cheap lexical candidate ranking,' and it explicitly sets expectations that results are candidates, not definitive duplicates. This is transparent about the tool's limitations, though it does not mention auth, rate limits, or empty-result behavior, which would make it fully transparent.

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 three sentences: the first states the core purpose, the second explains the mechanism and caveat, and the third gives an exclusionary usage rule. Every sentence carries useful information 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?

The tool has three parameters, no output schema, and no annotations. The description explains the return value conceptually ('candidates'), the ranking method, and the relationship to sibling tools. While it does not describe the exact return format, the conceptual explanation is sufficient for an AI to invoke the tool correctly and interpret the results appropriately.

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 already covers all three parameters with descriptions (owner, repo, description) at 100% coverage. The tool description does not add new parameter-level semantics beyond what the schema provides, so the baseline score of 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 opens with a specific verb-resource pair: 'Find the most likely existing open GitHub issues that could be related to a proposed issue.' This clearly distinguishes the tool from siblings like list_github_issues, especially with the explicit instruction not to call that sibling for duplicate checking.

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 explicit usage context: it is for duplicate checking against existing open issues, and it warns against using list_github_issues separately for this purpose. It also clarifies that results are candidates only and semantic determination is the AI's responsibility, which guides appropriate use.

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