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

Annotations only cover read-only/open-world, so the description adds real value: result ranking ('most-discussed first'), the fallback search strategy (exact phrase then keywords), the shape of each result, and an explicit cost model ($0.004 USDC per call via x402). The paid-call disclosure is exactly the kind of behavioral fact annotations cannot express.

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?

Compact and front-loaded: the use case leads, then matching strategy, then returned fields, then cost. Every clause carries information; only the initial rhetorical question is stylistically loose rather than informative.

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 no output schema, the description takes on the burden of describing the return shape and does so concretely (title, repo, state, comments, labels, link, excerpt). Cost, ranking, and matching behavior are all covered; only alternative-tool routing is 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 coverage is 80%, so the schema already documents q, repo, sort, limit, and state. The description reinforces ranking (most-discussed = comment sort) and confirms open/closed filtering, but does not add format or constraint details beyond the schema, so the baseline of 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 verb+resource: 'Searches GitHub issues for an error message', with the matching strategy (exact phrase first, then keywords) and returned fields enumerated. It does not explicitly distinguish itself from siblings like github_search or github_code, so an agent must infer the boundary.

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 framing question 'Has anyone hit this error?' implies the intended use case (troubleshooting an error against real-world reports), which is genuinely useful context. However, there is no explicit when/when-not guidance and no mention of github_search or github_code as alternatives for broader or code-scoped lookups.

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