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

Annotations only provide readOnlyHint=true, while the description adds rich behavioral detail: ranking by relevance, resolving different input types (stacktrace, diff), neighborhood expansion via spreading activation, and output format (path:line). This goes well beyond the minimal annotation.

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 concise (4-5 sentences) yet packs substantial information. It front-loads the core purpose and covers key variations. Every sentence contributes value, avoiding 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?

Given the tool's complexity (5 parameters, output schema exists), the description covers the primary use cases and output characteristics (path:line). It does not need to restate the output schema, but provides enough context for effective use.

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?

All 5 parameters are described in the schema (100% coverage), but the description adds meaningful context: examples for 'query' (paste raw stacktrace, test id), explanation of 'expand' (Personalized-PageRank), and 'kind' auto-detect behavior. This enhances understanding beyond schema defaults.

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 transforms text into ranked graph nodes, serving as an on-ramp to the graph. It specifies that it handles symbols, keywords, stacktraces, test IDs, and diffs, but does not explicitly differentiate from sibling tools like 'trace' or 'orient', though it mentions 'read' for subsequent steps.

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 context: use for initial search or failure resolution, with 'expand=true' for neighborhood exploration. It suggests reading top hits via 'read', but lacks explicit when-not-to-use guidelines or comparisons with sibling tools like 'impact' or 'trace'.

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