query

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

Annotations confirm safety (readOnly, idempotent, non-destructive). The description adds behavioral traits: ranking prioritization ('production/app defs rank above sample/test/fixture/style noise'), follow-up tool suggestions (context_bundle, impact), and token-efficiency behavior ('Lower = fewer tokens, sharper focus'). No contradictions with annotations.

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 dense but each sentence adds value. It front-loads core purpose and differentiation. While efficient, the long first sentence could be slightly restructured for easier parsing. Still, no wasted words.

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 10 parameters, no output schema, the description covers tool usage comprehensively: algorithm details, ranking behavior, parameter advice, fallback strategies, and follow-up tools. An agent has sufficient information to invoke correctly.

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 baseline is 3. The description adds extra meaning beyond schema: for 'limit', it clarifies default behavior ('default 24'); for 'top_k', explains trade-off ('Lower = fewer tokens, sharper focus'); for 'include_context_pack', provides use-case context. These enhancements justify above baseline.

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's purpose: 'Locate symbols in the indexed graph' with specific algorithmic details (BM25/FTS, graph expand, RRF, optional vector channel). It explicitly distinguishes from web search, a sibling tool, enhancing clarity.

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?

Provides explicit when-to-use guidance: 'Prefer search_hybrid when you also want a package public_api_map.' Also offers context-specific advice such as 'for broad/architecture questions set include_context_pack=true and limit 24-32' and fallback instructions on empty hits ('rephrase, ast_query, or analyze').

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