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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, but the description adds substantial behavioral context beyond that: ranking by relevance, default limit 5 capped server-side, results may include first-party agentic patterns, and the nuanced relevance preference rule ('never outranks a genuine failing-principle match; a pattern whose only relation to a failing principle is 'depends' receives no such match at all'). This gives the agent a true sense of what the tool does behaviorally.

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 fairly long but tightly packed with essential information. It front-loads the core action and then logically builds: filters, return payload, default limit, usage guidance, and pattern-specific nuances. No filler sentences; each clause adds meaning, though a slightly more compact structure would be ideal.

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 6 parameters, an output schema present, and complex ranking/filter behavior, the description is remarkably complete. It covers return payload fields (slug, title, summary, etc.), default and cap behavior, usage alternatives, and the tricky pattern-inclusion rules. The output schema handles return structure details, so the description's job is done well.

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 semantic value beyond the schema: it clarifies principle_ids as 'only examples covering those principles', explains pattern_family implies patterns only, and gives concrete library examples ('langgraph', 'openai'). It also explains the overall search+filters behavior, going beyond bare parameter names.

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?

Opens with a specific verb+resource: 'Search curated examples by free-text query, ranked by relevance.' It clearly distinguishes itself from siblings by naming alternatives in usage guidance: 'prefer examples.get when you already have the slug; prefer guides.search when the user wants a full walkthrough; prefer principles.search when the user wants doctrine guidance.'

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?

Explicitly states when to use this tool: 'Use this when the user describes a use case, technique, or library and wants matching examples.' It also gives explicit exclusions and alternatives: 'prefer examples.get when you already have the slug; prefer guides.search when the user wants a full walkthrough; prefer principles.search when the user wants doctrine guidance, not an implementation.' This is textbook usage guidance.

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