cache_warmup

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

No annotations provided, so description carries full burden. Discloses key behaviors: computes embedding, checks similarity (>=0.98), writes to Valkey+pgvector, requires API key. Could mention overwrite/update policy, but overall good transparency.

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?

Three concise sentences: purpose, process, use case, prerequisite. No fluff, front-loaded with key action. Excellent economy of 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?

Covers purpose, workflow, use case, and requirement. Lacks return value description (no output schema) and error handling details. Still, for a seeding tool with moderate complexity, fairly complete.

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 100%, so baseline is 3. However, description adds process-level context (embedding, similarity, write) that clarifies how parameters like entries and auto_namespace interact, raising value 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?

Description clearly states 'Pre-warm the semantic cache with a list of prompt/value pairs,' uses a specific verb and resource. It distinguishes from siblings like cache_set by explaining the batch embedding and similarity check process.

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: 'seed FAQ responses, product descriptions, or known-good LLM answers before the first real user traffic.' Mentions prerequisite OPENAI_API_KEY. Does not name alternatives but context implies single-entry tools exist.

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