syndicate_search

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

No annotations are provided, so the description must cover behavioral traits. It discloses ranking criteria (confirm_count then recency) and provides an example result format. It does not mention pagination, empty result behavior, or any side effects, which is acceptable for a search tool but not exhaustive.

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?

Two sentences plus a single example. The description is front-loaded with the purpose and ranking, immediately informing the agent. Every sentence adds value, and the example clarifies usage without unnecessary detail.

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 no output schema, the description adequately explains what the tool returns (ranked lessons) and shows an example. It does not specify the default limit or max limit (present in schema but not description), nor describe the full structure of a lesson result. Completeness is good but not perfect.

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?

Input schema has 100% description coverage, so the description does not need to restate each parameter. It adds value by explaining how results are ranked (confirm_count, recency) and gives a concrete example illustrating the query parameter. This is sufficient but not exceptional.

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 searches a global knowledge commons and returns ranked lessons. It uses specific verbs ('Search', 'Returns') and distinguishes itself from sibling search tools by emphasizing global community contribution and ranking by confirm_count and recency.

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 recommends using this tool before debugging unknown issues, positioning it as a primary diagnostic step. However, it does not explicitly mention when not to use it or compare directly to siblings like brain_search or fedbrain_search.

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