find_precedents

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

No annotations are present, so the description carries the full burden. It discloses the hybrid similarity search behavior, which implies a read-only semantic lookup, but does not state that it is non-destructive, how results are ordered, or what the return payload looks like.

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?

One compact sentence with no filler; the core action and method are front-loaded. It is easy to scan and every word contributes to understanding.

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?

For a two-parameter search tool the description is minimally adequate, but with no output schema or annotations it still leaves uncertainty about return structure and lacks usage context relative to sibling query tools. It could be improved with a note on result ranking or a sample of what is returned.

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?

The input schema already documents both parameters with 100% coverage, so the description is not required to add much. It adds little beyond 'hybrid similarity search' and does not elaborate on max_results behavior or format, so the baseline of 3 applies.

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 uses a specific verb ('find'), a clear resource ('past decisions'), and a scope qualifier ('similar to a given scenario') that signals semantic matching. It does not explicitly contrast with sibling query_decisions, but the hybrid similarity phrasing helps an agent tell them apart.

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?

No guidance is given on when to use find_precedents over query_decisions, run_reasoning, or get_causal_chain, nor are there exclusions or prerequisites. An agent must infer the use case from the name and description alone.

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