get_concept

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

With no annotations, the description carries the transparency burden. It discloses case-insensitive name matching and the scope of returned data, and implies read-only behavior with 'get'. It does not mention behavior for unknown IDs or not-found cases, but for a single-concept getter this is acceptable.

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: the first front-loads the action, target, and return fields; the second gives usage context. No wasted words or repetition of schema details.

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 simple read tool with two optional parameters and no output schema, the description adequately covers what the tool returns, how to identify the target concept, and when to use it. The absence of an error-handling note is minor given the tool's straightforward nature.

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 provides full descriptions for both parameters, including case-insensitivity and first-match-wins behavior. The description only paraphrases the id-or-name distinction without adding new meaning, so it meets the baseline for high schema coverage.

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 retrieves full detail for exactly one concept by id or name, listing the included fields (definition, measurement hint, measured entities with pendoIds, causes, playbook actions). This distinguishes it from sibling tools like get_product_map which focuses on map-level identification.

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 instructs to use this tool after get_product_map has identified the relevant concept, providing clear sequencing and implicit differentiation from alternatives like lookup_ontology or list_coverage_gaps.

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