yang_chercher

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

With no annotations, the description carries the full transparency burden. It discloses relevance ranking, French language acceptance, version fallback behavior (most recent installed version used and approximation declared), and the return structure (path, node kind, data type, vendor description). This goes beyond a basic operation statement, though it does not mention potential side effects or error conditions.

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 a moderately long paragraph but every sentence adds value: purpose, use examples, language, vendors, version behavior, and return items. It is front-loaded with the primary function and avoids tautology. It could be slightly more concise, but the length is justified by the 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?

For a search tool with moderate complexity, the description covers purpose, inputs, outputs, and fallback behavior. The mention of the return items compensates for the lack of an explicit output schema. The only gap is the omission of the 'limite' parameter and potential explicit differentiation from the sibling tool, but overall it is reasonably 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 description coverage is 0%, so the description must compensate. It explains 'sujet' as a natural-language query, 'plateforme' via vendor examples (nokia_sros, cisco_iosxe, arista_eos), and 'version' with an example ('24.3.R3') and optionality. However, it entirely omits the 'limite' parameter and does not specify exact value formats for 'plateforme', leaving a notable gap.

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 finds gNMI paths carrying given information and ranks them by relevance ('Trouve les chemins gNMI qui portent une information donnée, classés du plus pertinent au moins pertinent'). It identifies a specific verb, resource, and behavior, making the purpose clear. However, it does not explicitly distinguish itself from the sibling tool 'yang_detail', missing the opportunity for differentiation.

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?

The description provides clear usage context: it explains natural-language input with examples ('routes actives et inactives', 'transceiver SFP'), mentions supported vendors, and details the optional 'version' parameter with fallback behavior. It does not explicitly exclude scenarios or recommend the sibling tool, but the context is sufficient for typical use.

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