Record a review verdict on one mention as relevant or not_relevant. This feedback tunes how future mentions are scored for the account. Re-sending the same verdict is safe.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| verdict | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate that this is a write operation (readOnlyHint=false) and idempotent (idempotentHint=true). The description adds meaningful context beyond these: the feedback 'tunes how future mentions are scored for the account' and explicitly reassures that re-sending the same verdict is safe, reinforcing idempotency. No contradictions.
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 crisp sentences, front-loaded with the core action and followed by the consequence and idempotency note. No filler or redundant content; every sentence earns its place.
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?
The tool is simple with only two parameters and no output schema. The description covers the purpose, feedback effect, and idempotency. It does not explain return values or error handling, but given the low complexity and supportive annotations, the description is sufficiently complete for an agent to invoke the tool correctly.
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 mentions the two parameters implicitly: 'one mention' corresponds to 'id', and 'relevant or not_relevant' corresponds to 'verdict'. However, it does not provide details on the format of 'id' or how to obtain it, and only minimally explains 'verdict' by giving the enum values. It adds some value but is not fully compensatory.
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 action ('Record a review verdict'), the target ('on one mention'), and the specific verdict values ('relevant or not_relevant'). It is easily distinguished from sibling tools like search_mentions or get_mention, which focus on retrieval, whereas this focuses on writing feedback.
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 gives clear context: this is for providing feedback on a single mention to tune future scoring. It does not explicitly state when not to use it or list alternatives, but the purpose is distinct enough that context implies when it is appropriate. No exclusions are mentioned, but the intended use case is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct purposes, but the specialized mention getters (get_competitor_signals, get_pain_signals) overlap with get_recent_mentions since that function also supports role filters. The unique filtering criteria for signals are described, reducing ambiguity, but an agent might hesitate between these options.
Tool names mostly follow a verb_noun snake_case pattern, but there is inconsistency between list_keywords and get_recent_mentions for list-like operations. The specialized signal getters also deviate slightly from the standard pattern, though all names remain readable.
With 11 tools, the server is well-scoped for a mention monitoring service. The tool set covers keyword management, mention retrieval, search, digest, and reply drafting without unnecessary overlap or excessive granularity.
The surface provides strong coverage of the domain: keyword lifecycle (create, list, update with pause), mention retrieval (by id, recent, search, digest, signals), and a feedback loop. Minor gaps exist, such as the lack of a delete_keyword or single-keyword getter, but these are workaround-able.
