Return the most recent mentions matched for this account, newest first, each with its AI summary, sentiment, relevance score, and suggested action. Filter by keyword role, specific keyword, source, sentiment, and date range. Use this to answer "what came in lately".
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | ||
| from | No | ||
| role | No | ||
| limit | No | ||
| source | No | ||
| keyword | No | ||
| sentiment | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows it's safe. The description adds behavioral detail beyond the annotations: output ordering (newest first), return fields, and account-specific matching, which is useful context.
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 two sentences, front-loaded with the main purpose and return details, followed by filters and use case. No unnecessary words or repetition.
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 description covers purpose, output fields, ordering, filters, and usage context. With readOnly annotations and no output schema, this is fairly complete, though date range format and limit behavior are left unspecified.
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 has 7 params with no descriptions (0% coverage). The description mentions filtering by role, keyword, source, sentiment, and date range, covering most parameters, but omits limit and doesn't explain the format for to/from. It partially compensates for the lack of schema descriptions.
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 'Return the most recent mentions matched for this account, newest first' and lists specific return fields (AI summary, sentiment, relevance score, suggested action). It also enumerates filter dimensions (keyword role, keyword, source, sentiment, date range), distinguishing it from siblings like search_mentions and get_mention.
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?
It explicitly says 'Use this to answer "what came in lately"' which gives a clear use case. It does not mention when not to use it or name alternative tools, but the context is sufficient for guiding selection among siblings.
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.
