Return recent industry-role mentions that read as demand or pain signals, meaning they carry a suggested action or score at least 80 for relevance. Use this to find people publicly describing a problem the product solves.
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | ||
| from | No | ||
| limit | No | ||
| keyword | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds important behavioral criteria: mentions must 'read as demand or pain signals' and either carry a suggested action or score at least 80. It also scopes to 'recent' mentions. This goes beyond annotations without contradicting them, though it omits details like pagination or parameter effects.
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 long, front-loads the core action, and avoids any filler. The first sentence defines the output and filter criteria; the second sentence gives the use case. Every clause adds value, and the overall structure is highly efficient.
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 provides a strong purpose and usage scenario, and annotations cover the safety profile. However, correct invocation is hampered by missing parameter semantics (especially 'to' and 'from') and no mention of return format or pagination. Given the 4-parameter schema and no output schema, the description is not fully complete, though it is more than minimal.
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 schema has four parameters with zero descriptions (0% schema_description_coverage). The tool description does not explain the meaning of 'to' or 'from' (likely date range but could be user handles) or precisely how 'limit' and 'keyword' function. The description fails to compensate for the lack of schema detail, leaving the agent to guess parameter semantics.
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 'Return' and clearly identifies the resource as 'recent industry-role mentions' while defining what constitutes a pain signal ('carry a suggested action or score at least 80 for relevance'). This distinguishes it from siblings like get_recent_mentions and search_mentions, which are general-purpose.
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 offers clear usage context: 'Use this to find people publicly describing a problem the product solves.' This tells the agent when to select this tool, though it does not explicitly mention alternatives or when not to use it. The guidance is clear but lacks explicit exclusions or alternative tool names.
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.
