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social_mentions

What people are saying about your words on two public forums, deterministic and without an LLM: Hacker News stories and comments (via the Algolia HN Search API) and Polymarket event comments (via the Gamma API) within the last 1-168 hours (default 48), whole-word and case-insensitive, newest first, deduplicated, up to 50 items with the text (at most 300 characters), a link, the author's public handle and the time; counts per source and each source's ok flag. Public posts as written by their authors; not advice. Price $0.01 per call, paid with USDC over x402.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hoursNolook back this many hours (default 48)
limitNomaximum items (default 20)
queryYessearch words, matched whole-word and case-insensitively against posts and comments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses deduplication, newest-first ordering, the 300-character text truncation, per-source counts and an 'ok' flag for partial failures, plus the paid-access model ($0.01 per call via USDC over x402). These are exactly the operational traits an agent needs before invoking.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose and sources are front-loaded, and nearly every clause adds usable detail. However, it is packed into essentially one long run-on sentence with a trailing disclaimer and pricing clause, which hurts scannability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema or annotations, the description compensates by enumerating the returned fields (text, link, author handle, time, per-source counts, ok flag). Nothing an agent needs to call or interpret the tool correctly appears to be missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents query, hours, and limit, including the whole-word/case-insensitive matching. The description restates the matching rule and hours range but omits the schema's default limit of 20 (it only says 'up to 50 items'), adding little beyond the structured fields.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a concrete resource (public mentions from Hacker News and Polymarket) and scopes it precisely, including the upstream sources (Algolia HN Search API, Gamma API). An agent can distinguish this from news_search or topic_brief without opening the schema, since it explicitly targets forums/comments rather than news articles or synthesized briefs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage context is implied by the mention-search framing and the 1-168h lookback, but there is no explicit statement of when to prefer this over news_search, topic_brief, or claim_check, and no exclusions or prerequisites beyond the payment note. Adequate but leaves routing decisions to inference.

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

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