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ScrapeMole Pulse: FX rates (ECB), currency conversion, time zones, weather (global + official US NWS forecasts and alerts), Hacker News, public holidays and geocoding for AI agents: Hacker News stories

hn
Read-onlyIdempotent

Use to see what the tech/startup community is reading right now or to monitor launches: returns up to 30 stories from one Hacker News list (top = front page, new, best, ask, show, job) via the official HN API, each with title, external URL and domain, score, comment count, posted time and the news.ycombinator.com discussion link. Usernames are omitted (non-personal data). For full-text HN search and complete comment threads use ScrapeMole Social: https://social.scrapemole.workers.dev/v1/hn/search and /v1/hn/thread. Paid tool: x402 USDC on Base, $0.002 per successful call; call without payment to receive the PaymentRequired object.

Input Schema

NameRequiredDescriptionDefault
listNotop, new, best, ask, show or job.top
limitNoStories to return (1-30).10

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnly, openWorld and idempotent, so the safety profile is covered. The description adds real value beyond them: usernames are omitted (privacy posture), the 30-story cap, and critically the paid-access model (x402 USDC on Base at $0.002/call, with a PaymentRequired object returned on unpaid calls). Only the exact return payload shape is left implicit, and that is described in the purpose sentence.

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?

A single dense sentence plus a payment caveat, front-loaded with the purpose before the routing and pricing details. Every clause carries information, though the run-on length slightly 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?

No output schema exists, so the description compensates by enumerating returned fields (title, external URL and domain, score, comment count, posted time, discussion link). Purpose, filtering, pricing and privacy behavior are all covered for a two-parameter read tool.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds meaning the schema does not: 'top = front page' glosses the enum value, and it reaffirms the 1-30 limit range. Marginal but genuine added value.

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?

States a specific verb and resource — returns up to 30 stories from one Hacker News list — and enumerates the list variants (top, new, best, ask, show, job). Siblings are all unrelated services (fx, geocode, weather, holidays), so the tool is trivially distinguishable.

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

Usage Guidelines5/5

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

Explicitly frames when to use it ("see what the tech/startup community is reading right now or to monitor launches") and where to go instead for full-text search and complete comment threads, naming the alternative endpoints. Nothing is left 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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