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Hn Search

hn_search
Read-only

Full-text search of Hacker News stories or comments through the Algolia HN API: title, URL, author, points, comment count, time and HN link; comments include their text (max 500 characters). Filters: date range (from, to as YYYY-MM-DD), minimum points, sort by relevance or date. Covers the public HN index only; limit max 25. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Input Schema

NameRequiredDescriptionDefault
qYesSearch words (1-200 characters)
toNoLatest creation date YYYY-MM-DD (optional)
fromNoEarliest creation date YYYY-MM-DD (optional)
sortNorelevance (default) or date (newest first)
typeNostory (default) or comment
limitNoResults, 1-25 (default 10)
minPointsNoMinimum points (default 0)

Output Schema

NameRequiredDescriptionDefault
sortNo
typeNo
countNo
queryNo
nbHitsNo
sourceNo
resultsNo
checkedAtNo

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?

Goes well beyond the readOnlyHint/openWorldHint annotations: it discloses a paid-call model ($0.002 USDC per successful call via x402 on Base, Solana or Arc), that failed calls are not charged, that comment text is truncated at 500 characters, and that the result cap is 25. This is exactly the kind of operational context annotations cannot convey.

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?

Dense but front-loaded: purpose first, then returned fields, then filters, then scope and pricing. Every clause carries information, though the single long run-on sentence with stacked semicolons is slightly harder to scan than it could be.

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 an output schema present, return values need no further explanation, yet the description still summarizes them. Pricing, payment rails, scope limits and truncation behavior are all covered, leaving nothing an agent needs to call it correctly unaddressed.

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 every parameter including the YYYY-MM-DD format and enum-like values for sort and type. The description restates the filters and the limit cap but adds no syntax or default detail beyond what is already structured, so the baseline 3 applies.

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+resource ('Full-text search of Hacker News stories or comments') plus the backing source (Algolia HN API), which cleanly separates it from the sibling 'hn' tool that lists HN content rather than searching it. An agent can pick it without opening the schema.

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 is implied by 'full-text search' and the filter list, and it notes 'Covers the public HN index only; limit max 25', but it never states when to prefer this over the sibling 'hn' tool or what to do when the 25-result cap is insufficient. Adequate but with clear routing gaps.

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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