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EverythingMeetsAI

by com.everythingmeetsai
OverviewDiscussionsAdmin

Search AI-in-sector stories

search_stories
Read-onlyIdempotent

Search EverythingMeetsAI's record of AI's impact on real-world sectors: source-linked headlines placed in one of 18 sectors, with outlet, country, development type and time, since 24 June 2026. Filter by sector, country, outlet, development type, headline keyword and date. Returns headline, publisher link, outlet, sector and times; never article text. An empty result means no headline matched, not that nothing happened.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "search_stories"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNoISO date or datetime; stories first reported on or before.
fromNoISO date or datetime; stories first reported on or after.
sortNoDefault newest.
limitNoPage size. Anonymous callers get at most 25, keyed 50.
queryNoHeadline keyword search (web-search syntax: quotes, OR, -exclude). Not semantic.
offsetNoPage start, for the next page.
outletNoOutlet slugs (see list_outlets).
sectorNoPrimary sector slugs to include. Sector slugs: see list_sectors (e.g. healthcare_life_sciences, law, retail, regulation_government, financial_services, manufacturing_robotics).
countryNoISO 3166-1 alpha-2 codes (or EU). Set on ~62% of stories.
paywalledNoOnly paywalled (true) or only free-to-read (false) stories.
development_typeNoDevelopment-type slugs (see list_types). Set on ~8% of stories; most types are never used.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/closed-world, so the safety profile is covered. The description adds real value beyond that: it discloses the exact return fields, that article text is never returned, and that an empty result means 'no headline matched, not that nothing happened' — a genuinely useful interpretation hint.

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?

Front-loaded with the core purpose, followed by filters and return shape, then a short caveat sentence. Dense and largely waste-free, though the filter enumeration mildly duplicates the schema and could be trimmed.

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

Completeness4/5

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

With 11 parameters, no required fields, and no output schema, the description does the needed work by listing return fields and clarifying empty results. It omits pagination/wrapper behavior, but the schema covers limit/offset, so coverage is nearly complete.

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 coverage is 100%, so every parameter (including the 'from'/'to', 'query' syntax, and slug-based arrays) is already documented in the schema. The description only restates the filter dimensions ('Filter by sector, country, outlet, development type...') without adding syntax or format detail, so the baseline of 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 and resource ('Search ... record of AI's impact on real-world sectors'), plus scope (18 sectors, source-linked headlines, coverage since 24 June 2026). The clause 'never article text' implicitly differentiates it from get_story, so an agent can tell its role apart from siblings.

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?

The description enumerates the filterable dimensions and clarifies empty-result meaning, which implies usage, but it never states when to choose this tool over siblings like get_story or changes_since. No explicit when/when-not routing is provided.

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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