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AI Incident Law

AI Incident Law

by snapsynapse
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

search_records

Search AI litigation, regulation, and enforcement records by keyword across titles, descriptions, parties, jurisdictions, tags, and metadata. Get relevant public-record matches.

Instructions

Search across record titles, descriptions, parties, jurisdictions, tags, and source metadata.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search_records"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum matches to return. Default 10.
queryYesCase-insensitive search query.
datasetNoOptional dataset bucket filter.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations, the description should disclose behavioral traits like full-text search, pagination, or rate limits, but it only lists searched fields. Critical context for safe invocation is missing.

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?

The description is a single concise sentence without fluff, but it omits important usage details. It earns its place but could be more informative.

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

Completeness2/5

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

Given no output schema and simple input schema, the description is incomplete. It fails to mention return format, ordering, pagination, or combination rules for parameters like 'dataset', leaving gaps for effective usage.

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 baseline is 3. The description adds value by clarifying the scope of the 'query' parameter (searches across listed fields), which the schema does not specify, aiding proper parameter usage.

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 clearly states the tool searches across multiple specific fields (titles, descriptions, etc.), using the verb 'Search' and resource 'records', distinguishing it from sibling tools like 'get_record' (single record) and 'list_records' (all records).

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives like 'get_record' or 'list_records'. Implicitly, it's for searching but lacks explicit when-to-use or when-not-to-use advice.

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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