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plur_validate_meta

Validate meta-engram templates by testing them against a new domain, updating confidence and domain coverage.

Instructions

Test a meta-engram template against engrams from a new domain — updates confidence and domain_coverage

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": {
      "meta_engram_id": "<meta_engram_id>",
      "test_domain": "<test_domain>",
      "llm_base_url": "<llm_base_url>",
      "llm_api_key": "<llm_api_key>"
    },
    "name": "plur_validate_meta"
  }
}

Input Schema

NameRequiredDescriptionDefault
llm_modelNoModel name (default: gpt-4o-mini)
llm_api_keyYesAPI key for the LLM
test_domainYesDomain to test against (e.g. medicine)
llm_base_urlYesOpenAI-compatible API base URL
meta_engram_idYesMETA- engram ID to validate

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.14.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations only include idempotentHint=false and destructiveHint=false. The description adds behavioral context by stating it 'updates confidence and domain_coverage', which indicates a mutation. No contradiction with annotations.

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

Conciseness5/5

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

A single, concise sentence of 13 words communicates the tool's purpose without any redundant or unnecessary information.

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

Completeness3/5

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

The description is adequate for a simple tool but lacks explanation of the return value, prerequisites (e.g., existence of meta-engram), and any side effects beyond the stated updates. Given no output schema, more detail would help.

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?

Input schema has 100% coverage of parameter descriptions. The description adds no additional parameter-specific details beyond the schema, so a baseline of 3 is appropriate.

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 it tests a meta-engram template against engrams from a new domain, using specific verbs and resources. It distinguishes itself from sibling tools like plur_extract_meta (extraction) and plur_meta_engrams (listing) by focusing on validation.

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 implies usage for validating meta-engrams but provides no explicit guidance on when to use this tool versus its siblings or when not to use it. No alternatives or exclusions are mentioned.

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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