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Neotoma

Neotoma

by markmhendrickson
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analyze_schema_candidates

Analyze raw data fragments to identify fields that should become schema fields. Get recommendations with confidence scores based on frequency and type consistency.

Instructions

Analyze raw_fragments to identify fields that should be promoted to schema fields. Returns recommendations with confidence scores based on frequency and type consistency.

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": "analyze_schema_candidates"
  }
}

Input Schema

NameRequiredDescriptionDefault
user_idNoUser ID for user-specific analysis (optional)
entity_typeNoEntity type to analyze (optional, analyzes all if not provided)
min_frequencyNoMinimum frequency threshold (default: 5)
min_confidenceNoMinimum confidence score 0-1 (default: 0.8)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.15.0
  2. Removedv0.14.0
  3. Addedv0.12.1
  4. Removedv0.11.0
  5. First observedv0.1.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are present, so the description must fully convey behavior. It only states the output (recommendations with confidence scores) but does not disclose whether the tool is read-only, requires special permissions, or has side effects. This is a significant gap.

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?

The description is two sentences, front-loaded with the action, and contains no extraneous words. Every sentence adds value.

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?

Given the lack of output schema, the description should ideally clarify the structure of recommendations. It states 'recommendations with confidence scores' but no further detail on format or nesting. Adequate but not rich.

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 the baseline is 3. The description does not add additional meaning beyond what the schema already provides for each parameter, though it does mention 'confidence scores' which relates to min_confidence.

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 verb 'Analyze' and the resource 'raw_fragments' to identify schema field candidates. It distinguishes from siblings like 'get_schema_recommendations' and 'register_schema' by focusing on analysis rather than retrieval or registration.

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 (e.g., 'get_schema_recommendations'). The description does not specify prerequisites or conditions for use, leaving the agent to infer context.

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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