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Neotoma

Neotoma

by markmhendrickson
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get_schema_recommendations

Retrieve schema update recommendations for a specific entity type, sourced from raw fragments, agent suggestions, or inference, to identify needed schema changes.

Instructions

Get schema update recommendations for an entity type from raw_fragments analysis, agent suggestions, or inference.

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": {
      "entity_type": "<entity_type>"
    },
    "name": "get_schema_recommendations"
  }
}

Input Schema

NameRequiredDescriptionDefault
sourceNoRecommendation source (default: all)
statusNoFilter by recommendation status (default: pending)
user_idNoUser ID for user-specific recommendations (optional)
entity_typeYesEntity type to get recommendations for

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

B3.2/5.0
Behavior2/5

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

With no annotations, description bears full burden. It implies a read operation but doesn't confirm safety, side effects, or response behavior. No mention of authorization, rate limits, or what happens if no recommendations exist.

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?

Single sentence efficiently conveys action and sources. Front-loaded with verb and resource, no redundancy.

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?

No output schema provided, but description does not describe what recommendations contain (e.g., field changes, confidence). Missing details on pagination or ordering. Incomplete for a retrieval tool.

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 has 100% description coverage. Description adds 'from raw_fragments analysis, agent suggestions, or inference' which partially overlaps with source enum. Adds marginal value beyond schema.

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?

Description clearly states verb 'get', resource 'schema update recommendations', and scope 'for an entity type from raw_fragments, agent suggestions, or inference'. Distinguishes from sibling tools like analyze_schema_candidates by focusing on recommendations.

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 on when to use this tool vs alternatives like analyze_schema_candidates or other sibling tools. Lacks context about prerequisites or typical scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

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