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paperclip-mcp

paperclip-mcp

by shanewiseman
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Update decision training notes

pc_patch_decision_training_by_id

Update notes for a decision training record by specifying its ID and the new notes content. Use this tool to modify training notes as needed.

Instructions

Update decision training notes

Paperclip operation: PATCH /api/decision-training/{id}. Authorization class: board_or_agent.

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": {
      "path": "<path>",
      "body": "<body>"
    },
    "name": "pc_patch_decision_training_by_id"
  }
}

Input Schema

NameRequiredDescriptionDefault
bodyYes
pathYes

Output Schema

NameRequiredDescriptionDefault
bodyYes
headersYes
encodingYes
status_codeYes
content_typeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior3/5

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

The description adds the authorization class 'board_or_agent' and confirms it is a PATCH operation, which aligns with annotations (readOnlyHint=false, destructiveHint=false). However, it does not disclose any additional behavioral traits such as idempotency, side effects, or error conditions beyond what annotations already indicate.

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 concise with two sentences: the first states the purpose, the second provides operational context (HTTP method and auth). It is front-loaded and avoids unnecessary text, but could include parameter details without becoming verbose.

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?

While an output schema exists (so return values are documented elsewhere), the description lacks context about what 'decision training' is and how this update fits into a workflow. With no parameter descriptions and minimal usage guidance, the agent may struggle to use this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning no parameter descriptions exist in the schema. The tool description does not explain the 'body.notes' or 'path.id' parameters at all, leaving the agent without guidance on their meaning or format. This is a significant gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Update decision training notes', which specifies a verb ('Update') and a resource ('decision training notes'). This is specific and distinct from sibling tools like get or delete operations for the same resource, though it could further clarify that only the 'notes' field is updated.

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?

The description mentions the HTTP method and authorization class, but does not indicate when to use this tool versus alternatives such as pc_get_decision_training_by_id or pc_post_companies_by_company_id_decision_training. No guidance on prerequisites or context 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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