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Production MCP Template

Production MCP Template

by RichFerry
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

design_refine_with_sampling

Read-onlyIdempotent

Generate enriched rollout or feature briefs by applying host sampling to refine a design based on a stated goal and optional constraints.

Instructions

Use host sampling when available to draft a richer rollout or feature brief.

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": {
      "goal": "<goal>"
    },
    "name": "design_refine_with_sampling"
  }
}

Input Schema

NameRequiredDescriptionDefault
goalYes
constraintsNo

Output Schema

NameRequiredDescriptionDefault
statusYes
draftYes
modelNo
errorNo

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?

Annotations already provide readOnlyHint, idempotentHint, and openWorldHint. The description adds the behavioral nuance of using host sampling conditionally, but does not explain what happens when sampling is unavailable. 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.

Conciseness4/5

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

The description is a single concise sentence, but it sacrifices clarity for brevity. It is front-loaded with the action but could be restructured for better readability.

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?

The tool has two parameters and an output schema, yet the description omits key context such as the meaning of 'host sampling', the outcome when sampling is unavailable, and how the draft is generated. This leaves significant ambiguity for an agent.

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

Parameters2/5

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

Schema description coverage is 0%; the description does not mention the goal or constraints parameters. It adds no meaning beyond the schema's field names and types, failing to compensate for low coverage.

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

Purpose3/5

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

The description states the tool drafts a rollout or feature brief using host sampling, but the term 'host sampling' is unexplained. It vaguely distinguishes from sibling tools but does not clearly define its specific role.

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 explicit guidance on when to use this tool versus alternatives like design_collect_feature_brief or design_tool_contract. The phrase 'when available' hints at a condition but lacks clarity and comparison.

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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