designsafe-mcp

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approve_submission

Records human approval for a job request and returns the submission token. Use after presenting the trust summary to a human.

Instructions

Record human approval for exactly this job request; returns the token submit_job requires. The calling harness must show the trust summary (snippet, versions, cost, outputs) to a human before calling this.

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": {
      "job": "<job>"
    },
    "name": "approve_submission"
  }
}

Input Schema

Name	Required	Description	Default
`job`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 12, 2026

TDQS

A3.8/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses a human-review prerequisite and the return token, but does not mention whether approval is revocable, what happens with invalid/already-approved jobs, or permissions needed.

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?

Two concise, front-loaded sentences give the core purpose and the critical safety precondition. There is no filler or redundant repetition of schema/annotation 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 covers the tool's purpose, key prerequisite, and return value, which is adequate for a focused approval step. However, the lack of parameter details and unspecified behavior for error cases leaves gaps, especially without annotations to fill in the missing context.

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?

The schema provides only a generic 'job' object with additionalProperties true and no property descriptions, and schema description coverage is 0%. The description adds no detail about the object's required fields or how to construct/reference it, only that it must be the exact job request.

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 the action ('Record human approval'), the target ('exactly this job request'), and the distinctive outcome ('returns the token submit_job requires'). This distinguishes it from sibling tools like validate_job or submit_job.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly specifies a mandatory precondition: the harness must show the trust summary to a human before calling. It also implies when to use it by noting the token is required by submit_job, though it does not explicitly name alternatives or exclusions.

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