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designsafe-mcp

designsafe-mcp

by kks32
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

write_manifest

Emits a provenance manifest that makes a submitted job reproducible, refusing incomplete or unverified requests to ensure provenance integrity.

Instructions

Emit the provenance manifest that makes the run reproducible.

Refuses incomplete provenance: the job must be a fully built request (app, name, resources, inputs) and the uuid must belong to a job this server submitted. A manifest that cannot reproduce the run is worse than none.

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": {
      "request": "<request>",
      "snippet_ids": "<snippet_ids>",
      "job": "<job>",
      "uuid": "<uuid>",
      "out_path": "<out_path>"
    },
    "name": "write_manifest"
  }
}

Input Schema

NameRequiredDescriptionDefault
jobYes
uuidYes
requestYes
out_pathYes
snippet_idsYes
estimated_suNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses a key behavioral trait: the tool 'Refuses incomplete provenance' and explains the prerequisites for success. This goes beyond a simple write operation, though it stops short of mentioning file-writing side effects or output details.

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 three sentences long, each earning its place: the first states the core action, the second details validation constraints, and the third provides a rationale. No unnecessary content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has six parameters and no annotations, the description provides sufficient context about the purpose and the conditions for use. An output schema exists, so return-value details are not needed. The mention of uuid belonging to a submitted job suggests workflow placement, making it reasonably complete.

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?

With 0% schema description coverage, the description adds meaning to two key parameters: 'job' (must be fully built with app, name, resources, inputs) and 'uuid' (must belong to a server-submitted job). However, it leaves snippet_ids, out_path, and estimated_su unexplained, with only out_path being self-explanatory.

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 tool's function with a specific verb and resource: 'Emit the provenance manifest that makes the run reproducible.' This distinguishes it from sibling tools like build_job_request or validate_job, which have different purposes.

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?

The description provides implicit usage context by stating that the job must be a fully built request and that the uuid must belong to a submitted job. This tells the agent when the tool is appropriate, though it does not explicitly name alternative tools or exclusions.

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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