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devtune_review_prompt_set_proposal

Destructive

Apply, undo, dismiss or restore one analyzer proposal after explicit human approval of that operation. Read the proposal first and show the human the proposed change. Never infer approval from a read or analysis request. Preserves quotas and stale/conflict checks. Requires actions.write and a user-attributed credential with devtune.manage. Interactive review remains in-app; Slack execution is unsupported.

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": {
      "proposalId": "<proposalId>",
      "operation": "<operation>",
      "humanApproved": "<humanApproved>"
    },
    "name": "devtune_review_prompt_set_proposal"
  }
}

Input Schema

NameRequiredDescriptionDefault
operationYes
proposalIdYes
humanApprovedYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / proposalId / pattern
      Added value: +"^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12})$"
  2. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already flag destructiveHint=true and idempotentHint=false, and the description adds information the annotations cannot carry: quota preservation, stale/conflict checking behavior, required scopes (actions.write plus a user-attributed credential with devtune.manage), and an environment restriction (no Slack execution). That is exactly the extra context an agent needs before invoking a destructive mutation.

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?

Front-loads the action and the approval gate, then layers constraints in short sentences with no filler. The 'Preserves quotas and stale/conflict checks' fragment is terse but load-bearing; overall structure is dense but readable.

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

Completeness5/5

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

For a three-parameter destructive mutation with no output schema, the definition covers the approval ritual, authorization requirements, conflict handling, and channel limits, which is everything an agent needs to invoke it safely. No return-value documentation is needed since no output schema exists.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must supply meaning, and it largely does: it enumerates the four operation values matching the enum, establishes that humanApproved must reflect real human consent rather than inferred intent, and implies proposalId identifies the single proposal read beforehand. It stops short of stating the UUID format or what the boolean exactly asserts (e.g., that false is rejected rather than meaning 'dismiss').

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?

States a specific verb set (apply/undo/dismiss/restore) against a specific resource (one analyzer proposal) with a gating condition (explicit human approval). The 'analyzer proposal' scoping also implicitly separates it from the sibling devtune_review_knowledge_proposal, so an agent can pick the right tool without opening a schema.

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

Usage Guidelines5/5

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

Gives an explicit prerequisite sequence ('Read the proposal first and show the human the proposed change') and an explicit prohibition ('Never infer approval from a read or analysis request'), which rules out the most likely misuse. It also bounds the channel of use by stating interactive review stays in-app and Slack execution is unsupported.

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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