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Dropspace

by io.github.JCLVSH
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reject_autopilot_draft

Destructive

reject an autopilot draft - deletes it and refunds the launch slot. optional feedback teaches future runs what to avoid.

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": {
      "launch_id": "<launch_id>"
    },
    "name": "reject_autopilot_draft"
  }
}

Input Schema

NameRequiredDescriptionDefault
feedbackNowhy this doesn't work (feeds future generation)
launch_idYesthe draft launch id from list_autopilot_review

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior5/5

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

The annotations already mark the operation as destructive, and the description adds important context beyond that: it deletes the draft, refunds the launch slot, and optional feedback affects future generation. This gives the agent a clear picture of the side effects 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.

Conciseness5/5

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

The description is two compact sentences with the destructive consequence and refund front-loaded, followed by the optional feedback effect. Every sentence earns its place.

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?

For a simple two-parameter destructive mutation with complete schema and destructive annotations, the description covers the key behavior: deletion, slot refund, and feedback impact. It omits confirmation or result details, but the tool's low complexity and lack of an output schema make this a minor gap.

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?

Schema description coverage is 100%, so both parameters are already documented. The description reinforces that feedback is optional and teaches future runs what to avoid, but it does not add meaningful syntax or usage detail beyond the schema.

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 states a specific verb and resource: reject an autopilot draft, and explains the consequences of deleting it and refunding the launch slot. It does not explicitly contrast with approve_autopilot_draft, though the reject/approve distinction is inherent.

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

Usage Guidelines3/5

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

Usage is implied: call this when an autopilot draft should be rejected rather than approved. The description does not explicitly name alternatives, exclusions, or prerequisites, leaving the agent to infer the decision context.

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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