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lightbulb-mcp

lightbulb-mcp

by RPasquale
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

prepare_workflow_learning_handoff

Prepare a fail-closed candidate handoff after staging by verifying packet, delivery, audit trail, and action readiness. Produces a manifest to enable learning from verified workflow data without modifying artifacts.

Instructions

Prepare a fail-closed Puffer/Prime candidate handoff after staging.

This reads the exact packet, delivery, immutable audit trail, and installed action readiness. Omit episode_manifest to derive an exact content-free v2 manifest from verified input custody; supplying a v1 manifest avoids that extra custody read. The tool cannot admit, fund, launch, evaluate, promote, serve, or write artifacts.

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": {
      "packet_id": "<packet_id>",
      "delivery_id": "<delivery_id>",
      "installation_id": "<installation_id>",
      "revision_id": "<revision_id>",
      "candidate_manifest": "<candidate_manifest>"
    },
    "name": "prepare_workflow_learning_handoff"
  }
}

Input Schema

NameRequiredDescriptionDefault
packet_idYes
project_idNo
delivery_idYes
revision_idYes
installation_idYes
episode_manifestNo
candidate_manifestYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.1

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral disclosure burden, and it handles this well by explicitly stating that it 'reads' data and 'cannot... write artifacts.' The 'fail-closed' qualifier and the conditional custody-read behavior around episode_manifest add useful behavioral context. It does not cover auth or error conditions, but the main side-effect and safety profile is clear.

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 four dense sentences that front-load the purpose, then provide input semantics, then the optional-manifest behavior, then the explicit boundary. Every sentence contributes non-redundant information, and the list of unsupported actions is compact rather than rambling.

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?

Because an output schema exists, the description does not need to explain return values. It supplies the operational phase, the inputs read, the optional episode_manifest decision, and the tool's non-goals, which is a solid envelope for a prep-only handoff tool. The main remaining gaps are the lack of named successor tools and exact semantics of the manifest-related parameters.

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 0%, so the description must compensate, and it partially does: it explains episode_manifest's omit-vs-supply trade-off and maps packet, delivery, audit trail, and installed-action readiness to the main ID inputs. However, candidate_manifest and project_id are left mostly to inference from their names, and no format or validation guidance is given.

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 opening sentence names a specific action ('prepare'), a specific resource ('Puffer/Prime candidate handoff'), and a phase condition ('after staging'), so it goes well beyond the tool name. The follow-up 'reads the exact packet, delivery, immutable audit trail, and installed action readiness' further clarifies the tool's core job. This distinguishes it from downstream workflow-action tools.

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 gives a clear usage context ('after staging') and explains an input-mode decision ('Omit episode_manifest...; supplying a v1 manifest avoids that extra custody read'). The explicit non-goals list ('cannot admit, fund, launch, evaluate, promote, serve, or write artifacts') helps an agent avoid misusing it. It does not name a specific alternative sibling tool, so it stops short of a 5.

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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