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bicameral_finish

Finalize a run with verification, outcome logging, lesson storage, and scoring. Get a summary report to close out your AI coding workflow.

Instructions

Close the run: final verification, outcome logging, lesson storage and scoring. Returns the summary to report.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
run_idYes
lessonsNo
successYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of disclosing behavior. It does so by enumerating side effects: final verification, outcome logging, lesson storage, and scoring, plus returning a summary. It could add detail about irreversibility or state changes, but the terminal nature is clearly conveyed.

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 a single front-loaded sentence with no filler. Every phrase adds meaning: the action, the component steps, and the return value. It is an efficient, well-structured definition.

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 captures the core operations and return value, which is reasonable given an output schema exists. However, without annotations and with weak parameter semantics, it leaves uncertainty about how to supply success and lessons and what happens to the run after closing. It is adequate but not fully complete.

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?

Schema description coverage is 0%, so the description must compensate, but it does not explain how run_id, success, or lessons map to their expected values. 'Lesson storage' and 'outcome logging' loosely hint at lessons and success, but the agent gets little concrete guidance on the parameters.

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 starts with 'Close the run,' which names a specific verb and resource, and then lists the concrete operations involved: final verification, outcome logging, lesson storage, and scoring. It clearly distinguishes this terminal tool from lifecycle siblings like bicameral_begin, bicameral_execute, and bicameral_status.

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 opening phrase 'Close the run' establishes a clear terminal context: use this when the run is complete and needs final verification, logging, lesson storage, and scoring. It gives clear usage context but does not explicitly name alternatives or state when not to use it.

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