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Review Plan

review_plan

Review a development or architecture plan using peer LLMs, get a structured verdict with prioritized findings, and log the session locally for repeatable checkpoints.

Instructions

Review a development/architecture plan with peer LLMs and return a consolidated verdict (approve | revise | reject) with prioritized findings. Runs configured reviewer CLIs and writes a local session log to ~/.inspectrum/sessions/.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
planYesThe plan to review, in Markdown. Max 16 000 characters.
focusNoReview focus area.all
judgeNoRun judge agent to consolidate when >= 2 reviewers.
contextNoOptional codebase excerpts for context. Max 8 000 characters.
reviewersNoReviewer IDs (from config). Defaults to config defaults.reviewers.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
verdictYes
findingsYes
session_idYes
revised_planNo
session_pathYes
report_markdownYes
Behavior4/5

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

Beyond annotations, the description discloses that it runs configured reviewer CLIs and writes a local session log, adding specific side-effect information that the annotations only hint at. This provides useful transparency about external behavior.

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 sentences, front-loaded with the core purpose in the first sentence and side effects in the second. No wasted words, making it highly concise and well-structured.

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?

The description covers the primary purpose, side effects, and output summary. The presence of an output schema handles return value specifics. Minor gaps remain (e.g., configuration details) but are not critical given the richness of the schema and annotations.

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?

All parameters are fully described in the JSON schema (100% coverage), so the description does not add parameter-specific meaning. The baseline of 3 applies because the schema carries the load.

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 reviews a development/architecture plan, using a specific verb and resource, and describes the output as a consolidated verdict with prioritized findings. It is unambiguous and distinguishes the tool's function even without siblings.

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 context for use is clear: you review a plan. However, there are no explicit when-not-to-use instructions or alternative tools mentioned, given there are no siblings. The description implies usage effectively but lacks explicit exclusion guidance.

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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