Outer Review

Process an external AI review to extract actionable tasks. The human commissions the external review and saves the raw output; this skill processes it.

When to Use

•When /outer-review [filepath] is invoked with a new outer review file
•After a human has commissioned and saved an external AI analysis

Why External Review Matters

The Unfinishable Map's content is primarily generated and reviewed by Claude-based systems. This creates risk of:

•Confirmation bias: The reviewing system shares assumptions with the generating system
•Blind spot persistence: Gaps in Claude's knowledge propagate undetected
•Style homogenization: Content converges toward patterns Claude favors
•Coherence inflation: Arguments seem stronger than they are because the reviewer finds them compelling for the same reasons the writer did

External AI systems (GPT-4+, Gemini, etc.) have different training, different biases, and different blind spots. Their disagreements are informative even when wrong.

Prerequisites

The human must:

•Commission a review from an external AI system (ChatGPT, Gemini, etc.)
•Save the raw output to obsidian/reviews/outer-review-YYYY-MM-DD-[system-slug].md
•Add basic frontmatter (or leave for this skill to add)

Instructions

1. Read the Review File

The filepath is provided as an argument: /outer-review obsidian/reviews/outer-review-2026-01-15-site-chatgpt-5-2-pro.md

Read the file and assess its current state.

2. Add/Fix Frontmatter

Ensure the file has proper frontmatter:

yaml

---
title: "Outer Review - [System Name]"
created: YYYY-MM-DD
modified: YYYY-MM-DD
human_modified: null
ai_modified: YYYY-MM-DDTHH:MM:SS+00:00
draft: false
topics: []
concepts: []
related_articles:
  - "[[project]]"
ai_contribution: 90
author: [Human who commissioned it]
ai_system: [external-system-id]
ai_generated_date: YYYY-MM-DD
last_curated: null
---

**Date**: YYYY-MM-DD
**Reviewer**: [System name and version]
**Type**: Outer review (external AI analysis)

## About This Review

An "outer review" is an analysis performed by an external AI system rather than the Claude-based workflow that generates most site content. This provides an independent perspective, reducing the risk of self-reinforcing blind spots.

[External system's review content follows...]

3. Convert Links to Internal Format

The external system will likely use external URLs. Convert these to internal wikilinks:

•https://unfinishablemap.org/tenets/ → [[tenets]]
•https://unfinishablemap.org/topics/free-will/ → [[free-will]]
•https://unfinishablemap.org/concepts/qualia/ → [[qualia]]

This improves navigation and maintains link integrity.

4. Evaluate Review Quality

Read through the review and categorize findings:

High value findings:

•Logical gaps not previously noticed
•Counterarguments not addressed
•Inconsistencies between pages
•Missing connections that should exist
•Novel framings of existing positions

Lower value findings:

•Objections already addressed elsewhere
•Misunderstandings of the position
•Requests to adopt a different position entirely
•Style preferences that don't affect clarity

5. Generate Tasks

For high-value findings, create tasks in obsidian/workflow/todo.md:

markdown

### P1: [Specific issue from outer review]
- **Type**: [research-topic | expand-topic | refine-draft | cross-review]
- **Notes**: From outer review YYYY-MM-DD. [Brief description of the issue and why it matters]
- **Source**: outer-review
- **Generated**: YYYY-MM-DD

Priority guidance:

•P1: Logical errors, internal contradictions, unaddressed strong objections
•P2: Missing connections, expansion opportunities, clarity improvements
•P3: Style suggestions, minor enhancements

6. Log to Changelog

Append to obsidian/workflow/changelog.md:

markdown

### HH:MM - outer-review
- **Status**: Success
- **Reviewer**: [System name]
- **File**: [filepath]
- **High-value findings**: [count]
- **Tasks generated**: [count with priorities]

7. Commit

Create a git commit:

code

feat(auto): outer-review - process [system name] analysis

- Identified [N] actionable issues
- Generated [N] tasks (P1: X, P2: Y, P3: Z)

Evaluating Impact (After Tasks Complete)

After tasks from an outer review have been completed, evaluate the review's value:

•Count completed tasks: How many issues were addressed?
•Assess depth: Did the review surface deep insights or obvious issues?
•Track new content: What articles/sections resulted from the review?
•Note patterns: What kinds of issues does this external system catch that internal review misses?

This helps calibrate future review frequency and system selection.

Important

•This skill requires manual invocation with a filepath argument
•The human commissions and saves the external review; this skill processes it
•External systems may have different biases—their criticism isn't automatically correct
•The goal is diverse perspective, not consensus
•Some external criticism will be based on misunderstanding—that's expected
•Focus on actionable findings that improve content quality