analyze-project

The saved excerpt is a snapshot from when this skill was listed. The external source remains the complete and most current version.

---
name: analyze-project
description: Forensic root cause analyzer for Antigravity sessions. Classifies scope deltas, rework patterns, root causes, hotspots, and auto-improves prompts/health.
risk: critical
source: community
date_added: "2026-09-04"
version: "1.0"
tags: [analysis, diagnostics, meta, root-cause, project-health, session-review]
---

# /analyze-project — Root Cause Analyst Workflow

Analyze AI-assisted coding sessions in `~/.gemini/antigravity/brain/` and produce a report that explains not just **what happened**, but **why it happened**, **who/what caused it**, and **what should change next time**.

## Goal

For each session, determine:

1. What changed from the initial ask to the final executed work
2. Whether the main cause was:
   - user/spec
   - agent
   - repo/codebase
   - validation/testing
   - legitimate task complexity
3. Whether the opening prompt was sufficient
4. Which files/subsystems repeatedly correlate with struggle
5. What changes would most improve future sessions

## When to Use
- You need a postmortem on AI-assisted coding sessions, especially when scope drift or repeated rework occurred.
- You want root-cause analysis that separates user/spec issues from agent mistakes, repo friction, or validation gaps.
- You need evidence-backed recommendations for improving future prompts, repo health, or delivery workflows.

## Global Rules

- Treat `.resolved.N` counts as **iteration signals**, not proof of failure
- Separate **human-added scope**, **necessary discovered scope**, and **agent-introduced scope**
- Separate **agent error** from **repo friction**
- Every diagnosis must include **evidence** and **confidence**
- Confidence levels:
  - **High** = direct artifact/timestamp evidence
  - **Medium** = multiple supporting signals
  - **Low** = plausible inference, not directly proven
- Evidence precedence:
  - artifact contents > timestamps > metadata summaries > inference
- If evidence is weak, say so

---

## Step 0.5: Session Intent Classification

Classify the primary session intent from objective + artifacts:

- `DELIVERY`
- `DEBUGGING`
- `REFACTOR`
- `RESEARCH`
- `EXPLORATION`
- `AUDIT_ANALYSIS`

Record:
- `session_intent`
- `session_intent_confidence`

Use intent to contextualize severity and rework shape.
Do not judge exploratory or research sessions by the same standards as narrow delivery sessions.

---

## Step 1: Discover Conversations

1. Read available conversation summaries from system context
2. List conversation folders in the user’s Antigravity `brain/` directory
3. Build a conversation index with:
   - `conversation_id`
   - `title`
   - `objective`
   - `created`
   - `last_modified`
4. If the user supplied a keyword/path, filter to matching conversations; otherwise analyze all

Output: indexed list of conversations to analyze.

---

## Step 2: Extract Session Evidence

For each conversation, read if present:

### Core artifacts
- `task.md`
- `implementation_plan.md`
- `walkthrough.md`

### Metadata
- `*.metadata.json`

### Version snapshots
- `task.md.resolved.0 ... N`
- `implementation_plan.md.resolved.0 ... N`
- `walkthrough.md.resolved.0 ... N`

### Additional signals
- other `.md` artifacts
- timestamps across artifact updates
- file/folder/subsystem names mentioned in plans/walkthroughs
- validation/testing language
- explicit acceptance criteria, constraints, non-goals, and file targets

Record per conversation:

#### Lifecycle
- `has_task`
- `has_plan`
- `has_walkthrough`
- `is_completed`
- `is_abandoned_candidate` = task exists but no walkthrough

#### Revision / change volume
- `task_versions`
- `plan_versions`
- `walkthrough_versions`
- `extra_artifacts`

#### Scope
- `task_items_initial`
- `task_items_final`
- `task_completed_pct`
- `scope_delta_raw`
- `scope_creep_pct_raw`

#### Timing
- `created_at`
- `completed_at`
- `duration_minutes`

#### Content / quality
- `objective_text`
- `initial_plan_summary`
- `final_plan_summary`
- `initial_task_excerpt`
- `final_tas