Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/henryalouf/ruflow/analyze-projectnpx skills add henryalouf/ruflow --skill analyze-projectgit clone --depth 1 https://github.com/henryalouf/ruflowWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/henryalouf/ruflow/analyze-project)<a href="https://agentmods.dev/skills/henryalouf/ruflow/analyze-project"><img src="https://agentmods.dev/badge/skills/henryalouf/ruflow/analyze-project.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00038 | $0.02967 |
| Opus 5 | $0.00019 | $0.01484 |
| Sonnet 5 | $0.00008 | $0.00593 |
| Haiku 4.5 | $0.00004 | $0.00297 |
Grade A, and why
analyze-project scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 441 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/analyze-project — Root Cause Analyst Workflow
Analyze AI-assisted coding sessions in ~/.gemini/claude-code/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:
- What changed from the initial ask to the final executed work
- Whether the main cause was:
- user/spec
- agent
- repo/codebase
- validation/testing
- legitimate task complexity
- Whether the opening prompt was sufficient
- Which files/subsystems repeatedly correlate with struggle
- 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.Ncounts 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:
DELIVERYDEBUGGINGREFACTORRESEARCHEXPLORATIONAUDIT_ANALYSIS
Record:
session_intentsession_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.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 441 lines · 38 tokens per session scan A 00d8e345c666
analyze-project is a skill published in the GitHub repository henryalouf/ruflow (122 stars, last pushed 3mo ago), licensed MIT. It adds 38 tokens to every session and 2,967 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
analyze-project
Forensic root cause analyzer for Antigravity sessions. Classifies scope deltas, rework patterns, root causes, hotspots, and auto-improves prompts/health.
analyze-project
Forensic root cause analyzer for Antigravity sessions. Classifies scope deltas, rework patterns, root causes, hotspots, and auto-improves prompts/health.
analyze-project
Forensic root cause analyzer for Antigravity sessions. Classifies scope deltas, rework patterns, root causes, hotspots, and auto-improves prompts/health.
analyze-project
Forensic root cause analyzer for Antigravity sessions. Classifies scope deltas, rework patterns, root causes, hotspots, and auto-improves prompts/health.
analyze-project
Forensic root cause analyzer for Antigravity sessions. Classifies scope deltas, rework patterns, root causes, hotspots, and auto-improves prompts/health.
analyze-project
Forensic root cause analyzer for Antigravity sessions. Classifies scope deltas, rework patterns, root causes, hotspots, and auto-improves prompts/health.