@geekbb: Code Shit Mountain Analysis Skills generates rigorous, professional code review reports. The name may be crude, but every report is calm, structured, evidence-driven, and actionable. https://github.com/XiNian-dada/Fuck_My_Shit_Mountain…
Summary
Code Shit Mountain Analysis Skills is an AI skill/prompt framework for generating rigorous, professional code review reports, supporting multiple audit modes and HTML output.
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XiNian-dada/Fuck_My_Shit_Mountain
Source: https://github.com/XiNian-dada/Fuck_My_Shit_Mountain
Fuck My Shit Mountain 🏔️💩
Disclaimer: AI review results are for entertainment and reference only, and do not represent the actual quality, security, compliance, or release readiness of the project. Any conclusions should be validated through manual review, test results, and real runtime environments.
Evidence-based AI code audit skill. Professional output. Zero emotional bullshit.
Fuck My Shit Mountain is an AI skill (prompt framework) for generating rigorous, professional code review reports. The name is crude, but every report is calm, structured, evidence-driven, and actionable.
Workflow
- AI first confirms necessary inputs — only asks for missing mode, report language, output format after a lightweight project portrait, recommending options like “full audit / security-focused / frontend experience / release & ops” in your language; if you’ve already specified, it proceeds directly.
- AI systematically audits your codebase — covers first-party source code, tests, configs, dependencies, and release files, honestly recording exclusions.
- AI generates a structured report — scores, findings, principle compliance, fix priority, quick wins.
- HTML output — sidebar navigation + scroll tracking, colored score bars, findings table per dimension + verified checklist, design principle compliance table, fix priority table.
Demo Preview
If you want to show someone a “real-looking” review page, check out this static demo:
docs/index.htmlis the GitHub Pages entry page- The top of the page clearly marks it as
Demo / Fictional / Not a real audit - If the repo’s Pages source is set to
main /docs, it auto-deploys on push;.nojekyllis already placed indocs/
Modes
Regular users can directly choose natural language options like “Full Audit”, “Security & Privacy”, “Frontend Experience”, “Release & Ops”, and the AI maps them to internal modes. Advanced users can specify single or combined modes (e.g., security, stability, type-safety). Full mode covers 25 audit dimensions.
| Mode | Focus |
|---|---|
full | All 25 dimensions |
architecture | Architecture boundaries, dependency direction, state ownership |
security | Authentication, injection, secrets, dependencies |
stability | Panic paths, error handling, concurrency, lifecycle |
performance | Hot paths, memory, I/O, startup overhead |
testing | Test coverage, test types, flakiness |
maintainability | Complexity, coupling, duplication, naming |
design | Engineering principles and design risks |
release | CI/CD, version management, upgrade, rollback |
documentation | Doc accuracy, setup, ops/dev guides |
observability | Logging, metrics, tracing, health checks, alerting |
configuration | Config validation, defaults, environment isolation, feature flags |
data-integrity | Transactions, idempotency, migrations, consistency, backup/restore |
privacy | PII, data minimization, retention, deletion, export |
accessibility | Keyboard, focus, semantics, responsive & UX states |
supply-chain | Dependency provenance, reproducible builds, CI integrity, signing |
cost | Resource economy, budget, external API & LLM costs |
ai-safety | Prompt injection, tool authorization, RAG leakage, eval |
fallback | Silent degradation, empty catches, defensive guessing |
testing-authenticity | Over-mocking, implementation detail tests, false confidence |
type-safety | Unsafe blocks, type assertions, boundary types |
frontend-state | Component size, state duplication, side effects, coupling |
backend-api | API consistency, validation, N+1, data flow |
dependency-weight | Heavy dependencies, build toolchain |
code-consistency | Naming, imports, patterns, style uniformity |
comment-coverage | Doc quality, stale comments, missing docs |
Project Structure
fuck-my-shit-mountain/
├── SKILL.md — Entry point & rules
├── agents/ — UI metadata
├── prompts/ — 26 audit mode prompts
├── references/ — Common report format, HTML, coverage, lint, tool references
├── rubrics/ — Severity, confidence, evidence, principles, scoring
├── scripts/ — Project portrait, report lint, skill packaging tools
├── templates/ — audit-report.md, audit-report.html, issue-card.md, remediation-plan.md
└── examples/ — Rust, Node.js, Vue audit examples
It is recommended to generate a clean skill package before distribution or installation, or use the same exclusion rules to sync to the local skill directory, avoiding inclusion of non-essential files like README, .DS_Store, cache files, etc.
python3 fuck-my-shit-mountain/scripts/package_skill.py --dry-run
python3 fuck-my-shit-mountain/scripts/package_skill.py
The generated dist/fuck-my-shit-mountain.zip excludes README, .DS_Store, cache files, and other non-essential items.
To update an installed skill in Codex locally, run from the repo root:
rsync -av --delete --delete-excluded \
--exclude='README.md' \
--exclude='.DS_Store' \
--exclude='__pycache__/' \
--exclude='*.pyc' \
--exclude='*.pyo' \
--exclude='dist/' \
fuck-my-shit-mountain/ ~/.codex/skills/fuck-my-shit-mountain/
Example Score Panel
Security ████████░░ 8.0 A
Stability ██████░░░░ 6.0 B
Performance ██████████ 10.0 S
Testing ████░░░░░░ 4.0 C
Maintainability ███████░░░ 7.0 A
Design █████░░░░░ 5.0 B
Release ██████░░░░ 6.0 B
─────────────────────────────────────
Overall ██████░░░░ 6.6 B
Higher is better (10 = clean, 0 = shit mountain). Scores are based on judgment, not formulas.
See fuck-my-shit-mountain/rubrics/scoring.md.
Natively Supported Platforms
This repository provides a standard SKILL.md + prompts + rubrics + templates skill directory, natively usable with the following tools:
Codex
- Recommended: use the
rsynccommand above to sync to~/.codex/skills/fuck-my-shit-mountain/, or extractdist/fuck-my-shit-mountain.zipinto~/.codex/skills/ - Restart Codex or start a new conversation to reload skill metadata
- Request to use this skill in a Codex conversation
Claude Code
- Personal install: copy to
~/.claude/skills/fuck-my-shit-mountain/ - Project install: copy to
.claude/skills/fuck-my-shit-mountain/ - After starting
claude, invoke via prompt or/fuck-my-shit-mountain
GitHub Copilot (CLI / VS Code Agent / Cloud Agent)
- Personal install: copy to
~/.copilot/skills/fuck-my-shit-mountain/, or~/.agents/skills/fuck-my-shit-mountain/ - Project install: copy to
.github/skills/fuck-my-shit-mountain/,.claude/skills/fuck-my-shit-mountain/, or.agents/skills/fuck-my-shit-mountain/ - Run
/skills reloadin Copilot CLI - Confirm with
/skills info fuck-my-shit-mountain
Gemini CLI
- Personal install: copy to
~/.gemini/skills/fuck-my-shit-mountain/, or~/.agents/skills/fuck-my-shit-mountain/ - Project install: copy to
.gemini/skills/fuck-my-shit-mountain/, or.agents/skills/fuck-my-shit-mountain/ - Run
/skills reloadin Gemini CLI - Confirm with
/skills listthat the skill is discovered - If using project directory installation, ensure the workspace is trusted first.
When you update the skill content in this repo, prefer using package_skill.py or the rsync exclusion rules above to re-sync to the respective tool’s skills directory, then reload via each tool’s refresh method.
Example prompt:
Please use the fuck-my-shit-mountain skill to audit the current project
Mode: full
Report language: English
Output format: html
License
MIT
Learn AI on LinuxDo (https://linux.do/)
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