Atlas / Skills / florianbruniaux / Methodology Advisor

Methodology AdvisorCAUTION

skills/florianbruniaux/methodology-advisor

The most comprehensive Claude Code guide: agentic workflows, hooks, skills, MCP servers, quizzes, and production-ready templates. 430K+ lines.

Verdict
CAUTION
Grade
B
Trust score
89 /100
Version
—
Hosts
—
License
CC-BY-SA-4.0
Stars
6,123
01

Overview

The most comprehensive Claude Code guide: agentic workflows, hooks, skills, MCP servers, quizzes, and production-ready templates. 430K+ lines.

Read from source at commit d90170da4369OBSERVED · 2026-10-07
02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: methodology-advisor
description: Analyzes your codebase and asks 3 targeted questions to recommend the right AI-assisted development methodology stack
effort: medium
allowed-tools: Read Grep Glob
---

# Methodology advisor

Analyze this project and recommend the best AI-assisted development methodology stack. Read what you can from the codebase first, then ask only what you cannot infer.

**Time**: 2-4 minutes | **Output**: One recommended stack + contextual quick start

---

## Phase 1: Silent codebase analysis

Run these reads silently. Do not output results yet, build an internal picture only.

### 1.1 Project identity

```bash
# Config files
cat CLAUDE.md 2>/dev/null || cat claude.md 2>/dev/null
cat package.json 2>/dev/null | grep -E '"name"|"description"|"scripts"' | head -10
cat Cargo.toml 2>/dev/null | grep -E '^name|^description' | head -5
cat pyproject.toml 2>/dev/null | grep -E '^name|^description' | head -5
cat go.mod 2>/dev/null | head -3
```

### 1.2 Team size

```bash
# Unique contributors in last 90 days
git log --since="90 days ago" --format="%ae" 2>/dev/null | sort -u | wc -l
# Total commits
git log --oneline 2>/dev/null | wc -l
```

### 1.3 Test maturity

```bash
# Test files exist?
find . -name "*.test.*" -o -name "*.spec.*" -o -name "*_test.*" -o -name "test_*.py" \
  2>/dev/null | grep -v node_modules | grep -v ".git" | wc -l
# Test framework hints
grep -rn --include="*.json" --include="*.toml" --include="*.yaml" \
  -l "jest\|vitest\|pytest\|rspec\|mocha\|cypress\|playwright" \
  2>/dev/null | grep -v node_modules | head -5
# CI config
ls .github/workflows/*.yml 2>/dev/null | wc -l
ls .gitlab-ci.yml .circleci/config.yml 2>/dev/null | wc -l
```

### 1.4 Spec and documentation signals

```bash
# Spec files
find . -name "*.spec.md" -o -name "SPEC*.md" -o -name "spec.md" -o -name "DESIGN*.md" \
  -o -name "ADR*.md" -o -name "RFC*.md" \
  2>/dev/null | grep -v node_modules | grep -v ".git" | head -10
# OpenAPI / contract files
find . -name "openapi*.yaml" -o -name "openapi*.json" -o -name "swagger*.yaml" \
  -o -name "*.proto" \
  2>/dev/null | grep -v node_modules | head -5
# BDD feature files
find . -name "*.feature" 2>/dev/null | grep -v node_modules | wc -l
```

### 1.5 Codebase size and structure

```bash
# File count (rough)
find . -type f \( -name "*.ts" -o -name "*.tsx" -o -name "*.js" -o -name "*.py" \
  -o -name "*.rs" -o -name "*.go" -o -name "*.java" -o -name "*.rb" \) \
  2>/dev/null | grep -v node_modules | grep -v ".git" | wc -l
# Services / packages (monorepo signal)
ls packages/ apps/ services/ 2>/dev/null | head -10
```

### 1.6 AI and LLM signals

```bash
# LLM API usage in code
grep -rn --include="*.ts" --include="*.py" --include="*.js" \
  -l "anthropic\|openai\|groq\|mistral\|langchain\|llm\|ChatCompletion\|claude" \
  2>/dev/null | grep -v node_modules | grep -v ".git" | head -5
# Eval framework hints
find . -name "evals*" -o -name "*eval*" -type d 2>/dev/null | grep -v node_modules | head -5
```

---

## Phase 2: Score the 8 stacks

Using what you found, score each stack 0-10 based on fit signals:

| Stack | Key signals that boost the score |
|-------|----------------------------------|
| **solo-mvp** | 1 contributor, few files, no CI yet, greenfield |
| **team-greenfield** | 2-10 contributors, new project, no legacy files |
| **microservices** | `packages/`, `services/`, OpenAPI files, `.proto` |
| **brownfield-saas** | High commit count, large file count, few test files |
| **enterprise-gov** | 10+ contributors, CI, ADR files, `AGENTS.md` |
| **llm-native** | LLM imports, eval dirs, AI product signals |
| **power-solo** | 1 contributor, high commit rate, iterative commits |
| **plan-moderate** | Mixed signals, CLAUDE.md present, moderate size |

---

## Phase 3: Ask only what you cannot infer

After the silent analysis, present your preliminary picture to the user in 2-3 lines, then ask exactly 3 questions. No more.

Format:

```
From your codebase I can see: [2-3 concrete observations].
Before recommending, 3 quick questions:

1. [Pain point question, pick the most relevant from below]
2. [Deploy frequency, if not inferable from CI/CD signals]
3. [Setup appetite: how much ceremony are you willing to invest?]
```

**Question bank: pick the 3 most relevant given what you found:**

- Pain: "What slows you down most right now: regressions, unclear requirements, context rot between sessions, or no traceability?"
- Pain: "When Claude generates a large chunk of code, what is your biggest worry: quality, drift from spec, or losing track of what was built?"
- Deploy: "How often do you ship to production: multiple times a day, weekly, or on longer release cycles?"
- Deploy: "Is this a product with real users today, a prototype, or an internal tool?"
- Governance: "How much initial setup are you willing to invest: none (just start), 30 minutes, or half a day?"
- Governance: "Does anyone outside your dev team (PM, QA, compliance) need to validate what gets built?"
- AI product: "Does your product expose AI-generated outputs directly to end users?"
- Scale: "Do multiple services or teams need to agree on API contracts before implementing?"

---

## Phase 4: Recommendation

Output the recommendation in this structure:

---

### Your stack: [Stack name] [icon]

**Why this fits your project:**
- [Finding from Phase 1] -> [explains this stack choice]
- [Finding from Phase 1] -> [explains this stack choice]
- [Answer to question N] -> [explains this stack choice]

**Methodologies included:** `[Method A]` + `[Method B]` (+ `[Method C]` if applicable)

**What this looks like in practice:**
[2-3 sentences describing the concrete workflow for THIS project, using actual file names or paths found.]

**Quick start for your project:**
1. [Concrete first step using actual project context]
2. [Second step]
3. [Third step]

**Before you start, note:**
- [One honest trade-off or limitation of this stack]
- [One thing to watch out for given what you found]

**Go de
03

Trust audit

CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.

LayerWhat it checksResult
L0Provenance & inventoryWARN
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (2)

MEDIUMInventory / provenance · inv.symlink · CWE-1104
whitepapers/recap-cards/en/_extensions
whitepapers/recap-cards/en/_extensions
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
whitepapers/recap-cards/fr/_extensions
whitepapers/recap-cards/fr/_extensions
Why it matters. link not followed

Gates applied: no_behavioural_pass.

Audited 2026-10-07 · audit v0.4.1 · source sha d90170da4369full audit observations/trust-audit/skill/florianbruniaux__methodology-advisor.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-07d90170da4369CAUTIONB89first audit
05

Questions

What does the Methodology Advisor skill do?

The most comprehensive Claude Code guide: agentic workflows, hooks, skills, MCP servers, quizzes, and production-ready templates. 430K+ lines.

Is Methodology Advisor safe to install?

With care. The audit graded it B (89/100) and found 2 things worth knowing before you trust this skill, listed below with the exact line each was found on.

What can Methodology Advisor access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (d90170da4369), read on 2026-10-07. The repository is watched, and a new audit runs when it changes — this is the first audit.

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