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CLAUDE.md · alinaqi/maggy

CLAUDE.md from alinaqi/maggy: 226 lines covering General Preferences, Code Style, Git Workflow, Tools & Frameworks and more.

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About

The CLAUDE.md file that alinaqi/maggy (711 stars) keeps for coding agents. It has 226 lines in 11 sections: General Preferences; Code Style; Git Workflow; Tools & Frameworks; TDD — Non-Negotiable; Model Routing — Token Economy (13-Tier); Autonomous Plan → Validate → Execute; PR Workflow — Required Steps; Routing heuristic:; Tool Fallback Protocol; Followed Model & Pre-Analysis (hook signals). Use it as a model for your own project's instructions.

Use cases: prompt-engineering, testing

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What's in it

A CLAUDE.md file: project memory Claude Code loads at the start of every session.

For
Claude Code
Length
226 lines
File
CLAUDE.md

Sections

  1. General Preferences
  2. Code Style
  3. Git Workflow
  4. Tools & Frameworks
  5. TDD — Non-Negotiable
  6. Model Routing — Token Economy (13-Tier)
  7. Autonomous Plan → Validate → Execute
  8. PR Workflow — Required Steps
  9. Routing heuristic:
  10. Tool Fallback Protocol
  11. Followed Model & Pre-Analysis (hook signals)

First lines (shown under the repo's MIT license)

# Global Claude Code Settings

## General Preferences

- Concise responses preferred
- Use TypeScript over JavaScript when possible
- Prefer functional programming patterns
- Write tests for new functionality

## Code Style

- 2 spaces for indentation (JS/TS)
- 4 spaces for Python
- Single quotes for strings (JS/TS)
- No trailing commas
- Meaningful variable names

## Git Workflow

- Write clear, concise commit messages
- One logical change per commit
- Run tests before committing
- **Update `CHANGELOG.md` in the same commit** — every behaviour/config/docs/deps
  change ships a changelog entry (see `rules/changelog.md`). No commit without one.

## Tools & Frameworks

- Package manager: npm (Node.js), pip (Python)
- Testing: Jest/Vitest (JS), pytest (Python)
- Linting: ESLint (JS), ruff/black (Python)

---

# Engineering Policy

## TDD — Non-Negotiable

ALWAYS write tests before implementation. No exceptions.

1. Read the requirement
2. Write failing tests that describe the expected behaviour
3. Run tests — confirm they fail for the right reason
4. Write the minimum implementation to pass
5. Refactor, keep tests green
6. Never write a function, class, or API endpoint without a corresponding test

If asked to add a feature without tests, write the tests first then ask to proceed.
If a PR diff shows untested code paths, flag them before continuing.

## Model Routing — Token Economy (13-Tier)

| Tier | Model | Cost (in/out per M) | Role |
|------|-------|---------------------|------|
| 1 | Gemini 2.5 Flash-Lite | $0.10 / $0.40 | Bulk extraction, classification, CIG pipelines |
| 2 | DeepSeek V4 Flash | $0.14 / $0.28 | Sub-agents, cheap internal calls |
| 3 | Gemini 2.5 Flash | $0.15 / $0.60 | Multimodal, video analysis, brand assets |
| 4 | DeepSeek V4 Pro | $0.435 / $0.87 | Main coding workhorse — ~80% of work |
| 5 | Gemini CLI (coding agent) | ~$0.25-1.25 / M | Agentic coding, multi-file impl, Google tier |
| 6 | AGY / Antigravity (Google) | Google tier | Terminal coding agent, end-to-end impl |
| 7 | Kimi K2.6 | $0.60 / $2.50 | Long agentic loops, routing alt |
| 8 | Gemini 3.1 Pro + Search | $1.25 / $10 | Deep research, Google grounding, 2M context |
| 9 | Grok 4.3 (xAI) | $5 / $15 | Competitor intel, CKG, deep reasoning |
| 10 | Codex | varies | Code review, bulk generation |
| 11 | Claude Sonnet/Opus | $3-5 / $15-25 | Quality-critical, security, architecture |

### Use Gemini Flash-Lite (Tier 1) for:
- Bulk extraction and classification pipelines
- Cheap summarization, CIG data processing
- Non-code batch tasks (cheapest model at $0.10/M)

Invoke: gemini --flash-lite ""

### Use DeepSeek Flash (Tier 2) for:
- Simple code tasks, boilerplate, CRUD, config changes
- Single-file additions, small bug fixes

Invoke: deepseek --flash ""

### Use DeepSeek Pro (Tier 4) for:
- Multi-file features and refactors
- Debugging, API endpoints, test suites
- Documentation writing — main coding workhorse

Invoke: deepseek --pro ""

### Use Gemini Flash (Tier 5) for:
- Multimodal tasks (image screenshots, brand assets)
- Video content processing and analysis
- Audio transcription review

Invoke: gemini --flash ""

### Use Gemini CLI (Tier 5) for:
- Agentic coding tasks with file read/write
- Multi-file implementation within Google ecosystem
- Alternative coding agent for medium-complexity work

Invoke: gemini-cli --pro ""

### Use AGY / Antigravity (Tier 6) for:
- End-to-end implementation (git operations, file edits, testing)
- Terminal coding agent tasks (Google's coding agent)
- Multi-step implementation with autonomous execution

Invoke: agy-delegate --print ""
Invoke (headless): agy-delegate --headless ""

### Use kimi (Tier 7) for:
- Commit messages, changelogs, diff summaries
- Research questions needing reasoning
- Quick single-model analysis

Invoke: kimi ""

### Multi-Model Review
For architecture/code reviews, run DeepSeek + Kimi + Codex in parallel instead of single-model:
```bash
~/bin/review --all "review this implementation"
~/bin/review --deepseek --kimi "architecture review of auth module"
```
- Agree/disagree analysis across all three reviewers
- Estimated cost: ~$0.02 per review (vs $3-5 for Claude solo)
- Review log: `~/.claude/review-log.jsonl`

### Use Gemini Pro Search (Tier 7) for:
- Deep research with native Google Search grounding
- Competitor intelligence and market research
- 2M context document analysis

Invoke: gemini --pro-search ""

### Use Grok (Tier 9) for:
- Competitor intelligence and CKG building
- Deep reasoning and market analysis
- Truthful, insightful research

Invoke: grok ""

### Use Codex (Tier 10) for:
- Large-scale boilerplate or test generation
- Mechanical changes across many files
- Code review (codex-review)

### Use Claude (Tier 11) for:
- Architecture and system design
- Security-critical code
- Complex debugging, multi-service refactors
- Customer-facing quality-critical code

## Autonomous Plan → Validate → Execute

When a task requires planning (CLAUDE tier), the full cycle is automated:

```
Goal detected → Enter plan mode → Write plan to ~/.claude/plans/
    ↓
~/bin/validate-plan --threshold 2 <plan-file>
    ↓ (DeepSeek Pro + Codex + Gemini Pro vote in parallel)
2+ APPROVED → Auto-approve → Execute immediately
1 APPROVED → Surface to user with reviewer feedback

Signals

Stars
711
Forks
61
Open issues
0
Last commit (this folder)
Oct 13, 2026 (15 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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CLAUDE.md · alinaqi/maggy. Agent Mart. https://agentmart.dev/templates/alinaqi-maggy-claude-md (last updated 2026-10-24)