Borrowing it
Nothing to install: this file belongs to porcupine-md/jonggrang. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/porcupine-md/jonggrang/main/CLAUDE.mdgit clone --depth 1 https://github.com/porcupine-md/jonggrangWrote 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/instructions/porcupine-md/jonggrang/claude-md)<a href="https://agentmods.dev/instructions/porcupine-md/jonggrang/claude-md"><img src="https://agentmods.dev/badge/instructions/porcupine-md/jonggrang/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/porcupine-md/jonggrang/claude-md"><img src="https://agentmods.dev/badge/instructions/porcupine-md/jonggrang/claude-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.02108 | $0.02108 |
| Opus 5 | $0.01054 | $0.01054 |
| Sonnet 5 | $0.00422 | $0.00422 |
| Haiku 4.5 | $0.00211 | $0.00211 |
Grade A, and why
jonggrang CLAUDE.md 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 9d 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md — Project Guide for AI Agents
Guide for any AI agent (Claude Code, Codex, OpenCode, Jonggrang) working in this repo.
AGENTS.mdis a symlink to this file — both point to the same source.
What Jonggrang Is
Jonggrang is a CLI orchestrator for AI development workflows. It runs the pipeline Plan → Implement → Simplify → Test → Review with one atomic task per fresh-context agent, enforced by hooks (secrets blocker, context overload guard, quality gate). The goal is not to make agents faster — they are already fast enough — but to force them to stop and clean up before complexity quietly accumulates.
Two primary modes:
- Work Loop — iterative, stateless, one agent per task. Good for small-to-medium features.
- Orchestrate Mode — deterministic 16-phase, 5 specialist agents, persistent state via
MANIFEST.yaml. For serious delivery.
Agent backends: opencode, claude, codex, jonggrang (Pi SDK in-process). Selected via .jonggrang/jonggrang.json.
Entry points: bin/jonggrang (CLI), client/ (Pi TUI), server.js (web dashboard). Hooks live in hooks/, skills in skills/, templates in templates/.
→ Full detail: docs/JONGGRANG.md · docs/PHILOSOPHY.md · docs/WORKFLOW.md
Read These When You Need Context
Two docs are the canonical source of truth for the project's intent. Read them before any non-trivial change — do not infer architecture from code alone:
docs/PHILOSOPHY.md— Why Jonggrang exists, the pipeline as a quality gate, the five-layer stack, hook layers, autonomy modes, project file structure. Read this when:- You are touching the pipeline (
Plan → Implement → Simplify → Test → Review), any hook inhooks/, the compaction gate, or the feedback loop. - You are unsure why a constraint exists (e.g., why coordinators cannot edit files, why exit is blocked until tests pass).
- You are tempted to "simplify" something that looks redundant — it is probably load-bearing.
- You are touching the pipeline (
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.
- 9d ago First seen · 109 lines · 2,108 tokens per session scan A 9f5c84dadab7
jonggrang CLAUDE.md is an instructions file published in the GitHub repository porcupine-md/jonggrang (11 stars, last pushed 12d ago), licensed MIT. It adds 2,108 tokens to every session, about $0.0105 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 2026-08-30.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.