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 instructions/lukas-grigis/ralphctl/claude-mdgit clone --depth 1 https://github.com/lukas-grigis/ralphctlWrote 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/lukas-grigis/ralphctl/claude-md)<a href="https://agentmods.dev/instructions/lukas-grigis/ralphctl/claude-md"><img src="https://agentmods.dev/badge/instructions/lukas-grigis/ralphctl/claude-md.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 | $0.02395 | $0.02395 |
| Opus 5 | $0.01197 | $0.01197 |
| Sonnet 5 | $0.00479 | $0.00479 |
| Haiku 4.5 | $0.00239 | $0.00239 |
Grade A, and why
ralphctl CLAUDE.md scanned grade A with 1 finding 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 5d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
`typescript-result` / `fs.writeFile` / `node:child_process.spawn` / `@inquirer/prompts` imports — are How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RalphCTL — Agent Harness for AI Coding Tasks
Node.js 24 + TypeScript + Ink TUI. Five AI provider backends (Claude Code / GitHub Copilot / OpenAI Codex /
OpenCode / Grok). Grok is xai-grok, binary grok. OpenCode is an aggregator — its model ids are
provider/model and its catalog is discovered at runtime via opencode models, so it is the one backend
whose reachable models are not a static list.
The TUI is the primary surface; the CLI exposes inspection + one-shot operations only.
Version is read from package.json via JSON import attribute in src/business/version/cli-metadata.ts.
Both commander.version() and the npm-update poll consume the same constant — bin and registry cannot drift.
Build & Run
pnpm install
pnpm dev <command> # tsx, no build needed
pnpm dev # bare → Ink TUI (primary surface)
pnpm build # tsup + tsx scripts/build-assets.ts → dist/cli.mjs + dist/{prompts,skills,manifest.json}
pnpm typecheck # tsc --noEmit
pnpm lint # ESLint
pnpm test # vitest
pnpm coverage # vitest run --coverage (ad-hoc threshold check; not in verify)
pnpm verify:coverage # alias for pnpm coverage
pnpm format:check # prettier
pnpm deadcode # knip (clean tree exits 0)
pnpm skills:update # re-vendor upstream SKILL.md into scripts/vendor/skills/ for review (maintainers only)
Before every commit, run /verify (wraps pnpm typecheck && pnpm lint && pnpm test). All three must pass.
Pre-commit hook runs lint-staged (ESLint + Prettier on staged files); pnpm lint:fix / pnpm format patch.
Requirements: Node.js 24+ (managed via mise.toml), pnpm 10+, one of the supported AI CLIs in PATH and
authenticated.
Read on demand
Not auto-imported — open with the Read tool when the work touches the area.
.claude/docs/ARCHITECTURE.md— module layout, ports, repository interfaces, data models, error tables.claude/docs/KERNEL-DESIGN.md— chain framework reference (element/leaf/sequential/loop/guard).claude/docs/WORKFLOWS.md— sprint lifecycle + state table, two-phase planning, gen-eval loop, TUI navigation, setup/verify, branch management.claude/docs/AI-SETTINGS.md—settings.aishape, effort resolution, presets, fail-fast PATH check.claude/docs/SECURITY.md— permission model, cross-process lock, spawning, AbortError rule, skills, refine write-back, file-based provider contract.claude/docs/PERFORMANCE.md— scheduler / parallel waves, rate-limit retry, iteration budget, plateau escalation, progress journal, learning ledger, env vars, release procedure.claude/docs/REQUIREMENTS.md— acceptance-criteria checklist.claude/docs/DESIGN-SYSTEM.md— TUI tokens, components, copy rules.claude/docs/MANUAL-TEST-PLAYBOOK.md— manual smoke-test script.claude/docs/HARNESS-PRINCIPLES.md— distilled harness research (Anthropic + martinfowler.com); consult before structural changes to the chain framework, flow registry, or provider engine.claude/docs/RESEARCH-REFERENCES.md— verified source table (papers/articles → claims → where used), adopted techniques, and rejected ideas with reasons; consult before adding a citation or re-proposing a technique.claude/docs/diagrams/— Mermaid sequence / data-flow diagrams: chain framework, flow lifecycle, sprint lifecycle, task lifecycle, AI-session data flow
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.
- 5d ago First seen · 130 lines · 2,395 tokens per session scan A c670fa430af6
ralphctl CLAUDE.md is an instructions file published in the GitHub repository lukas-grigis/ralphctl (23 stars, last pushed yesterday), licensed MIT. It adds 2,395 tokens to every session, about $0.0120 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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