register-generated-program

A rule for registering a finished runnable project in LLMPET Launcher after checking that it actually starts.

In plain words
What is it for?
Use it for websites, apps, demos, servers, command-line tools, and other executable projects that have passed a real launch check.
Why use it?
It prevents incomplete or untested projects from appearing as launchable shortcuts.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/myunwang/llmpet/register-generated-program
Any agent
npx skills add myunwang/LLMPET --skill register-generated-program
Clone the repo
git clone --depth 1 https://github.com/myunwang/LLMPET

Made for: Claude Code, Codex.

Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 495 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00071 $0.00495
Opus 5 $0.00036 $0.00247
Sonnet 5 $0.00014 $0.00099
Haiku 4.5 $0.00007 $0.00049

Measured 3d ago against content hash b7847117e10e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

register-generated-program 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 3d 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.

.agents/skills/register-generated-program/SKILL.md · 49 lines

What it actually says

Register Codex Program

Add a Codex-created shortcut to LLMPET Launcher only after proving the deliverable really runs.

Workflow

  1. Identify the user-facing launch path. Prefer the same command or file the user should run later.
  2. Launch it in the real target environment. Compilation, lint, or unit tests alone do not count.
  3. Confirm an observable successful startup. If that remains unverified, do not register anything.
  4. Use exactly one of the following forms. Keep --provider codex; this skill must never attribute a program to Claude Code.

For a command:

node "$HOME/.octopus/bin/register-generated-program.js" --verified \
  --name "Program name" \
  --description "What the shortcut opens" \
  --cwd "/absolute/project/path" \
  --command "npm" --arg "run" --arg "dev" \
  --provider codex

For an app bundle or directly openable file:

node "$HOME/.octopus/bin/register-generated-program.js" --verified \
  --name "Program name" \
  --cwd "/absolute/project/path" \
  --open "/absolute/project/path/Program.app" \
  --provider codex
  1. Add --icon /absolute/path only when a suitable local icon already exists.
  2. Report registration only after the command prints JSON with "ok": true.

Boundaries

  • Use absolute paths.
  • If the registrar is missing, ask the user to open LLMPET Workbench → Generated Programs and authorize the Codex skill. Do not recreate LLMPET's registry format manually.
  • Pass arguments as repeated --arg values. Do not embed shell pipelines in --command.
  • Register the canonical project once; the same path and launch command update the existing shortcut.
  • Never pass --verified before a real launch succeeds.
  • Registration changes only LLMPET's local shortcut index. It does not copy, deploy, publish, or delete the project.
Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 3d ago First seen · 49 lines · 71 tokens per session scan A b7847117e10e

Subscribe to this mod's changes

register-generated-program is a skill published in the GitHub repository myunwang/LLMPET (112 stars, last pushed 3d ago), licensed MIT. It adds 71 tokens to every session and 495 once invoked, about $0.0004 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.