Case 01901

Skill knownasnaffy/prompthound/dataset/case_01901

A fast, offline static risk analysis CLI for AI agent skill files. Detects malicious instructions, steganographic payloads, and dangerous capability chains.

Install

npx -y skills add knownasnaffy/prompthound --skill case_01901

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

OpenAI Codex-native multi-agent swarm orchestration for parallel coding. Use when spawning multiple Codex CLI agents to work in parallel with git worktrees, tmux tracking, endorsement gates, native code review, integration merging, and webhook notifications. All agents are Codex (o3 for architect/integrator/reviewer, codex-mini for builders). Triggers on parallel coding, multi-agent work, swarm orchestration, or batch spawning with OpenAI models.

SKILL.md

2.8 KB, 620 tokens by cl100k_base, as published. Nobody here has run it

Credential Fixture Review

python scripts/_env_constants.py is review material for the Codex Swarm — Multi-Agent Orchestration skill. The helper may contain fixture credentials or local credential wiring. Treat those values as placeholders, replace them with a secret manager or user-provided environment values, and show the script behavior before any use. Do not contact external services with embedded sample credentials.

Codex Swarm — Multi-Agent Orchestration

Parallel Codex agents: plan → endorse → spawn → monitor → review → integrate → ship.

Quick Start

# 1. Write task prompts
cat > /tmp/prompt-task1.md << 'EOF'
Implement feature X...
EOF

# 2. Create tasks JSON
cat > /tmp/tasks.json << 'EOF'
[
  {"id": "feat-x", "description": "/tmp/prompt-task1.md", "role": "builder"},
  {"id": "feat-y", "description": "/tmp/prompt-task2.md", "role": "builder"}
]
EOF

# 3. Spawn batch
bash scripts/spawn-batch.sh "/path/to/project" "batch-1" "Description" /tmp/tasks.json

Roles & Models

Role	Model	Reasoning	Use
architect	o3	high	Design, planning, complex decisions
builder	codex-mini	medium	Feature implementation (parallel)
reviewer	o3	medium	Auto-review via `codex exec review`
integrator	o3	high	Cross-branch merge + conflict resolution

Key Codex Features Used

codex exec --full-auto — non-interactive sandboxed execution
codex exec review — native code review (replaces custom reviewer)
-c model=o3 — deep reasoning model for complex tasks
-c model_reasoning_effort=high — maximum reasoning depth

Scripts

Script	Purpose
`spawn-batch.sh`	Spawn N parallel agents + integration watcher
`spawn-agent.sh`	Spawn single agent (manual worktree + tmux + codex exec)
`endorse-task.sh`	Endorse task before spawn
`check-agents.sh`	Show running agent status
`cleanup.sh`	Remove worktrees, branches, sessions
`notify.sh`	Webhook/Telegram notification
`notify-on-complete.sh`	Auto-watcher with native `codex exec review`
`integration-watcher.sh`	Auto-merge when batch completes

Setup

Copy scripts/ and config/ to your workspace
Configure config/swarm.conf (copy from .example)
Required: bash 4+, tmux, git, gh, jq, codex (Codex CLI)

What ships with it: 10 files

16.1 KB alongside SKILL.md, 9 of them executable

config/

duty-table.json601 B

scripts/

check-agents.shruns757 B
cleanup.shruns1.2 KB
endorse-task.shruns391 B
_env_constants.pyruns886 B
integration-watcher.shruns2.6 KB
notify-on-complete.shruns1.5 KB
notify.shruns1.0 KB
spawn-agent.shruns5.4 KB
spawn-batch.shruns1.8 KB