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 skills/jpoutrin/product-forge/parallel-executionnpx skills add jpoutrin/product-forge --skill parallel-executiongit clone --depth 1 https://github.com/jpoutrin/product-forgeWrote 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/skills/jpoutrin/product-forge/parallel-execution)<a href="https://agentmods.dev/skills/jpoutrin/product-forge/parallel-execution"><img src="https://agentmods.dev/badge/skills/jpoutrin/product-forge/parallel-execution.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 5.1 | $0.00033 | $0.01118 |
| Opus 5 | $0.00016 | $0.00559 |
| Sonnet 5 | $0.00007 | $0.00224 |
| Haiku 4.5 | $0.00003 | $0.00112 |
Grade A, and why
parallel-execution 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 2d 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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Parallel Execution
Execute multiple Claude Code agents in parallel using the cpo (Claude Parallel Orchestrator) CLI.
Primary Method: cpo CLI
The cpo tool handles all execution complexity: git worktrees, wave dependencies, and progress monitoring.
Installation
pip install claude-parallel-orchestrator
# or
pipx install claude-parallel-orchestrator
Commands
| Command | Description |
|---|---|
cpo validate <dir> |
Validate manifest structure and prompts |
cpo run <dir> |
Execute all waves (respects dependencies) |
cpo status <dir> |
Check execution status |
Basic Workflow
# 1. Validate before execution
cpo validate parallel/TS-0042-inventory-system/
# 2. Execute parallel agents
cpo run parallel/TS-0042-inventory-system/
# 3. Monitor progress (in another terminal)
cpo status parallel/TS-0042-inventory-system/
What cpo run Does
- Validates manifest.json structure and prompt files
- Creates git worktrees for each task (isolated workspaces)
- Launches agents in parallel (respects wave dependencies)
- Monitors progress with live output
- Collects results in
logs/andreport.json
Wave Execution
Tasks execute in waves based on dependencies:
Wave 1: task-001, task-002, task-003 (parallel - no deps)
↓ wait for completion
Wave 2: task-004, task-005 (parallel - depend on Wave 1)
↓ wait for completion
Wave 3: task-006 (sequential - depend on Wave 2)
Each wave waits for all tasks in the previous wave to complete before starting.
Agent Permissions
Agents run with --dangerously-skip-permissions because they're isolated in worktrees:
- Each agent runs in its own git worktree
- Agents can only affect files in their workspace
- Main branch remains protected until explicit merge
Alternative: Claude Code SDK
For programmatic orchestration in CI/CD or custom workflows:
// orchestrator.ts
import { ClaudeAgent } from '@anthropic-ai/claude-agent-sdk';
import { readdir, readFile } from 'fs/promises';
import { join } from 'path';
async function runParallelTasks(parallelDir: string) {
const tasksDir = join(parallelDir, 'tasks');
const contextFile = join(parallelDir, 'context.md');
const context = await readFile(contextFile, 'utf-8');
const tasks = await readdir(tasksDir);
const agents = tasks
.filter(f => f.endsWith('.md'))
.map(async (taskFile) => {
const taskPath = join(tasksDir, taskFile);
const taskContent = await readFile(taskPath, 'utf-8');
const agent = new ClaudeAgent({
systemPrompt: `You are implementing a task.
Context: ${context}
Follow contracts in ${parallelDir}/contracts/.`,
});
return agent.run(`Execute this task:\n\n${taskContent}`);
});
const results = await Promise.all(agents);
return results;
}
runParallelTasks('parallel/TS-0042-inventory-system');
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.
- 2d ago First seen · 160 lines · 33 tokens per session scan A ea738ee93632
parallel-execution is a skill published in the GitHub repository jpoutrin/product-forge (15 stars, last pushed 6mo ago), licensed MIT. It adds 33 tokens to every session and 1,118 once invoked, about $0.0002 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 2026-09-03.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…