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 skills add TerminalSkills/skills --skill activepiecesgit clone --depth 1 https://github.com/TerminalSkills/skillsWrote 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/terminalskills/skills/activepieces)<a href="https://agentmods.dev/skills/terminalskills/skills/activepieces"><img src="https://agentmods.dev/badge/skills/terminalskills/skills/activepieces/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/skills/terminalskills/skills/activepieces"><img src="https://agentmods.dev/badge/skills/terminalskills/skills/activepieces.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00074 | $0.01397 |
| Opus 5.5 | $0.00030 | $0.00559 |
| Sonnet 5.5 | $0.00015 | $0.00279 |
| Haiku 4.5 | $0.00007 | $0.00140 |
Grade A, and why
activepieces scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 18d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Activepieces
Overview
Activepieces is an open-source workflow automation platform built with TypeScript. It ships a visual flow builder, 400+ pre-built pieces (integrations), MCP server support, code steps, and conditional branching. It is self-hosted for free with no limit on flows or runs, or used as a managed cloud service.
Instructions
Self-host with Docker Compose
Generate the two secrets first, then start the stack:
export AP_ENCRYPTION_KEY=$(openssl rand -hex 16) # 256-bit key, 32 hex chars
export AP_JWT_SECRET=$(openssl rand -hex 32)
# docker-compose.yml
services:
activepieces:
image: ghcr.io/activepieces/activepieces:latest
ports: ["8080:80"]
environment:
AP_ENGINE_EXECUTABLE_PATH: dist/packages/engine/main.js
AP_API_URL: http://localhost:8080/api
AP_FRONTEND_URL: http://localhost:8080
AP_ENCRYPTION_KEY: ${AP_ENCRYPTION_KEY}
AP_JWT_SECRET: ${AP_JWT_SECRET}
AP_POSTGRES_DATABASE: activepieces
AP_POSTGRES_HOST: postgres
AP_POSTGRES_PORT: "5432"
AP_POSTGRES_USERNAME: activepieces
AP_POSTGRES_PASSWORD: ${POSTGRES_PASSWORD}
AP_REDIS_HOST: redis
AP_REDIS_PORT: "6379"
AP_EXECUTION_MODE: UNSANDBOXED
depends_on: [postgres, redis]
postgres:
image: postgres:16
environment:
POSTGRES_DB: activepieces
POSTGRES_USER: activepieces
POSTGRES_PASSWORD: ${POSTGRES_PASSWORD}
volumes: [pgdata:/var/lib/postgresql/data]
redis:
image: redis:7-alpine
volumes:
pgdata:
export POSTGRES_PASSWORD=$(openssl rand -hex 16)
docker compose up -d
AP_ENCRYPTION_KEY and AP_JWT_SECRET must stay the same for the life of the deployment: rotating the encryption key makes every stored connection undecryptable, and rotating the JWT secret signs everyone out.
Build a flow with a code step
Code steps run Node.js inside the flow:
// Inside an Activepieces Code step
export const code = async (inputs: { lineItems: { sku: string; price: number; qty: number }[] }) => {
const total = inputs.lineItems.reduce((sum, item) => sum + item.price * item.qty, 0)
return {
total,
overThreshold: total > 500,
}
}
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.
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.
- 18d ago Changed · +51 lines · +30 tokens per session 5b5cfdb6be7c
- 1mo ago First seen · 102 lines · 44 tokens per session scan A 798a3823b9e1
activepieces is a skill published in the GitHub repository TerminalSkills/skills (175 stars, last pushed yesterday), licensed Apache-2.0. It adds 74 tokens to every session and 1,397 once invoked, about $0.0003 per session on Opus 5.5. 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.
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