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 pipefy/ai-toolkit --skill pipefy-automationsgit clone --depth 1 https://github.com/pipefy/ai-toolkitWrote 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/pipefy/ai-toolkit/pipefy-automations)<a href="https://agentmods.dev/skills/pipefy/ai-toolkit/pipefy-automations"><img src="https://agentmods.dev/badge/skills/pipefy/ai-toolkit/pipefy-automations/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/pipefy/ai-toolkit/pipefy-automations"><img src="https://agentmods.dev/badge/skills/pipefy/ai-toolkit/pipefy-automations.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
- Socket pass
- Snyk 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 | $0.00055 | $0.06031 |
| Opus 5.5 | $0.00022 | $0.02412 |
| Sonnet 5.5 | $0.00011 | $0.01206 |
| Haiku 4.5 | $0.00006 | $0.00603 |
Grade A, and why
pipefy-automations 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 17d 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 — 308 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Automations
Read only the reference for your active surface: MCP or CLI. The workflows below use shared operation names and arguments.
Traditional automations (if/then rules), AI automations (prompt-driven), task automations, and simulation.
For AI agents (conversational agents with behaviors), see pipefy-ai-agents.
Traditional automations (rules engine)
| Operation | Purpose |
|---|---|
get_automations |
List rules with event_id, event_params, condition, actionEnabled, and disabledReason. Empty condition expressions are API placeholders, not active filters. Pages hold at most 50 rules; continue with after before concluding a rule or filter does not exist. |
get_automation |
Single automation with full rule config — returns event_params and action_params (including aiParams for AI rules). |
create_automation |
Create an if/then rule. active defaults to true. First-class typed condition (see Conditions); other fields via extra_input. |
update_automation |
Patch a rule: first-class typed condition (see Conditions) and/or extra_input. |
delete_automation |
Destructive delete. |
simulate_automation |
AI-only dry-run (generate_with_ai action). |
get_automation_events |
Available trigger events. |
get_automation_event_attributes |
Official field_map.value event-attribute tokens. |
get_automation_actions |
Available action types for a pipe. |
create_send_task_automation |
Shortcut for send-a-task rules. |
Logs, usage, and job exports for automations live in pipefy-observability (get_automation_logs, get_automation_logs_by_repo, get_automations_usage, export_automation_jobs, and related tools).
AI automations (prompt-driven)
Consent: create or suggest an AI automation only when the user explicitly asked for AI. If it seems useful but was not requested, ask first — never introduce AI automations without being asked.
What ships with it
2 files 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.
- 17d ago Changed · +22 lines · -5 tokens per session c96e98ec6450
- 1mo ago First seen · 286 lines · 60 tokens per session scan A 5440730045fe
pipefy-automations is a skill published in the GitHub repository pipefy/ai-toolkit (51 stars, last pushed yesterday), licensed Apache-2.0. It adds 55 tokens to every session and 6,031 once invoked, about $0.0002 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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