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-process-designgit 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-process-design)<a href="https://agentmods.dev/skills/pipefy/ai-toolkit/pipefy-process-design"><img src="https://agentmods.dev/badge/skills/pipefy/ai-toolkit/pipefy-process-design/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-process-design"><img src="https://agentmods.dev/badge/skills/pipefy/ai-toolkit/pipefy-process-design.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 | $0.00089 | $0.01211 |
| Opus 5.5 | $0.00036 | $0.00484 |
| Sonnet 5.5 | $0.00018 | $0.00242 |
| Haiku 4.5 | $0.00009 | $0.00121 |
Grade A, and why
pipefy-process-design 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 12d 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pipefy Process Design
Read the MCP reference or CLI reference for the surface you are using. Load only the relevant reference.
This skill activates when the user wants consulting help to design a process — not when they want you to build one. If the user already knows what they want (gave you phases, fields, a spec, or a clear use case), do not use this skill. Execute directly.
When to use vs when to execute
| Signal | Response |
|---|---|
| "Help me design a process for X" | Use this skill — consulting mode. |
| "What's the best structure for Y?" | Use this skill — architecture guidance. |
| "Create a pipe for X" | Skip this skill — route via pipefy-building, then the domain skill. |
| User provides phases, fields, or a spec | Skip this skill — the spec IS the plan. Route via pipefy-building, then build. |
Prerequisites
- Understand the user's industry and use case before advising structure.
- Always search for existing pipes in the org before recommending a new one (
search_pipes).
Discovery phase
-
Research existing org structure:
Operation:
search_pipes pipe_name=""(empty search returns all visible pipes) Operation:get_organization organization_id=<id> -
Understand the process intent:
- What triggers a new case? (form submission, email, manual)
- Who are the actors? (submitter, approver, ops team)
- What are the key decision points? (approve/reject, escalate, auto-close)
- What data needs to be tracked? (fields per phase)
- Are there related processes that should be connected? (use relations)
-
Identify the right Pipefy components:
Need Component Workflow stages Pipe + Phases Structured data per stage Phase fields Reference/lookup data Database table Cross-process linkage Pipe relation Automatic actions Automation rule AI-driven processing AI automation or AI agent
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.
- 12d ago Changed · +6 lines 3289b4141663
- 1mo ago First seen · 122 lines · 89 tokens per session scan A 4f11b6820b99
pipefy-process-design is a skill published in the GitHub repository pipefy/ai-toolkit (50 stars, last pushed 3d ago), licensed Apache-2.0. It adds 89 tokens to every session and 1,211 once invoked, about $0.0004 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.
Other skills, from other repositories
atmos-modernization
Atmos Modernization: migrate deprecated or legacy Atmos patterns to current names, Native CI, Atmos Pro drift detection, dependencies.components, nametemplate, and declared secrets.
atmos-init
Bootstrapping new Atmos projects with atmos init: built-in template catalog, differences from atmos scaffold generate, project record, and update-safe 3-way merge.
atmos-workflows
Workflow automation: native step types, multi-step workflows, parallel/matrix/wait/container/emulator steps, when: conditions (CEL), require/assert preconditions, output steps, retries, dependencies, and cross-component orchestration.
atmos-config
Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.
atmos-imports
Atmos imports: local and remote stack imports, go-getter schemes, templated imports, import context, remote imports vs component source/vendoring, and private GitHub imports through github/sts.
squads-cli
Squads CLI — operate your squads through the loop; intent in, reviewed work out. TRIGGER when running squads, dispatching agents, triaging the inbox, reading/writing memory, recording feedback, or checking status/usage.