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-impactgit 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-impact)<a href="https://agentmods.dev/skills/pipefy/ai-toolkit/pipefy-process-impact"><img src="https://agentmods.dev/badge/skills/pipefy/ai-toolkit/pipefy-process-impact/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-impact"><img src="https://agentmods.dev/badge/skills/pipefy/ai-toolkit/pipefy-process-impact.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00103 | $0.01784 |
| Opus 5.5 | $0.00041 | $0.00714 |
| Sonnet 5.5 | $0.00021 | $0.00357 |
| Haiku 4.5 | $0.00010 | $0.00178 |
Grade A, and why
pipefy-process-impact 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 11d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Process impact
Help the user find the one step in their process where an automation or an AI agent returns the most time, and show the arithmetic. One hop, one formula, one question per turn. The next hop comes after they have the first number.
Read the MCP reference or CLI reference only when the user names a pipe, and only for the reads listed there.
When to use
- "Is it worth automating X?" / "Where do I start?" / "What is the ROI?" / "How much time does this give back?"
- "Help me justify this internally."
- The user wants more than the
Impact:line thatpipefy-process-designorpipefy-process-intelligencealready emitted.
Not for designing a process (pipefy-process-design), a full pipe diagnosis or implementation (pipefy-process-intelligence), building the step (pipefy-building, then the domain skill), or finding what a change breaks elsewhere.
How to answer
- Pick the hop. From the conversation, name the one manual, repetitive step with the best return: a move someone does by hand, a triage, a copy-paste, a chase. With several candidates, take the one with the most cases per week. Do not walk the whole process.
- Check coverage when a pipe is named. Run the reads in the reference:
get_pipe,get_automations,get_ai_agents, thenget_ai_agentfor each active agent. If an active automation or agent already does the hop, say so, size that coverage, and move to the next uncovered hop, restating what the agent or rule already does there. Do not propose a second one. With no pipe in view, say coverage was not checked instead of claiming nothing covers the hop.cards_countis what sits in a phase now, not volume or duration, andget_cardsselects no dates; when the answer needs time, use the timed card read under Measuring. - Show the arithmetic, with the user's numbers or the gaps named:
hours returned per week ≈ minutes per case × cases per week / 60
cost avoided per week ≈ hours returned per week × hourly cost (only if the user gave an hourly cost)
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.
- 11d ago First seen · 92 lines · 103 tokens per session scan A e500d06f5ff6
pipefy-process-impact is a skill published in the GitHub repository pipefy/ai-toolkit (50 stars, last pushed yesterday), licensed Apache-2.0. It adds 103 tokens to every session and 1,784 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 2026-10-07.
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