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-api-fallbackgit 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-api-fallback)<a href="https://agentmods.dev/skills/pipefy/ai-toolkit/pipefy-api-fallback"><img src="https://agentmods.dev/badge/skills/pipefy/ai-toolkit/pipefy-api-fallback/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-api-fallback"><img src="https://agentmods.dev/badge/skills/pipefy/ai-toolkit/pipefy-api-fallback.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
- Socket pass
- Snyk pass
SkillSpector: 10 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 7 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 44 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Supply Chain · line 38 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- medium Data Exfiltration · line 38 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 64 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 75 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 84 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 75 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 84 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 117 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00086 | $0.02990 |
| Opus 5.5 | $0.00034 | $0.01196 |
| Sonnet 5.5 | $0.00017 | $0.00598 |
| Haiku 4.5 | $0.00009 | $0.00299 |
Grade A, and why
pipefy-api-fallback scanned grade A with 1 finding 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 8d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
call the Pipefy GraphQL API directly using curl or httpx, authenticating How it starts
The opening of the file, as written. The whole thing — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pipefy API Fallback (Tier 3 — Last Resort)
Read the MCP reference or CLI reference for the surface you are using. Load only the relevant reference.
This skill activates only after Tiers 1 and 2 have failed. Call the Pipefy GraphQL API directly, bypassing the toolkit connection.
If a write reports failure, re-read the target before changing tiers or retrying. The mutation may already have applied; follow Ambiguous write failure.
3-tier resolution strategy (always follow in order)
- Try a dedicated operation (
create_card,get_phase_cards,get_phase_allowed_move_targets,update_pipe, etc.). For card/phase seeding and inventory, seepipefy-pipes-and-cards— Seed pipe across phases. - Use schema introspection and
execute_graphqlwhen a dedicated operation is unavailable or fails unexpectedly. Seepipefy-introspection. - Use direct HTTP only when the toolkit connection is unavailable or GraphQL execution fails with an infrastructure error.
Do not jump to Tier 3 after a single failure. Follow the tiers in order. Testing a new mutation belongs in Tier 2.
Authentication
Two options (use whichever is available in the environment). Prefer the Service Account when both exist.
To see which variables are set, list their names only, never their values:
env | cut -d= -f1 | grep '^PIPEFY_'
Do not run env, printenv, or echo on these variables to choose an option: that prints the secret into the conversation before the user agrees.
Before reading any PIPEFY_* variable, tell the user which variable you will read and that its value goes to app.pipefy.com in the Authorization header or the token request, and wait for a yes. Do not read it from a file the user did not name.
Option A — OAuth2 Client Credentials (preferred):
TOKEN=$(curl -s -X POST https://app.pipefy.com/oauth/token \
-H "Content-Type: application/json" \
-d "{\"grant_type\":\"client_credentials\",\"client_id\":\"$PIPEFY_SERVICE_ACCOUNT_CLIENT_ID\",\"client_secret\":\"$PIPEFY_SERVICE_ACCOUNT_CLIENT_SECRET\"}" \
| python3 -c "import sys,json; print(json.load(sys.stdin)['access_token'])")
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.
- 8d ago Changed · +11 lines 8e1648b12068
- 11d ago Changed · -8 lines a616095e7cf9
- 1mo ago First seen · 230 lines · 86 tokens per session scan A 58b3254225c2
pipefy-api-fallback is a skill published in the GitHub repository pipefy/ai-toolkit (50 stars, last pushed yesterday), licensed Apache-2.0. It adds 86 tokens to every session and 2,990 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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