Borrowing it
Nothing to install: this file belongs to andersonaguiar/haiflow. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/andersonaguiar/haiflow/main/.claude/skills/integration-builder/SKILL.mdgit clone --depth 1 https://github.com/andersonaguiar/haiflowWrote 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/andersonaguiar/haiflow/integration-builder)<a href="https://agentmods.dev/skills/andersonaguiar/haiflow/integration-builder"><img src="https://agentmods.dev/badge/skills/andersonaguiar/haiflow/integration-builder/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/andersonaguiar/haiflow/integration-builder"><img src="https://agentmods.dev/badge/skills/andersonaguiar/haiflow/integration-builder.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 | $0.00150 | $0.01723 |
| Opus 5.5 | $0.00060 | $0.00689 |
| Sonnet 5.5 | $0.00030 | $0.00345 |
| Haiku 4.5 | $0.00015 | $0.00172 |
Grade B, and why
integration-builder scanned grade B with 2 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 2mo 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
curl -X POST localhost:3333/session/start -d '{"cwd":"/path/to/project"}' Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST localhost:3333/session/start -d '{"cwd":"/path/to/project"}' How it starts
The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Integration Builder
Build integrations between services using haiflow as the AI orchestration layer. Haiflow wraps Claude Code in tmux sessions and exposes a REST API — integrations trigger prompts, queue work, and poll for responses over HTTP.
Project references (read these for API details, don't duplicate):
README.md— Full API docs, setup, and architecturesrc/index.ts— Endpoint implementations and typesexamples/chained-calc/— Chained calc workflow example
Workflow
- Discover — What services to connect, what triggers the flow, what data moves
- Research — Look up API/library capabilities via context7
- Propose — Recommend n8n or raw integration path, present the plan
- Build — Create the workflow or code
- Deploy — Activate in n8n or hand off runnable code
Phase 1: Discover
Ask concise questions (max 3 per message) to understand:
- Source system(s) — Where does data/event originate?
- Destination system(s) — Where should data/action land?
- Trigger — Webhook, schedule, manual, or polling?
- Data flow — What moves between systems? Transforms needed?
- Path preference — n8n workflow or raw code?
n8n vs raw code decision:
| Factor | n8n | Raw code |
|---|---|---|
| User has n8n instance or n8n MCP available | Prefer | - |
| Visual workflow management needed | Prefer | - |
| Many conditional branches | Prefer | - |
| High-performance / low-latency | - | Prefer |
| Deep custom logic / complex transforms | - | Prefer |
| User explicitly prefers code | - | Prefer |
Default to n8n if user mentions it or mcp__n8n-mcp__* tools are available.
Phase 2: Research
Use context7 MCP to research each service/library involved:
mcp__context7__resolve-library-id— Resolve each service/library namemcp__context7__query-docs— Query for:- Authentication methods
- Available endpoints / webhook events
- Rate limits or quirks
- SDK availability
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.
- 2mo ago First seen · 195 lines · 150 tokens per session scan B 5422f32986ff
integration-builder is a skill published in the GitHub repository andersonaguiar/haiflow (10 stars, last pushed yesterday), licensed MIT. It adds 150 tokens to every session and 1,723 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
groq-inference
Ultra-fast LLM inference on custom LPU hardware. OpenAI-compatible API at api.groq.com. Lowest latency in the industry (500-1000+ tok/s). Supports chat completions, vision, audio (Whisper STT + TTS), tool calling, JSON mode, and streaming. Free tier available. Inference only — no training.
better-t-stack
Create or extend an end-to-end type-safe TypeScript project with Better-T-Stack (create-better-t-stack). Use when the user wants to start, scaffold or bootstrap an app, API, fullstack project or monorepo with any of Next.js, TanStack Router or Start, React Router, Nuxt, Svelte, Solid, Astro, React Native, Hono…
protocolsio-integration
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io…
bunqueue
Use when building or operating bunqueue queues, workers, durable workflows, agent turns, MCP tools, retries, cron or dependency flows.
tauri-django-react
Agents should invoke this skill for Tauri + Django + React desktop apps, especially backend lifecycle, CORS/auth, frontend integration, mandatory light/dark theming, German/English i18n, build packaging, dual desktop/web deployment, Rust commands, and platform-specific gotchas.
multi-app-orchestration
Orchestrate workflows across multiple applications and APIs — inter-app coordination, data handoff, and multi-system task completion.