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 agentmods add commands/celigo/ai/celigo-plan-integrationgit clone --depth 1 https://github.com/celigo/aiWrote 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/commands/celigo/ai/celigo-plan-integration)<a href="https://agentmods.dev/commands/celigo/ai/celigo-plan-integration"><img src="https://agentmods.dev/badge/commands/celigo/ai/celigo-plan-integration.svg" alt="Measured on agentmods" 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 | $0.00032 | $0.00258 |
| Opus 5 | $0.00016 | $0.00129 |
| Sonnet 5 | $0.00006 | $0.00052 |
| Haiku 4.5 | $0.00003 | $0.00026 |
Grade A, and why
celigo-plan-integration 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 4d 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.
What it actually says
Help me plan a new Celigo integration. Ground your guidance in the getting-started skill (core concepts, build order, planning discipline) and building-flows skill.
First, confirm the requirements (ask me for anything I haven't already given):
- Source system(s) and destination system(s)
- What data moves, and in which direction(s)
- Sync frequency -- real-time/webhook, scheduled (cron), or on-demand
- Failure handling --
proceedOnFailure, retries, error notifications - One-off or reusable template
- Sandbox or production (never mix)
Then produce a plan:
- The resources to build bottom-up -- connections, then exports/imports, then the flow(s) -- naming each.
- For each resource, which skill to follow (e.g.
configuring-connections,configuring-exports,configuring-imports,building-flows). - Open questions, risks, and any reusable existing resources to look for first.
This is a design step -- do not create or modify any resources.
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.
- 4d ago First seen · 23 lines · 32 tokens per session scan A b9064737de81
celigo-plan-integration is a command published in the GitHub repository celigo/ai (3 stars, last pushed yesterday), licensed MIT. It adds 32 tokens to every session and 258 once invoked, about $0.0002 per session on Opus 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 2026-08-31.
Other commands, from other repositories
awesome-chatgpt
Search awesome-ChatGPT-repositories for open-source GitHub repositories related to ChatGPT and LLMs.
init
Scaffold a new MindBase project (v2 layout). Usage: /mb:init [template] [-- mission ...].
commit
智能生成 Git 提交信息并提交.
pr
Handle the full workflow from current branch state to an open, CI-monitored pull request.
doctor.es
Diagnostica problemas de inferencia LLM en Mac: asiai doctor verifica el estado de los motores, conflictos de puertos, carga de modelos y estado de la GPU.
claude-request
Send a prompt to Claude Code via the LLM gateway with session tracking.