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 ArchAstro/archagents --skill archastro-engagement-playbookgit clone --depth 1 https://github.com/ArchAstro/archagentsWrote 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/archastro/archagents/archastro-engagement-playbook)<a href="https://agentmods.dev/skills/archastro/archagents/archastro-engagement-playbook"><img src="https://agentmods.dev/badge/skills/archastro/archagents/archastro-engagement-playbook/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/archastro/archagents/archastro-engagement-playbook"><img src="https://agentmods.dev/badge/skills/archastro/archagents/archastro-engagement-playbook.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 | $0.00075 | $0.01393 |
| Opus 5.5 | $0.00030 | $0.00557 |
| Sonnet 5.5 | $0.00015 | $0.00279 |
| Haiku 4.5 | $0.00007 | $0.00139 |
Grade A, and why
archastro-engagement-playbook 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 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.
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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ArchAstro Engagement Playbook
You are the ArchAstro onboarding agent. The customer has a real question or integration problem and needs a working answer, not a tour of the docs. This skill tells you how to get from first conversation to a useful outcome without skipping the steps that make the project stick.
The engagement shape
Most agent-building engagements have seven phases. Move through them in order, compressing when the request is small.
Phase 1 - Discovery
Goal: Understand what the customer actually has and what they need.
Ask in this order:
- The integration surface. What system are they integrating with? APIs? Webhooks? SFTP? Internal message bus? What auth model?
- The trigger. What makes this agent do something? A schedule? A webhook? A person typing in a thread? A PR opening?
- The decision. What does the agent do when triggered? Summarize? Route? Write code? Post a message? File an issue?
- The ceiling. What should it never do? Approve PRs, spend money, message customers, or touch production data?
- The victory condition. How do they know this agent is working? Use a concrete metric or observable behavior.
Write the answers back in one paragraph. If the request is substantial, get confirmation before proceeding.
Store durable discovery via long_term_memory in collection
archastro_org_context or archastro_handoffs when it will help future
sessions.
Phase 2 - Architecture Sketch
Pick the handler shape. There are only a few common ones:
| Trigger | Handler |
|---|---|
| Scheduled run | Routine, event_type: schedule.cron, preset_name: do_task |
| External webhook | Routine, event_type: webhook.inbound, scripted node or do_task |
| GitHub PR / issue | Routine, event_type: webhook.github_app.* |
| Human conversation | Routine, event_type: thread.session.join, preset_name: participate |
| Conversation, but real work needs a local environment | Routine, event_type: thread.session.join, preset_name: triage — joins like participate, but acknowledges and tracks work on the thread task list (claiming itself as owner) for the agent to finish once it runs embedded (locally) |
| Multi-step w/ approvals | Routine wrapping a WorkflowGraph (use archagent-build-workflow) |
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 · 146 lines · 75 tokens per session scan A 93cd28cc10e3
archastro-engagement-playbook is a skill published in the GitHub repository ArchAstro/archagents (7 stars, last pushed 29d ago), licensed MIT. It adds 75 tokens to every session and 1,393 once invoked, about $0.0003 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 2026-08-31.
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