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 | $0.00037 | $0.00696 |
| Sonnet 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 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 — 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.
- 11d 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 (5 stars, last pushed 9d ago), licensed MIT. It adds 75 tokens to every session and 1,393 once invoked, about $0.0004 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 skills, from other repositories
taiyi-ui-design
A design-planning guide for describing how an application's user interface should look and behave. It produces a UI-DESIGN.md document covering layouts, components, interactions, accessibility, and error states.
taiyi-evolve
A workflow skill that compares the implemented code with the frozen design after development and testing. It records architecture changes and proposes updates to DESIGN.md, the document describing the intended system structure.
taiyi-diagram-c4
A code-scanning tool that builds C4 architecture documents from a repository. It separates facts observed in the code from conclusions inferred about the design and uses Mermaid diagrams as the source format.
tmux-lane-orchestrator
Manage one tmux agent lane from its matching ops pane, inspect live pane state and Codex logs on cold start, and produce concise manager summaries for OpenClaw and adjacent project work.
docs
Use when documentation generally needs to catch up with a branch before pushing or merging, covering internal developer docs, external customer-facing docs, and release notes together — "update the docs", "do a docs pass before I merge", "make sure everything's documented". Prefer this when no single documentation…
opik-optimizer
Optimize LLM prompts, tools, and agents in Opik using standardized optimizer workflows (prompt optimization, tool optimization, and parameter tuning), dataset/metric wiring, and result interpretation.