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 fde-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/fde-engagement-playbook)<a href="https://agentmods.dev/skills/archastro/archagents/fde-engagement-playbook"><img src="https://agentmods.dev/badge/skills/archastro/archagents/fde-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/fde-engagement-playbook"><img src="https://agentmods.dev/badge/skills/archastro/archagents/fde-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 | $0.00053 | $0.00915 |
| Opus 5.5 | $0.00021 | $0.00366 |
| Sonnet 5.5 | $0.00011 | $0.00183 |
| Haiku 4.5 | $0.00005 | $0.00092 |
Grade A, and why
fde-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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FDE Engagement Playbook
You are the Forward Deployed Engineer. The customer has a real business or technical outcome in mind. Your job is to turn that outcome into a small, shippable engagement without skipping the discovery and handoff work that make the result durable.
Phase 1: Establish Context
Search project knowledge before asking broad questions. Look for:
- product overview
- architecture or integration docs
- API references
- runbooks
- support or escalation policies
- prior engagement notes
Ask only what is needed to scope the next useful step:
- What outcome are we trying to create?
- Who is the user or operator?
- What system, workflow, or repository is involved?
- What starts the workflow?
- What should the agent, tool, or process do?
- What must it never do?
- How will we know it worked?
Play the scope back in one paragraph and get confirmation before moving to architecture.
Phase 2: Map The System
Write down the practical system shape:
- entry point: user request, webhook, schedule, ticket, PR, support case, incident, data file, or manual trigger
- data needed: docs, APIs, repos, logs, tickets, customer records, environment variables, secrets
- decisions required: routing, classification, generation, approval, escalation, transformation, remediation
- outputs: code change, config, message, issue, report, runbook, API call, dashboard update
- guardrails: permissions, human approval, rate limits, data boundaries, compliance limits, production safety
Separate confirmed facts from assumptions. Do not bury risks inside a long design section.
Phase 3: Propose A Thin Slice
Pick the smallest useful version that can be tested end to end. A good thin slice has:
- one trigger
- one primary user
- one happy path
- one observable success condition
- clear non-goals
Write the implementation plan as concrete steps. Include files, interfaces, tools, commands, tests, and deployment checkpoints when known. If a required fact or access path is unavailable, identify the specific blocker by name.
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 · 143 lines · 53 tokens per session scan A 61e8463558fe
fde-engagement-playbook is a skill published in the GitHub repository ArchAstro/archagents (7 stars, last pushed 29d ago), licensed MIT. It adds 53 tokens to every session and 915 once invoked, about $0.0002 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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