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 skills/ao92265/claude-code-playbook/draft-replynpx skills add ao92265/claude-code-playbook --skill draft-replygit clone --depth 1 https://github.com/ao92265/claude-code-playbookWrote 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/ao92265/claude-code-playbook/draft-reply)<a href="https://agentmods.dev/skills/ao92265/claude-code-playbook/draft-reply"><img src="https://agentmods.dev/badge/skills/ao92265/claude-code-playbook/draft-reply.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 | $0.00047 | $0.00315 |
| Opus 5 | $0.00023 | $0.00158 |
| Sonnet 5 | $0.00009 | $0.00063 |
| Haiku 4.5 | $0.00005 | $0.00032 |
Grade A, and why
draft-reply 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 3d 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
Draft Reply
Prevents the recurring "first draft too technical, needs tone rework" friction.
Pre-Write Checklist (ASK IF UNSPECIFIED)
Before writing a single word, confirm:
- Recipient: name + role
- Technical level: engineer / manager / non-technical
- Tone: formal / conversational / terse / warm
- Desired action: what should the reader do after reading?
- Format: Slack thread / email / Teams / inline comment
- Length cap: sentence / paragraph / multi-paragraph
If ANY are unspecified and not obvious from context → ASK before drafting. Single batched question.
Drafting Rules
- Non-technical audience → no bullets unless explicitly requested. Conversational prose.
- Manager audience → lead with outcome/ask, technical detail only if requested.
- Engineer audience → bullets + code refs fine.
- Match the recipient's prior message style (formality, length) when reply thread exists.
Output
Single draft. No "let me know if you want changes" coda — user will iterate naturally.
Attribution
When naming people (PR authors, ticket owners) → verify via gh CLI / source-of-truth before draft. Don't guess from memory.
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.
- 3d ago First seen · 37 lines · 47 tokens per session scan A 10b3316c4453
draft-reply is a skill published in the GitHub repository ao92265/claude-code-playbook (10 stars, last pushed 17d ago), licensed MIT. It adds 47 tokens to every session and 315 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.
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