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 protomated/protomated-plugins-official --skill engagement-lettergit clone --depth 1 https://github.com/protomated/protomated-plugins-officialWrote 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/protomated/protomated-plugins-official/engagement-letter)<a href="https://agentmods.dev/skills/protomated/protomated-plugins-official/engagement-letter"><img src="https://agentmods.dev/badge/skills/protomated/protomated-plugins-official/engagement-letter/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/protomated/protomated-plugins-official/engagement-letter"><img src="https://agentmods.dev/badge/skills/protomated/protomated-plugins-official/engagement-letter.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 | $0.00058 | $0.02440 |
| Opus 5 | $0.00029 | $0.01220 |
| Sonnet 5 | $0.00012 | $0.00488 |
| Haiku 4.5 | $0.00006 | $0.00244 |
Grade A, and why
engagement-letter 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 8d 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 — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/engagement-letter — Engagement Letter Drafter
⚠️ AI-ASSISTED DRAFT — ATTORNEY REVIEW REQUIRED This output was generated by an AI assistant. It has not been reviewed by a licensed attorney. Do not send or have a client sign this letter without your independent review and approval. Engagement letters are binding agreements. This is not legal advice.
Draft a retainer and engagement letter from intake data in the matter folder. If the attorney has saved their own engagement-letter template, it fills that template's own wording rather than a generic letter. The attorney reviews, customizes, and sends it — the client never sees an AI-generated version without attorney sign-off.
This skill reads files only. It does not send anything.
Invocation
/engagement-letter [matter folder path or client name]
Workflow
Step 1 — Locate intake data
Use the Filesystem connector to find the matter folder. Look for:
intake.mdorintake-summary.md— client name, contact info, matter description- Prior email with client (search Gmail:
from:[client email] OR to:[client email]last 30 days) to capture agreed fee terms
If no intake file exists, ask the attorney to provide:
- Client full name and address
- Matter description (what you are being retained to do)
- Fee type: flat fee / hourly / contingency
- Fee amount or rate, and payment terms
- Any scope exclusions (what you are NOT handling)
Step 2 — Locate candidate templates
Before drafting, check whether the attorney has their own engagement-letter template on file — this skill fills in the attorney's own wording rather than a generic letter whenever one is available. Use the Filesystem connector to check, in order:
- The matter folder itself (a matter-specific override, if the attorney saved one there).
- A
templates/folder at the top level of the connected Filesystem workspace (e.g.~/Matters/templates/) — the standard place to keep a template that gets reused across every matter.
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.
- 8d ago First seen · 213 lines · 58 tokens per session scan A bbda53d70839
engagement-letter is a skill published in the GitHub repository protomated/protomated-plugins-official (2 stars, last pushed 5d ago), licensed Apache-2.0. It adds 58 tokens to every session and 2,440 once invoked, about $0.0003 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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