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 zgbrenner/agentcounsel --skill enforcement-risk-memogit clone --depth 1 https://github.com/zgbrenner/agentcounselWrote 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/zgbrenner/agentcounsel/enforcement-risk-memo)<a href="https://agentmods.dev/skills/zgbrenner/agentcounsel/enforcement-risk-memo"><img src="https://agentmods.dev/badge/skills/zgbrenner/agentcounsel/enforcement-risk-memo/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/zgbrenner/agentcounsel/enforcement-risk-memo"><img src="https://agentmods.dev/badge/skills/zgbrenner/agentcounsel/enforcement-risk-memo.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 | $0.00037 | $0.02634 |
| Opus 5 | $0.00018 | $0.01317 |
| Sonnet 5 | $0.00007 | $0.00527 |
| Haiku 4.5 | $0.00004 | $0.00263 |
Grade A, and why
Enforcement Risk Memo 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 9d 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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Enforcement Risk Memo
Purpose
Produce a structured, attorney-ready draft memo assessing potential regulatory enforcement exposure for a described situation, conduct, or practice. The output organizes the facts, identifies the regulatory framework as supplied by the user, applies an analytical structure (elements, mitigating and aggravating factors, plausible regulator responses), and surfaces verification items — without predicting outcomes, inventing enforcement precedent, or asserting what any regulation requires.
This skill provides workflow discipline and output structure. It does not provide legal advice.
Use When
- A user asks to "assess our enforcement risk," "memo out the exposure here," or "what could a regulator do."
- A client describes a business practice or past conduct and wants to understand how a regulator might view it.
- Counsel needs a structured first-pass risk assessment to organize facts and frame the legal analysis before drafting advice.
- An internal compliance or legal team needs to document a risk assessment for audit, governance, or privilege log purposes.
- The user provides (or references) specific regulatory rules and asks for analysis of whether those rules are implicated.
Required Inputs
- Conduct or practice at issue: a concrete description of what happened or is happening. If vague, ask for specifics — dates, actors, decisions, volumes, systems affected.
- Regulator(s): the agency or agencies the user believes have jurisdiction (e.g., SEC, CFPB, FTC, state AG, FDA). Do not invent or assume regulators.
- Rule(s) or framework: the specific rule, statute, or guidance the user believes may be implicated. If the user cannot identify rules, note this as a gap and flag it as an attorney verification item; do not supply rules from model knowledge without clearly marking them
[UNVERIFIED — attorney must confirm]. - Relevant facts: who, what, when, where, why. Ask follow-up questions if the factual record is incomplete.
- Client posture: are we counseling the entity under review, a potential whistleblower, an industry participant, or another role? This affects tone and analytical framing.
- Jurisdiction and governing law: state/federal, domestic/cross-border. Flag as
[CONFIRM]if unclear.
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.
- 9d ago First seen · 150 lines · 37 tokens per session scan A 26a8c52e39b9
Enforcement Risk Memo is a skill published in the GitHub repository zgbrenner/agentcounsel (19 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 2,634 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 2026-09-03.
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