Privacy Policy Gap Review

Privacy Policy Gap Review is a skill for Claude Code, Codex from zgbrenner/agentcounsel. It costs 38 tokens per session (3,608 once invoked), scanned A, original, MIT.

A review of a published privacy policy or notice against the organization's described data practices. It identifies missing topics, unclear wording, internal contradictions, and mismatches for attorney review.

In plain words
What is it for?
It helps check privacy notices before updates, compare policy language with data practices, and prepare issues for legal redrafting.
Why use it?
It helps reveal where public privacy statements may not explain what the organization actually does with personal data.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps check privacy notices before updates, compare policy language with data practices, and prepare issues for legal redrafting.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zgbrenner/agentcounsel/privacy-policy-gap-review
Install

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.

Any agent
npx skills add zgbrenner/agentcounsel --skill privacy-policy-gap-review
Clone the repo
git clone --depth 1 https://github.com/zgbrenner/agentcounsel

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for Privacy Policy Gap Review

README.md
[![agentmods](https://agentmods.dev/badge/skills/zgbrenner/agentcounsel/privacy-policy-gap-review/github.svg)](https://agentmods.dev/skills/zgbrenner/agentcounsel/privacy-policy-gap-review)
Your own site
<a href="https://agentmods.dev/skills/zgbrenner/agentcounsel/privacy-policy-gap-review"><img src="https://agentmods.dev/badge/skills/zgbrenner/agentcounsel/privacy-policy-gap-review/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.

agentmods 80×15 button for Privacy Policy Gap Review

Your own site · 80×15
<a href="https://agentmods.dev/skills/zgbrenner/agentcounsel/privacy-policy-gap-review"><img src="https://agentmods.dev/badge/skills/zgbrenner/agentcounsel/privacy-policy-gap-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,608 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00038 $0.03608
Opus 5 $0.00019 $0.01804
Sonnet 5 $0.00008 $0.00722
Haiku 4.5 $0.00004 $0.00361

Measured 9d ago against content hash 37892c6ab7c1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

Privacy Policy Gap Review 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.

skills/privacy/privacy-policy-gap-review/SKILL.md · 179 lines

How it starts

The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Privacy Policy Gap Review

Purpose

Produce a structured, attorney-ready gap review of a published privacy policy or privacy notice. The review identifies: missing standard disclosure topics, vague or boilerplate language that may not reflect actual practice, internal inconsistencies within the policy, and discrepancies between the policy's representations and the organization's actual data practices as described by the user. It produces draft legal work product for attorney review — not legal advice.

This skill provides structural and drafting analysis only. It does not certify compliance with any specific privacy law, regulation, or jurisdiction. Whether any identified gap constitutes a legal violation — and what remediation is legally required — are attorney-verification items. The applicable law, the organization's compliance posture, and the jurisdictional scope of the policy must be determined by counsel.

Use When

  • A user asks to "review our privacy policy," "find gaps in this privacy notice," or "does our policy match what we actually do."
  • An organization is updating its privacy policy and wants a first-pass review before attorney review and redrafting.
  • A privacy audit or assessment requires a document review of the current privacy notice.
  • An organization has changed its data practices (new vendor, new product feature, new data collection) and needs to identify whether the policy needs to be updated.
  • Due diligence on a transaction requires review of the target's public-facing privacy representations.
  • A regulator or counterparty has raised concerns about the organization's privacy policy and the legal team needs a structured analysis.
  • The organization operates in multiple jurisdictions and wants to identify disclosure topics that may need to be addressed for different audiences [CONFIRM: applicable requirements with counsel].

Required Inputs

  • The privacy policy or privacy notice text — uploaded, pasted, or linked. If not provided, stop and request it. Do not fabricate or assume policy terms.
  • A description of the organization's actual data practices — what personal data is collected, from whom, for what purposes, who it is shared with, how it is processed, and how long it is retained. This description must come from the user; do not invent practices. If this description is not provided, the practice-versus-policy comparison step cannot be completed — note the gap and proceed with a structural review only, flagging the comparison as an open item.
  • Optional: the organization's industry or sector (e.g., healthcare, financial services, children's services, e-commerce) — relevant for identifying sector-specific disclosure topics to flag, though applicable law is always [CONFIRM].
  • Optional: the audience or jurisdictions the policy is intended to serve (e.g., EU residents, California residents, global) — used to identify disclosure topics commonly associated with those audiences, not to assert applicable law.
  • Optional: a prior version of the policy, if this is a revision review.
  • Optional: the practice group's practice-profiles/privacy.md if it has been populated and is loaded alongside this skill. If present, the skill uses its Standard Positions and Source-of-Truth Documents tables to benchmark the policy against the group's baseline policy template. If absent, the skill proceeds without practice-profile benchmarking and asks the user to supply standing positions inline if needed.

Read the full file on GitHub · 179 lines

Changes

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.

  1. 9d ago First seen · 179 lines · 38 tokens per session scan A 37892c6ab7c1

Subscribe to this mod's changes

Privacy Policy Gap Review is a skill published in the GitHub repository zgbrenner/agentcounsel (19 stars, last pushed 1mo ago), licensed MIT. It adds 38 tokens to every session and 3,608 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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