Implementing Compliance
ancoleman/ai-design-components
Implement and maintain compliance with SOC 2, HIPAA, PCI-DSS, and GDPR using unified control mapping, policy-as-code enforcement, and automated evidence collection.
Guides privacy audit evidence collection processes including evidence planning, sampling strategies, documentation standards, chain of custody, interview techniques, system walkthrough procedures…
Install Audit Evidence Collect
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill audit-evidence-collect -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills audit-evidence-collect --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/privacy/audit-evidence-collect .claude/skills/audit-evidence-collect && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "audit-evidence-collect" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/audit-evidence-collect into .claude/skills/audit-evidence-collect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "audit-evidence-collect", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/audit-evidence-collectType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill audit-evidence-collect -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills audit-evidence-collect --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/privacy/audit-evidence-collect .agents/skills/audit-evidence-collect && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "audit-evidence-collect" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/audit-evidence-collect into .agents/skills/audit-evidence-collect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "audit-evidence-collect", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill audit-evidence-collect -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills audit-evidence-collect --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/privacy/audit-evidence-collect .cursor/skills/audit-evidence-collect && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "audit-evidence-collect" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/audit-evidence-collect into .cursor/skills/audit-evidence-collect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "audit-evidence-collect", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mukul975/Privacy-Data-Protection-Skills.git --path skills/privacy/audit-evidence-collect--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill audit-evidence-collect -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills audit-evidence-collect --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/privacy/audit-evidence-collect .gemini/skills/audit-evidence-collect && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "audit-evidence-collect" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/audit-evidence-collect into .gemini/skills/audit-evidence-collect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "audit-evidence-collect", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mukul975/Privacy-Data-Protection-Skills audit-evidence-collectInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill audit-evidence-collect -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/privacy/audit-evidence-collect .github/skills/audit-evidence-collect && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "audit-evidence-collect" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/audit-evidence-collect into .github/skills/audit-evidence-collect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "audit-evidence-collect", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill audit-evidence-collect -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills audit-evidence-collect --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/privacy/audit-evidence-collect .opencode/skills/audit-evidence-collect && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "audit-evidence-collect" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/audit-evidence-collect into .opencode/skills/audit-evidence-collect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "audit-evidence-collect", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
audit-evidence-collect- GitHub stars
- 301
- Token cost
- ~1.5k tokens
- SKILL.md length
- 627 words
- Files
- 5 (incl. scripts, references, assets)
- Skills in repo
- 280
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Guides privacy audit evidence collection processes including evidence planning, sampling strategies, documentation standards, chain of custody, interview techniques, system walkthrough procedures…
- Works in 5 steps: Labeled: Unique reference number, date… → Stored securely: Encrypted storage with… → Cross-referenced: Linked to specific… → …
- Tasks that involve Privacy and GDPR
- SKILL.md covers Overview, Evidence Categories, Evidence Quality Criteria and Sampling Approaches, plus 4 more sections
- Runs Python scripts from its folder
What it does
Audit Evidence Collect is an agent skill from mukul975/Privacy-Data-Protection-Skills. Guides privacy audit evidence collection processes including evidence planning, sampling strategies, documentation standards, chain of custody, interview techniques, system walkthrough procedures, and evidence evaluation. Covers ISO 19011 evidence categories (records, statements of fact, observations) and ISACA audit evidence requirements for privacy compliance assessments. Keywords: audit evidence, evidence collection, sampling, chain of custody, audit documentation, interview techniques.
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts, reference files and assets (for example `assets/template.md`, `references/standards.md` and `references/workflows.md`).
It sits in Legal & Compliance, covering Privacy and GDPR, SOC 2 and security compliance and Audit readiness. The repository describes itself as: 282+ structured privacy & data protection skills for AI agents. GDPR, CCPA, EU AI Act, HIPAA, LGPD, PIPL, DPDP Act. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Privacy and GDPR
- Tasks that involve SOC 2 and security compliance
- Tasks that involve Audit readiness
Example prompts
- “Use the audit-evidence-collect skill to guide privacy audit evidence collection processes including evidence planning, sampling strategies…”
- “/audit-evidence-collect”
Requirements
- Python 3
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Labeled: Unique reference number, date collected, source, collector name
- Stored securely: Encrypted storage with access controls appropriate to data sensitivity
- Cross-referenced: Linked to specific audit objectives and findings
- Time-stamped: Collection date and date of the evidence item
- Authenticated: Screenshots include system timestamps; documents include version information
What it can do on your machine
Read from SKILL.md and the folder at commit 9b2ef9e. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Audit Evidence Collect loads about 1.5k tokens when it runs, and up to ~3.4k if it reads all its reference files. Until then it costs about 129 tokens; SKILL.md has 627 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from mukul975/Privacy-Data-Protection-Skills at commit 9b2ef9e, republished under its Apache-2.0 licence (© mukul975). 627 words, ~1,544 tokens.
Download SKILL.mdSave it as
.claude/skills/audit-evidence-collect/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- audit-evidence-collect
- description
- Guides privacy audit evidence collection processes including evidence planning, sampling strategies, documentation standards, chain of custody, interview techniques, system walkthrough procedures, and evidence evaluation. Covers ISO 19011 evidence categories (records, statements of fact, observations) and ISACA audit evidence requirements for privacy compliance assessments. Keywords: audit evidence, evidence collection, sampling, chain of custody, audit documentation, interview techniques.
- license
- Apache-2.0
- metadata.author
- mukul975
- metadata.version
- 1.0
- metadata.domain
- privacy
- metadata.subdomain
- privacy-audit-certification
- metadata.tags
- audit-evidence, evidence-collection, sampling, chain-of-custody, audit-documentation
Audit Evidence Collection
Overview
Audit evidence collection is the systematic process of gathering sufficient, reliable, relevant, and useful information to support audit findings and conclusions. In privacy audits, evidence must demonstrate the degree of compliance with data protection regulations (GDPR, CCPA, HIPAA), internal policies, and industry standards. The quality of evidence directly determines the credibility and defensibility of audit conclusions.
ISO 19011:2018 defines audit evidence as "records, statements of fact, or other information which are relevant to the audit criteria and verifiable." The IIA Standards require that internal auditors "identify sufficient, reliable, relevant, and useful information to achieve the engagement's objectives" (Standard 2310).
Evidence Categories
Documentary Evidence
- Policies and procedures: Data protection policies, privacy notices, retention schedules, breach response plans
- Records: Processing activity records (Art. 30 ROPA), consent records, DSAR logs, DPIA reports, breach registers
- Contracts: Data processing agreements (Art. 28), joint controller arrangements (Art. 26), standard contractual clauses
- Training records: Attendance logs, completion certificates, training materials, competency assessments
- Correspondence: DPA correspondence, data subject complaints, vendor communications
Testimonial Evidence
- Interviews: Structured interviews with DPO, process owners, data stewards, IT administrators
- Declarations: Written statements from management regarding compliance posture
- Walkthroughs: Verbal explanations of processes during system demonstrations
Observational Evidence
- System walkthroughs: Live demonstrations of privacy controls in IT systems
- Physical inspection: Physical security controls, clean desk compliance, document handling
- Process observation: Real-time observation of DSAR handling, consent collection, breach triage
Analytical Evidence
- Data analysis: Consent rate analysis, DSAR response time metrics, breach statistics
- Trend analysis: Compliance metrics over time, training completion trends
- Benchmarking: Comparison against regulatory expectations or industry standards
Evidence Quality Criteria
| Criterion | Definition | Application |
|---|---|---|
| Sufficiency | Enough evidence to support findings | Multiple evidence items per finding; corroboration |
| Reliability | Evidence is trustworthy and verifiable | Source independence, system-generated over self-reported |
| Relevance | Evidence relates to audit objectives | Direct link to audit criteria and control being tested |
| Usefulness | Evidence helps reach conclusions | Actionable, clear, and understandable by stakeholders |
Sampling Approaches
Statistical Sampling
- Random sampling: Each item has equal probability of selection; suitable for large homogeneous populations
- Stratified sampling: Population divided into strata (e.g., by data category, department); samples drawn from each stratum
- Systematic sampling: Every nth item selected; useful for time-ordered records
Show full SKILL.md (269 more words)Show less
Non-Statistical (Judgmental) Sampling
- Risk-based selection: Focus on high-risk processing activities, special category data, cross-border transfers
- Key item sampling: Select all items above a materiality threshold (e.g., all DPIAs for high-risk processing)
- Discovery sampling: Sample specifically to detect at least one instance of non-compliance
Evidence Documentation Standards
All evidence must be:
- Labeled: Unique reference number, date collected, source, collector name
- Stored securely: Encrypted storage with access controls appropriate to data sensitivity
- Cross-referenced: Linked to specific audit objectives and findings
- Time-stamped: Collection date and date of the evidence item
- Authenticated: Screenshots include system timestamps; documents include version information
Chain of Custody
For evidence that may support regulatory enforcement or legal proceedings:
- Document who collected the evidence, when, and from whom
- Record all transfers of evidence between team members
- Maintain integrity (hash values for digital evidence)
- Restrict access to authorized audit team members only
- Retain evidence per the audit evidence retention policy (typically 7 years for privacy audits)
Interview Best Practices
- Prepare: Review available documentation before the interview; prepare targeted questions
- Open-ended questions: Start with broad questions, then narrow to specifics
- Corroborate: Verify interview statements against documentary or observational evidence
- Document contemporaneously: Take notes during the interview; produce a summary within 24 hours
- Validate: Share interview notes with the interviewee for confirmation of accuracy
Integration Points
- audit-remediation-program: Evidence supports finding documentation and remediation verification
- audit-follow-up-verify: Follow-up audits require new evidence collection to verify remediation
- ai-dpia: DPIA audits require specific evidence types (algorithmic impact assessments, fairness metrics)
- records-of-processing: ROPA serves as key documentary evidence in any privacy audit
© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 4 other files (scripts, references, assets) in skills/privacy/audit-evidence-collect of mukul975/Privacy-Data-Protection-Skills.
- SKILL.md
- assets/template.md
- references/standards.md
- references/workflows.md
- scripts/process.py
Open the folder on GitHubat commit 9b2ef9e
Compare with similar skills
Audit Evidence Collect next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Audit Evidence Collect this skillmukul975/Privacy-Data-Protection-Skills | 301 | — | ~1.5k | Automated safety check: Pass | Apache-2.0 | |
| Implementing Complianceancoleman/ai-design-components | 525 | — | ~4k | Automated safety check: Pass | MIT | |
| Performing Soc2 Type2 Audit Preparationmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~2.7k | Automated safety check: Pass | Apache-2.0 | |
| Compliance Osalirezarezvani/claude-skills | 28k | — | ~3.3k | Automated safety check: Pass | MIT | |
| Cursor Compliance Auditjeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~2.3k | Automated safety check: Notes | MIT | |
| Compliance Checklistmohitagw15856/pm-claude-skills | 1.4k | — | ~1.2k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Audit Evidence Collect
What does Audit Evidence Collect do?
Guides privacy audit evidence collection processes including evidence planning, sampling strategies, documentation standards, chain of custody, interview techniques, system walkthrough procedures…. Audit Evidence Collect is an agent skill from mukul975/Privacy-Data-Protection-Skills. Guides privacy audit evidence collection processes including evidence planning, sampling strategies, documentation standards, chain of custody, interview techniques, system walkthrough procedures, and evidence evaluation.
When should I use Audit Evidence Collect?
Audit Evidence Collect fits situations like: tasks that involve Privacy and GDPR; tasks that involve SOC 2 and security compliance; tasks that involve Audit readiness.
How do I install Audit Evidence Collect in Claude Code?
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill audit-evidence-collect -a claude-code`. Or copy the skill folder (skills/privacy/audit-evidence-collect in mukul975/Privacy-Data-Protection-Skills) into .claude/skills/audit-evidence-collect in your project. Claude Code loads it when a task matches its description.
How do I install Audit Evidence Collect in Codex?
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill audit-evidence-collect -a codex`. Or copy the skill folder (skills/privacy/audit-evidence-collect in mukul975/Privacy-Data-Protection-Skills) into .agents/skills/audit-evidence-collect in your project. Codex loads it when a task matches its description.
Can I use Audit Evidence Collect in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill audit-evidence-collect -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/audit-evidence-collect, .gemini/skills/audit-evidence-collect, .github/skills/audit-evidence-collect and .opencode/skills/audit-evidence-collect in your project.
What does Audit Evidence Collect need to run?
Going by SKILL.md and its folder, Audit Evidence Collect needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Audit Evidence Collect access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Audit Evidence Collect safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Audit Evidence Collect use?
Audit Evidence Collect is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Audit Evidence Collect use?
About 1.5k tokens (SKILL.md is roughly 6.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.9k tokens, read only when the agent opens those files.
What are the alternatives to Audit Evidence Collect?
Skills that share tags, products or a category with Audit Evidence Collect: Implementing Compliance (ancoleman/ai-design-components, 525 stars), Performing Soc2 Type2 Audit Preparation (mukul975/Anthropic-Cybersecurity-Skills, 34k stars), Compliance Os (alirezarezvani/claude-skills, 28k stars) and Cursor Compliance Audit (jeremylongshore/tons-of-skills-marketplace, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Audit Evidence Collect?
mukul975 (a GitHub user) maintains it in mukul975/Privacy-Data-Protection-Skills, which has 301 GitHub stars. The repository holds 280 skills in this directory. The repository was last updated on March 16, 2026.
Source: mukul975/Privacy-Data-Protection-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.