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 d-o-hub/github-template-ai-agents --skill privacy-firstgit clone --depth 1 https://github.com/d-o-hub/github-template-ai-agentsWrote 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/d-o-hub/github-template-ai-agents/privacy-first)<a href="https://agentmods.dev/skills/d-o-hub/github-template-ai-agents/privacy-first"><img src="https://agentmods.dev/badge/skills/d-o-hub/github-template-ai-agents/privacy-first/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/d-o-hub/github-template-ai-agents/privacy-first"><img src="https://agentmods.dev/badge/skills/d-o-hub/github-template-ai-agents/privacy-first.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 | $0.00101 | $0.01177 |
| Opus 5.5 | $0.00040 | $0.00471 |
| Sonnet 5.5 | $0.00020 | $0.00235 |
| Haiku 4.5 | $0.00010 | $0.00118 |
Grade A, and why
privacy-first 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 25d 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 — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Privacy First
This skill ensures no email addresses or personal data leak into the codebase. It provides detection, prevention, and automated checking.
When to Use
- User asks: "prevent emails", "remove personal data", "privacy check", "never use email"
- Before writing any new code, config, or documentation file
- During code review or quality gate checks
- When adding contact information to any file
Agent Workflow
1. Before Writing Any File
Before creating or editing any file, check for email patterns:
# Scan the file being edited for email patterns
grep -E '[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}' <file> || true
2. Replacement Rules
| Context | Instead of | Use |
|---|---|---|
| Author/contact | [email protected] |
GitHub Issues link |
| Support | [email protected] |
https://github.com/owner/repo/issues |
| Code of Conduct | [email protected] |
"Report via GitHub Issues" |
| Package metadata | email = "..." |
Remove email field entirely |
| Examples | [email protected] |
Test domain: [email protected] (only in tests) |
3. File-Type Specific Rules
Python (pyproject.toml, setup.py)
# Bad
authors = [{name = "Author", email = "[email protected]"}]
# Good
authors = [{name = "Author"}]
Markdown (README.md, CONTRIBUTING.md)
<!-- Bad -->
Contact: [email protected]
<!-- Good -->
Report issues: https://github.com/owner/repo/issues
Configuration files
- Never add email fields
- Use URLs to GitHub instead
4. Exceptions (Allowed)
The following are permitted and should NOT be flagged:
- Test data in
tests/directories using standard test domains:example.com,example.org,test.com,localhost
- URLs in documentation pointing to external services
- Git history (cannot modify)
- Skill reference files with generic examples (for demonstration)
Quality Gate Integration
To add automated checks to pre-commit or CI:
# Add to scripts/quality_gate.sh or .pre-commit-config.yaml
# Scan for email patterns (exclude test data and git)
EMAIL_PATTERN='[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}'
# Exclude patterns (test domains, git, node_modules)
EXCLUDE_PATTERN='example\.com|example\.org|test\.com|\.git|node_modules'
# Check source files
if grep -rE "$EMAIL_PATTERN" --include="*.py" --include="*.toml" --include="*.yaml" --include="*.json" --include="*.md" . 2>/dev/null | grep -vE "$EXCLUDE_PATTERN"; then
echo "ERROR: Email address detected in codebase"
exit 1
fi
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 25d ago Changed · -3 tokens per session 8c5121da248f
- 1mo ago First seen · 147 lines · 104 tokens per session scan A fc0ac31b9fea
privacy-first is a skill published in the GitHub repository d-o-hub/github-template-ai-agents (2 stars, last pushed yesterday), licensed MIT. It adds 101 tokens to every session and 1,177 once invoked, about $0.0004 per session on Opus 5.5. 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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