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completetech

Agentic Security Review Skill

by CompleteTech · GitHub ↗ · v1.0.2 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install agentic-security-review-skill
Description
Create CompleteTech LLC security, safety, permissions, and production-readiness review artifacts for agentic development workflows, including risk intake, to...
README (SKILL.md)

Agentic Security Review Skill

Purpose

Create practical security review artifacts for CompleteTech LLC agentic development workflows. Use this skill before launch, before granting new access, after material configuration changes, and after incidents or near misses.

System Boundary

This skill owns security, safety, permissions, data, credential, tool, and launch-risk review. Use it alongside discovery, proposal, or delivery when risk needs a dedicated artifact. It does not replace agentic-delivery-skill launch checklists, agentic-contract-skill legal terms, external compliance certification, formal penetration testing, or counsel-reviewed privacy/security advice.

Core Workflow

  1. Identify the review event: launch, new tool, sensitive data, external action, retrieval/RAG, credential change, dependency change, incident, or signoff.
  2. Gather verified facts: workflow purpose, users, data classes, tools, permissions, credentials, integrations, retrieval sources, human approvals, logs, deployment path, rollback owner, incident contacts, and known constraints.
  3. Use references/use-case-decision-table.md to choose the right review artifact.
  4. Use references/security-positioning.md for CompleteTech LLC security language and guardrails.
  5. Use references/security-catalog.md for the artifact library.
  6. Keep the review bounded and evidence-based. Do not claim compliance, certification, legal approval, penetration-test completion, production readiness, or guaranteed security unless the user provides verified evidence.

Artifact Selection Guide

  • Starting a new agentic workflow: use agentic-risk-intake.
  • Adding a tool or integration: use tool-permission-inventory.
  • Handling API keys, tokens, service accounts, or secrets: use credential-secret-handling-checklist.
  • Accessing sensitive, client, personal, regulated, or proprietary data: use data-exposure-review.
  • Testing prompt injection or tool misuse: use prompt-injection-test-plan.
  • Adding retrieval/RAG, indexed docs, websites, or knowledge stores: use retrieval-source-trust-review.
  • Reviewing human-in-the-loop controls: use approval-gate-audit.
  • Sending emails, creating calendar events, modifying files, posting messages, purchasing, billing, or changing production systems: use external-action-review.
  • Needing traceability, audit trails, or operational evidence: use logging-auditability-review.
  • Changing model, provider, system prompt, tool runtime, or safety settings: use model-provider-configuration-review.
  • Defining storage, deletion, or retention behavior: use data-retention-review.
  • Adding packages, services, scripts, or vendor dependencies: use dependency-supply-chain-review.
  • Reducing access scope or sandboxing execution: use sandbox-least-privilege-checklist.
  • Preparing for launch: use production-readiness-security-checklist.
  • Deciding what blocks launch: use launch-blocker-checklist.
  • Preparing a backout path: use rollback-plan.
  • Responding to a security event or near miss: use incident-response-plan.
  • Defining who to contact and when to escalate: use human-escalation-procedure.
  • Summarizing adversarial testing: use red-team-test-report.
  • Recording final approval status: use security-signoff-memo.

When several artifacts fit, start with the artifact closest to the change or decision being reviewed, then add supporting artifacts only when they materially reduce risk.

Quality Rules

  • Use verified contact routing. Do not invent client, security, legal, billing, support, or approval email addresses; ask for the right address or use TBD.
  • Preserve least privilege: name each tool, permission, credential, data class, and external action that is actually needed.
  • Protect human approval gates for irreversible actions, client-facing communication, payments, data export/deletion, production changes, and material business decisions.
  • Separate facts from recommendations. Label unknowns, assumptions, residual risks, blockers, and owner decisions.
  • Recommend technical escalation when secrets may be exposed, logs are missing, sandboxing is weak, prompt injection can trigger tools, approval gates are bypassed, production rollback is unclear, or sensitive data flows are not understood.
  • Recommend client or human approval before launch, before expanding permissions, before connecting client systems, before sending external communications, and before closing incident follow-up.

Resource Guide

  • references/security-positioning.md: load for CompleteTech LLC review language and boundaries.
  • references/use-case-decision-table.md: load when choosing a security review artifact.
  • references/security-lifecycle.md: load for review flow from intake through launch and post-incident follow-up.
  • references/security-catalog.md: load for the reusable artifact templates.
  • references/template-index.json: machine-readable artifact metadata used by the renderer.
  • scripts/render_security_review.py: list security artifacts or render a draft with placeholders.

Renderer

python3 scripts/render_security_review.py --list
python3 scripts/render_security_review.py --stage launch --list
python3 scripts/render_security_review.py --template agentic-risk-intake --var client_name=Acme --var workflow="support triage agent"

Rendered artifacts are drafts. Replace placeholders with verified project facts before sending, storing, or relying on them.

Rendering to a Branded PDF

Artifacts from this skill are delivered as branded CompleteTech LLC PDF documents, not raw Markdown. The renderer emits the PDF (and prints the Markdown) in one command, using the same reportlab branding engine as the contract skill:

pip install -r requirements.txt
python3 scripts/render_security_review.py --template security-signoff-memo \
  --out artifact.pdf --png artifact.png \
  --title "Security Signoff Memo" --doc-type "SECURITY REVIEW" \
  --subtitle "Workflow: \x3Cb>Support Email Triage Agent (Pilot)\x3C/b>" --meta "MEMO NO.=SEC-2026-0090" --meta "DATE=2026-06-17" \
  --var client_name="Client Name" --var workflow="support triage"
  • --no-pdf emits Markdown only (the original behavior); --no-cover drops the cover page.
  • Already drafted the Markdown yourself? Render it directly: python3 scripts/render_pdf.py --markdown artifact.md --out artifact.pdf --logo assets/logo.png --title "...".
  • The PDF supports a Markdown subset: #/##/### headings, paragraphs, - bullets, tables, > callouts, **bold**, and [PAGE_BREAK]. PDF requires reportlab; the optional --png preview requires pypdfium2 and pillow. See assets/examples/ for a rendered example.

Network Boundary

This skill is local-only. It does not include outbound network helpers, callbacks, or any helper that posts security-review run metadata to an external service.

Usage Guidance
Before installing, treat generated reviews as drafts, avoid entering actual secret values into templates, and install the Python PDF dependencies only if you need branded PDF or PNG output.
Capability Tags
requires-sensitive-credentials
Capability Assessment
Purpose & Capability
The artifacts coherently support drafting security, permissions, data, credential, launch-readiness, incident, and signoff review documents; credential references are review topics rather than instructions to collect or store secret values.
Instruction Scope
Instructions are bounded to evidence-based review artifact selection, local rendering, and explicit cautions not to claim compliance, legal approval, penetration testing, or production readiness without verified evidence.
Install Mechanism
The skill declares Python and uv-installed packages for reportlab and PyYAML, with optional PDF/PNG rendering dependencies in requirements.txt; these are purpose-aligned for local document generation.
Credentials
The included scripts read local templates and write user-directed Markdown/PDF/PNG outputs; the skill states it is local-only and inspection found no outbound network helpers or callbacks.
Persistence & Privilege
No background agents, autorun persistence, credential storage, privilege escalation, or broad local indexing behavior was found; outputs are generated only when the user runs the provided commands.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install agentic-security-review-skill
  3. After installation, invoke the skill by name or use /agentic-security-review-skill
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.2
Remove external receipt helper and tighten local validation
v1.0.1
Fix installed package validation and packaged contract template
v1.0.0
Initial CompleteTech public ClawHub release
Metadata
Slug agentic-security-review-skill
Version 1.0.2
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 3
Frequently Asked Questions

What is Agentic Security Review Skill?

Create CompleteTech LLC security, safety, permissions, and production-readiness review artifacts for agentic development workflows, including risk intake, to... It is an AI Agent Skill for Claude Code / OpenClaw, with 77 downloads so far.

How do I install Agentic Security Review Skill?

Run "/install agentic-security-review-skill" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Agentic Security Review Skill free?

Yes, Agentic Security Review Skill is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Agentic Security Review Skill support?

Agentic Security Review Skill is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Agentic Security Review Skill?

It is built and maintained by CompleteTech (@completetech); the current version is v1.0.2.

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