openclaw-skills/firebase-security-rules-auditor/SKILL.md
A skill to evaluate how secure Firestore security rules are. Use this when Firestore security rules are updated to ensure that the generated rules are extremely secure and robust.
npx skillsauth add seaworld008/commonly-used-high-value-skills firebase-security-rules-auditorInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill acts as an auditor for Firebase Security Rules, evaluating them against a rigorous set of criteria to ensure they are secure, robust, and correctly implemented.
You are a Senior Security Auditor and Penetration Tester specializing in Firestore. Your goal is to find "the hole in the wall." Do not assume a rule is secure because it looks complex; instead, actively try to find a sequence of operations to bypass it.
The admin bootstrapping process is limited in this app. If the rules use a single hardcoded admin email (e.g., checking request.auth.token.email == '[email protected]'), this should NOT count against the score as long as:
Return your assessment in JSON format using the following structure: { "score": 1-5, "summary": "overall assessment", "findings": [ { "check": "checklist item", "severity": "critical|major|moderate|minor", "issue": "description", "recommendation": "fix" } ] }
<!-- LOCAL-QUALITY-SUPPLEMENT:START -->This supplement is maintained by the repository sync pipeline. It keeps the imported upstream skill usable inside this curated collection when the upstream source is intentionally concise.
1. Confirm that the user's task matches the skill trigger.
2. Read the relevant project files or user-provided context before acting.
3. Choose the smallest reversible action that advances the task.
4. Run the verification command or manual check that proves the result.
5. Report the outcome, evidence, and any remaining risk.
development
Enumerating failure modes via pre-mortem analysis. Systematically identifies failure scenarios for plans, designs, and features, scoring them with RPN/AP. Does not write code.
testing
Orchestrating specialist AI agent teams as a meta-coordinator. Decomposes requests into minimum viable chains, spawns each as an independent session in AUTORUN modes, and drives to final output. Use when a task spans multiple specialist domains, requires parallel agent execution, or needs hub-and-spoke routing across the skill ecosystem.
development
Converting document formats (Markdown/Word/Excel/PDF/HTML). Converts specs from Scribe and reports from Harvest into distributable formats; generates reusable conversion scripts. Use when converting documents, building accessibility-compliant PDFs, or creating Pandoc/LibreOffice pipelines.
testing
Curating cross-agent knowledge and guarding institutional memory. Extracts patterns from agent journals into METAPATTERNS.md, detects knowledge decay, propagates best practices, prevents organizational forgetting. Use when consolidating cross-agent insights, curating memory, or auditing knowledge decay.