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 seaworld008/Commonly-used-high-value-skills --skill firebase-security-rules-auditorgit clone --depth 1 https://github.com/seaworld008/Commonly-used-high-value-skillsWrote 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/seaworld008/commonly-used-high-value-skills/firebase-security-rules-auditor)<a href="https://agentmods.dev/skills/seaworld008/commonly-used-high-value-skills/firebase-security-rules-auditor"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/firebase-security-rules-auditor/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/seaworld008/commonly-used-high-value-skills/firebase-security-rules-auditor"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/firebase-security-rules-auditor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 82 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00034 | $0.01459 |
| Opus 5 | $0.00017 | $0.00730 |
| Sonnet 5 | $0.00007 | $0.00292 |
| Haiku 4.5 | $0.00003 | $0.00146 |
Grade A, and why
firebase-security-rules-auditor 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 4d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
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.
Scoring Criteria
Assessment: Security Validator (Red Team Edition)
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.
Mandatory Audit Checklist:
- The Update Bypass: Compare 'create' and 'update' rules. Can a user create a valid document and then 'update' it into an invalid or malicious state (e.g., changing their role, bypassing size limits, or corrupting data types)?
- Authority Source: Does the security rely on user-provided data (request.resource.data) for sensitive fields like 'role', 'isAdmin', or 'ownerId'? Carefully consider the source for that authority.
- Business Logic vs. Rules: Does the rule set actually support the app's purpose? (e.g., In a collaboration app, can collaborators actually read the data? If not, the rules are "broken" or will force insecure workarounds).
- Storage Abuse: Are there string length or array size limits? If not, label it as a "Resource Exhaustion/DoS" risk.
- Type Safety: Are fields checked with 'is string', 'is int', or 'is timestamp'?
- Field-Level vs. Identity-Level Security: Be careful with rules that use `hasOnly()` or `diff()`. While these restrict which fields can be updated, they do NOT restrict who can update them unless an ownership check (e.g., `resource.data.uid == request.auth.uid`) is also present. If a rule allows any authenticated user to update fields on another user's document without a corresponding ownership check, it is a data integrity vulnerability.
Admin Bootstrapping & Privileges:
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:
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.
- 4d ago Changed · -34 tokens per session de6dfa3b8dbe
- 8d ago First seen · 141 lines · 68 tokens per session scan A 91b3a59f6e98
firebase-security-rules-auditor is a skill published in the GitHub repository seaworld008/Commonly-used-high-value-skills (70 stars, last pushed 4d ago), licensed MIT. It adds 34 tokens to every session and 1,459 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.
Other skills, from other repositories
read-only-postgres
Execute read-only SQL queries against PostgreSQL databases. Use when: (1) querying PostgreSQL data, (2) exploring schemas/tables, (3) running SELECT queries for analysis, (4) checking database contents. Supports multiple database connections with descriptions for auto-selection. Blocks all write operations (INSERT…
supabase
Run Supabase Management API SQL for persistent data tasks such as querying records, applying schema changes, managing policies, and handling storage metadata. Use when requests involve Supabase database CRUD, migrations, or production-like data inspection.
database-expert
Advanced database design and administration for PostgreSQL, MongoDB, and Redis. Use when designing schemas, optimizing queries, managing database performance, or implementing data patterns.
clickhouse-architect
ClickHouse schema design and optimization. TRIGGERS - ClickHouse schema, compression codecs, MergeTree, ORDER BY tuning, partition key.
imessage-query
Query macOS iMessage database (chat.db) via SQLite. Decode NSAttributedString messages, handle tapbacks, search conversations.
backtesting-py-oracle
Configuration and anti-patterns for using backtesting.py to validate ClickHouse SQL sweep results. Ensures bit-atomic replicability between SQL and Python trade evaluation.