ai-tool-compliance

supercent-io/skills-template · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/supercent-io/skills-template --skill ai-tool-compliance
0 commentsdiscussion
summary

Automated compliance verification and enforcement for AI tools against 11 mandatory P0 rules covering auth, security, cost tracking, and logging.

  • Verifies 11 P0 rules across four domains (Security 40pts, Auth 25pts, Cost 20pts, Logging 15pts) with quantitative compliance scoring and deploy gate verdicts (Green/Yellow/Red)
  • Three execution modes: quick static scan via grep/glob patterns, full verification with evidence collection, and guided improvement with fix suggestions and re-verific
skill.md

ai-tool-compliance - Internal AI Tool Compliance Automation

When to use this skill

  • Starting a new AI project: When scaffolding the compliance foundation (RBAC, Gateway, logs, cost tracking) from scratch
  • Pre-deploy P0 full verification: When automatically evaluating all 13 P0 mandatory requirements as pass/fail and computing a compliance score
  • RBAC design and permission matrix generation: When defining the 5 roles (Super Admin/Admin/Manager/Viewer/Guest) + granular access control per game/menu/feature unit
  • Auditing existing code for compliance: When inspecting an existing codebase against the guide and identifying violations
  • Implementing cost transparency: When building a tracking system for model/token/BQ scan volume/cost per action
  • Designing a behavior log schema: When designing a comprehensive behavior log recording system (Firestore/BigQuery)
  • Role-based verification workflow: When configuring the release approval process based on Section 14 (ServiceStability/Engineer/PM/CEO)
  • Building a criteria verification system: When setting up the Rule Registry + Evidence Collector + Verifier Engine + Risk Scorer + Gatekeeper architecture

Installation

npx skills add https://github.com/supercent-io/skills-template --skill ai-tool-compliance

Quick Reference

Action Command Description
Project initialization /compliance-init Generate RBAC matrix, Gateway boilerplate, log schema, cost tracking interface
Quick scan /compliance-scan, /compliance-quick, /quick Quick inspection of P0 key items (code pattern-based)
Full verification /compliance-verify, /compliance-full, /full Full verification of 11 P0 rules + compliance score computation
Score check /compliance-score Display current compliance score (security/auth/cost/logging)
Deploy gate /compliance-gate Green/Yellow/Red verdict + deploy approve/block decision
Improvement guide /compliance-improve, /improve Specific fix suggestions per violation + re-verification loop

Slash Mode Router

Mode slash commands are mapped as follows.

  • /quick, /compliance-quick -> Quick Scan (/compliance-scan)
  • /full, /compliance-full -> Full Verify (/compliance-verify)
  • /improve -> Improve (/compliance-improve)

3 Execution Modes

1. Quick Scan (quick-scan)

Statically analyzes the codebase to quickly identify potential P0 violations.

How to run: /compliance-scan, /compliance-quick, /quick or trigger keywords compliance scan, quick scan

What it does:

  • Grep/Glob-based code pattern search
  • Detect direct external API calls (whether Gateway is bypassed)
  • Detect direct Firestore client access
  • Detect hardcoded sensitive data
  • Check for missing Guest role

Output: List of suspected violations (file path + line number + rule ID)

Duration: 1–3 minutes

2. Full Verify (full-verify)

Fully verifies all 11 P0 rules and computes a quantitative compliance score.

How to run: /compliance-verify, /compliance-full, /full or trigger keywords P0 verification, full verify, deploy verification

What it does:

  • Collect Evidence and evaluate pass/fail for each of the 11 P0 rules
  • Compute scores per 4 domains (Security 40pts / Auth 25pts / Cost 20pts / Logging 15pts)
  • Calculate total compliance score (out of 100)
  • Determine deploy gate grade (Green/Yellow/Red)
  • Generate role-based approval checklist

Output: Compliance report (compliance-report.md)

## Compliance Report
- Date: 2026-03-03
- Project: my-ai-tool
- Score: 92/100 (Green)

### Rule Results
| Rule ID | Rule Name | Result | Evidence |
|---------|-----------|--------|----------|
| AUTH-P0-001 | Force Guest for New Signups | PASS | signup.ts:45 role='guest' |
| AUTH-P0-002 | Block Guest Menu/API Access | PASS | middleware.ts:12 guestBlock |
| ... | ... | ... | ... |

### Score Breakdown
- Security: 33/40
- Auth: 25/25
- Cost: 17/20
- Logging: 12/15
- Total: 92/100

### Gate Decision: GREEN - Deploy Approved

Duration: 5–15 minutes (varies by project size)

3. Improve (improve)

Provides specific fix guides for violations and runs a re-verification loop.

How to run: /compliance-improve, /improve or trigger keywords compliance improvement, fix violations

What it does:

  • Code-level fix suggestions for each FAIL item (file path + before/after code)
  • Re-verify the rule after applying the fix
  • Track score changes (Before -> After)
  • Guide for gradually introducing P1 recommended requirements after passing P0

Output: Fix proposal + re-verification results

Improve Mode Auto-Fix Logic

/compliance-improve runs
       |
  1. Load latest verification-run.json
       |
  2. Extract FAIL items (rule_id + evidence)
       |
  3. For each FAIL:
       |
     a. Read violation code from evidence file:line
     b. Derive fix direction from rule.remediation + rule.check_pattern.must_contain
     c. Generate before/after code diff
     d. Apply fix via Write (after user confirmation)
     e. Re-verify only that rule (re-run Grep pattern)
     f. Confirm transition to PASS
       |
  4. Full re-verification (/compliance-verify)
       |
  5. Output Before/After score comparison
       |
  6. If no remaining FAILs → present guide for introducing P1 recommended requirements

Fix application priority:

  1. must_not_contain violations (requires immediate removal) → delete the code or replace with server API call
  2. must_contain unmet (pattern needs to be added) → insert code per the remediation guide
  3. Warning (partially met) → apply supplement only to unmet files

P0 Rule Catalog

11 P0 rules based on the internal AI tool mandatory implementation guide v1.1:

Rule ID Category Rule Name Description Score
AUTH-P0-001 Auth Force Guest for New Signups Automatically assign role=Guest on signup; elevated roles granted only via invitation Auth 8
AUTH-P0-002 Auth Block Guest Menu/API Access Do not expose tool name, model name, internal infrastructure, cost, or structure to Guest. Only allow access to permitted menus/APIs Auth 7
AUTH-P0-003 Auth Server-side Final Auth Check Server-side auth verification middleware required for all API requests. Client-side checks alone are insufficient Auth 10
SEC-P0-004 Security Prohibit Direct Firestore Access Direct read/write to Firestore from client is forbidden. Only via Cloud Functions is allowed Security 12
SEC-P0-005 Security Enforce External API Gateway Direct calls to external AI APIs (Gemini, OpenAI, etc.) are forbidden. Must route through internal Gateway (Cloud Functions) Security 18
SEC-P0-009 Security Server-side Sensitive Text Processing Sensitive raw content (prompts, full responses) is processed server-side only. Only reference values (IDs) are sent to clients Security 10
COST-P0-006 Cost Model Call Cost Log Must record model, inputTokens, outputTokens, estimatedCost for every AI model call Cost 10
COST-P0-007 Cost BQ Scan Cost Log Must record bytesProcessed, estimatedCost when executing BigQuery queries Cost 5
COST-P0-011 Cost Cache-first Lookup Cache lookup required before high-cost API calls. Actual call only on cache miss Cost 5
LOG-P0-008 Logging Mandatory Failed Request Logging Must log all failed requests (4xx, 5xx, timeout). No omissions allowed Logging 10
LOG-P0-010 Logging Auth Change Audit Log Record all auth-related events: role changes, permission grants/revocations, invitation sends Logging 5

Scoring System

Domain Max Score Included Rules
Security 40 SEC-P0-004, SEC-P0-005, SEC-P0-009
Auth 25 AUTH-P0-001, AUTH-P0-002, AUTH-P0-003
Cost 20 COST-P0-006, COST-P0-007, COST-P0-011
Logging 15 LOG-P0-008, LOG-P0-010
Total 100 11 P0 rules

Per-rule Automatic Verification Logic

Verification for each rule is performed based on the check_pattern defined in rules/p0-catalog.yaml. The core mechanism is Grep/Glob static analysis.

Verdict Algorithm (per rule):

1. Glob(check_targets) → collect target files
2. grep_patterns matching → identify files using that feature
   - 0 matches → N/A (feature not used, no penalty)
3. must_not_contain check (excluding exclude_paths)
   - Match found → immediate FAIL + record evidence
4. must_contain check
   - All satisfied → PASS
   - Partially satisfied → WARNING
   - Not satisfied → FAIL

Key Grep Patterns per Rule:

Rule ID Feature Detection (grep_patterns) Compliance Check (must_contain) Violation Detection (must_not_contain)
AUTH-P0-001 signup|register|createUser role.*['"]guest['"] role.*['"]admin['"] (on signup)
AUTH-P0-002 guard|middleware|authorize guest.*block|guest.*deny --
AUTH-P0-003 router\.(get|post|put|delete) auth|verify|authenticate --
SEC-P0-004 -- (all targets) -- firebase/firestore|getDocs|setDoc (client paths)
SEC-P0-005 -- (all targets) -- fetch\(['"]https?://(?!localhost) (client paths)
SEC-P0-009 -- (all targets) -- res\.json\(.*password|console\.log\(.*token
COST-P0-006 openai|vertexai|gemini|anthropic cost|token|usage|billing --
COST-P0-007 bigquery|BigQuery|createQueryJob totalBytesProcessed|bytesProcessed|cost --
COST-P0-011 openai|vertexai|gemini|anthropic cache|Cache|redis|memo --
LOG-P0-008 catch|errorHandler|onError logger|log\.error|winston|pino --
LOG-P0-010 updateRole|changeRole|setRole audit|auditLog|eventLog --

Detailed schema: see rules/p0-catalog.yaml and the "Judgment Algorithm" section in REFERENCE.md


Verification Scenarios (QA)

5 key verification scenarios run in Full Verify mode (/compliance-verify). Each scenario groups related P0 rules for end-to-end verification.

ID Scenario Related Rules Verification Method Pass Criteria
SC-001 New Signup -> Guest Isolation AUTH-P0-001, AUTH-P0-002 Verify role=guest assignment in signup code + confirm 403 return pattern when Guest calls protected API PASS when role is guest and access-denied pattern exists for protected API
SC-002 AI Call -> Via Gateway + Cost Logged SEC-P0-005, COST-P0-006, COST-P0-011 (1) Confirm absence of direct external API calls (2) Confirm routing via Gateway function (3) Confirm cost log fields (model, tokens, cost) recorded (4) Confirm cache lookup logic exists PASS when Gateway routing + 4 cost log fields recorded + cache layer exists
SC-003 Firestore Access -> Functions-Only SEC-P0-004, AUTH-P0-003 (1) Detect direct Firestore SDK import in client code (2) Confirm server-side auth verification middleware exists PASS when 0 direct client access instances + server middleware exists
SC-004 Failed Requests -> No Log Gaps LOG-P0-008, LOG-P0-010 (1) Confirm log call in error handler (2) Confirm no log gaps in catch blocks (3) Confirm audit log exists for auth change events PASS when all error handlers call log + auth change audit log exists
SC-005 Sensitive Data -> Not Exposed to Client SEC-P0-009, AUTH-P0-002 (1) Confirm API responses do not include raw prompts/responses, only reference IDs (2) Confirm Guest responses do not include model name/cost/infrastructure info PASS when raw content not in response + Guest exposure control confirmed

Verification Flow by Scenario

SC-001: grep signup/register -> assert role='guest' -> grep guestBlock/guestDeny -> assert exists
SC-002: grep fetch(https://) in client -> assert 0 hits -> grep gateway log -> assert cost fields -> assert cache check
SC-003: grep firebase/firestore in client/ -> assert 0 hits -> grep authMiddleware in functions/ -> assert exists
SC-004: grep catch blocks -> assert logAction in each -> grep roleChange -> assert auditLog
SC-005: grep res.json for raw text -> assert 0 hits -> grep guest response -> assert no model/cost info

Role-based Go/No-Go Checkpoints

After the deploy gate verdict, the role's Go/No-Go checkpoints must be cleared based on the grade. 4 roles × 5 items = 20 checkpoints total.

Service Stability (5 items)

# Checkpoint Go Condition No-Go Condition
1 SLA Impact Analysis Confirmed no impact on existing service availability/response-time SLA SLA impact unanalyzed or degradation expected
2 Rollback Procedure Rollback procedure documented + tested Rollback procedure not established
3 Performance Test Load/stress test completed + within threshold Performance test not run
4 Incident Alerts Incident detection alert channels (Slack/PagerDuty, etc.) configured Alert channels not configured
5 Monitoring Dashboard Dashboard for key metrics (error rate, response time, AI cost) exists Monitoring absent

Engineer (5 items)

# Checkpoint Go Condition No-Go Condition
1 FAIL Rule Root Cause Analysis Root cause identified + documented for all FAIL rules Unidentified items exist
2 Fix Code Verification Fixed code accurately reflects the intent of the rule Fix does not match rule intent
3 Re-verification Pass Rule transitions to PASS in re-verification after fix Re-verification not run or still FAIL
4 No Regression Impact Fix confirmed to have no negative impact on other P0 rules Another rule newly FAILs
5 Code Review Done Code review approval completed for fixed code Code review not completed

PM (5 items)

# Checkpoint Go Condition No-Go Condition
1 User Impact Assessment User impact of non-compliant items is acceptable User impact not assessed
2 Schedule Risk Fix timeline is within release schedule Schedule overrun expected
3 Scope Agreement Stakeholder agreement completed for scope changes Agreement not reached
4 Cost Impact AI usage cost within approved budget Budget overrun expected
5 Communication Changes shared with relevant teams Not shared

CEO (5 items)

# Checkpoint Go Condition No-Go Condition
1 Cost Cap Monthly AI cost within pre-approved budget Budget cap exceeded
2 Security Risk All security P0 passed or exception reason is reasonable P0 security FAIL + insufficient exception justification
3 Legal/Regulatory Risk Data processing complies with applicable laws (privacy laws, etc.) Legal risks not reviewed
4 Business Continuity Business impact is limited if deployment fails Business disruption risk exists
5 Final Approval Final approval when all 4 above are Go Deferred if even 1 is No-Go

Report Format

compliance-report.md, generated when /compliance-verify runs, consists of 6 sections.

Report Section Structure (6 sections)

# Compliance Report

## 1. Summary
- Project name, verification date/time, verification mode (quick-scan / full-verify)
- Total compliance score / 100
- Deploy gate grade (Green / Yellow / Red)
- P0 FAIL count
- Verification duration

## 2. Rule Results
| Rule ID | Category | Rule Name | Result | Score | Evidence |
|---------|----------|
how to use ai-tool-compliance

How to use ai-tool-compliance on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add ai-tool-compliance
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/supercent-io/skills-template --skill ai-tool-compliance

The skills CLI fetches ai-tool-compliance from GitHub repository supercent-io/skills-template and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/ai-tool-compliance

Reload or restart Cursor to activate ai-tool-compliance. Access the skill through slash commands (e.g., /ai-tool-compliance) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.533 reviews
  • Mia Johnson· Dec 16, 2024

    I recommend ai-tool-compliance for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Ganesh Mohane· Dec 4, 2024

    Solid pick for teams standardizing on skills: ai-tool-compliance is focused, and the summary matches what you get after install.

  • Benjamin Okafor· Dec 4, 2024

    Registry listing for ai-tool-compliance matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Sakshi Patil· Nov 23, 2024

    We added ai-tool-compliance from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Benjamin Tandon· Nov 23, 2024

    Useful defaults in ai-tool-compliance — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Mia Garcia· Nov 7, 2024

    ai-tool-compliance reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Naina Choi· Nov 3, 2024

    ai-tool-compliance is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Neel Sharma· Oct 22, 2024

    Keeps context tight: ai-tool-compliance is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Chaitanya Patil· Oct 14, 2024

    ai-tool-compliance fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Arya Jackson· Oct 14, 2024

    I recommend ai-tool-compliance for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

showing 1-10 of 33

1 / 4