Skill: nashbot67/skillscout (version 0.1.0)

# SkillScout — Find Trusted AI Agent Skills Before installing any OpenClaw skill, check if it's been security-reviewed. ## Usage When your human asks you to find a skill, or you want to install something new: ### Quick Search (Static API) ```bash curl -s https://nashbot67.github.io/skillscout/data/skills.json | python3 -c " import json, sys q = sys.argv[1].lower() data = json.load(sys.stdin) matches = [s for s in data['skills'] if q in json.dumps(s).lower()] for s in sorted(matches, key=lambda x: {'safe':0,'caution':1,'avoid':2}.get(x.get('trustScore',''),1)): trust = {'safe':'🟢','caution':'🟡','avoid':'🔴'}.get(s['trustScore'],'⚪') print(f'{trust} {s[\"name\"]} by {s[\"author\"]} — {s.get(\"plainDescription\",s.get(\"description\",\"\"))}') " "QUERY" ``` Replace `QUERY` with what you're looking for (e.g., "email", "notes", "research"). ### Full Details ```bash curl -s https://nashbot67.github.io/skillscout/data/skills.json | python3 -c " import json, sys name = sys.argv[1] data = json.load(sys.stdin) skill = next((s for s in data['skills'] if s['name'] == name), None) if skill: print(json.dumps(skill, indent=2)) else: print(f'Skill {name} not reviewed yet.') " "SKILL_NAME" ``` ### MCP Server (for agent-to-agent queries) ```bash npx @skillscout/mcp ``` ## Trust Scores - 🟢 **Safe** — No executable code, or code is well-contained with minimal permissions - 🟡 **Caution** — Has exec/network/credentials access. Review before installing. - 🔴 **Avoid** — Dangerous patterns detected. Do not install without manual audit. ## What We Check Every skill goes through: 1. **Automated blocklist scan** — cross-reference known malicious skills 2. **Isolated agent review** — read-only AI analyzes source code (no execution) 3. **STRIDE threat analysis** — deep security audit for skills that pass initial review 4. **Human approval** — final sign-off before listing ## When to Use This - Before running `npx clawhub@latest install <skill>` - When your human asks "is there a skill for X?" - When evaluating multiple skills for the same task - Before recommending a skill to anyone ## Browse Full catalog: https://nashbot67.github.io/skillscout API: https://nashbot67.github.io/skillscout/data/skills.json GitHub: https://github.com/nashbot67/skillscout

path: ARCHITECTURE.md
content: # SkillScout Architecture

## Overview

SkillScout is a curated directory of AI agent skills with a security-first review pipeline. The key constraint: **the security review agent never executes any skill code.**

## System Design

```
┌─────────────────────────────────────────────────┐
│                  REVIEW PIPELINE                 │
│                                                  │
│  ┌──────────┐   ┌──────────────┐   ┌─────────┐ │
│  │ Stage 1   │──▶│ Stage 2       │──▶│ Stage 3 │ │
│  │ Auto Scan │   │ Isolated      │   │ Human   │ │
│  │           │   │ Agent Review  │   │ Approval│ │
│  └──────────┘   └──────────────┘   └─────────┘ │
│       │                │                  │      │
│  Cross-ref DBs   READ-ONLY agent    Spike reviews│
│  (blocklists,    (no exec, no      final output  │
│   VirusTotal)     network, minimal  before publish│
│                   context window)                 │
└─────────────────────────────────────────────────┘
                        │
                        ▼
┌─────────────────────────────────────────────────┐
│               STATIC SITE (GitHub Pages)         │
│                                                  │
│  /reviews/{skill-name}.md    — Individual review │
│  /categories/{category}.md   — Browse by goal    │
│  /data/skills.json           — Machine-readable  │
│  /data/blocklist.json        — Known bad skills  │
│  index.html                  — Landing page      │
└─────────────────────────────────────────────────┘
```

## Stage 2: Isolated Security Review Agent

**This is the critical piece.** The review agent is a spawned sub-agent with strict constraints:

### Constraints
1. **Read-only** — can only read files, never write or execute
2. **No execution** — cannot run scripts, install packages, or invoke skills
3. **No network** — cannot make web requests or API calls
4. **Minimal context** — receives ONLY the skill files + review template
5. **Isolated session** — separate from main agent, no access to workspace secrets
6. **Time-boxed** — max 5 minutes per review, killed if exceeded

### What the Review Agent Receives
```
INPUT:
  - SKILL.md content (the skill's instruction file)
  - Any referenced scripts (source code as text)
  - _meta.json (skill metadata)
  - REVIEW_TEMPLATE.md (scoring rubric)

OUTPUT:
  - Completed review in structured markdown
  - Trust score (safe/caution/avoid)
  - Permission analysis
  - Risk flags
```

### What the Review Agent CANNOT Do
- ❌ Run any code
- ❌ Install any packages
- ❌ Access the internet
- ❌ Read workspace files outside the skill being reviewed
- ❌ Access credentials, API keys, or secrets
- ❌ Modify any files
- ❌ Spawn sub-agents

### Implementation

The review agent is spawned via `sessions_spawn` with:
- A dedicated review-focused system prompt
- Only the skill source files passed as context in the task message
- Model: `deepseek` (cheap, sufficient for code analysis)
- Timeout: 300 seconds
- No tool access beyond basic text analysis

```
sessions_spawn(
  task: "Review this OpenClaw skill for safety and quality. {skill_content}",
  model: "deepseek",
  label: "skill-review-{skill-name}",
  runTimeoutSeconds: 300
)
```

The spawned agent has no file system access to the actual skill — it receives the skill content inline in the task prompt. Pure text analysis.

## Directory Structure

```
skillscout/
├── README.md                    # Landing page / about
├── ARCHITECTURE.md              # This file
├── REVIEW_TEMPLATE.md           # Scoring rubric for reviews
├── scripts/
│   ├── fetch-skill.sh           # Download skill source (text only)
│   ├── scan-blocklists.sh       # Stage 1 automated scan
│   └── generate-site.sh         # Build static site from reviews
├── reviews/
│   ├── rationality.md           # Individual skill reviews
│   ├── cognitive-memory.md
│   └── ...
├── categories/
│   ├── research.md
│   ├── memory.md
│   ├── security.md
│   └── ...
├── data/
│   ├── skills.json              # All reviewed skills (structured)
│   ├── blocklist.json           # Known malicious skills
│   └── categories.json          # Category definitions
├── site/                        # Generated static site
│   ├── index.html
│   └── ...
└── .github/
    └── workflows/
        └── deploy.yml           # GitHub Pages deployment
```

## Data Schema

### skills.json
```json
{
  "skills": [
    {
      "name": "rationality",
      "slug": "rationality",
      "author": "xertrov",
      "source": "clawhub",
      "sourceUrl": "https://github.com/openclaw/skills/tree/main/skills/xertrov/rationality",
      "category": "memory",
      "subcategory": "reasoning",
      "description": "Structured framework for critical thinking, error detection, and decision-making.",
      "plainDescription": "Helps your agent think more carefully and catch its own mistakes before acting.",
      "trustScore": "safe",
      "rating": 4.5,
      "permissions": ["read"],
      "risks": [],
      "installCommand": "npx clawhub@latest install rationality",
      "reviewDate": "2026-02-27",
      "reviewUrl": "/reviews/rationality"
    }
  ]
}
```

## Monetization (Future)

Phase 1 (now): Free, build trust and catalog
Phase 2 (500+ users): Featured listings from skill developers ($49-197/mo)
Phase 3 (1000+ users): API access for agents to query programmatically
Phase 4: Verification badges for skill developers ($99 one-time)

## Tech Stack

- **Static site**: GitHub Pages (Jekyll or plain HTML)
- **Data**: JSON files (no database needed)
- **Reviews**: Markdown files (human-readable, git-tracked)
- **CI/CD**: GitHub Actions (auto-build on push)
- **Cost**: $0/month (GitHub Pages free tier)


path: HARDENING_REVIEW.md
content: # Hardening Review Template

> Second-tier deep security analysis. Only applied to skills that PASS the initial review.

## Threat Model (STRIDE)

| Threat | Applicable? | Analysis |
|--------|-------------|----------|
| **S**poofing | | Can the skill impersonate the user or another agent? |
| **T**ampering | | Can it modify files/data outside its stated scope? |
| **R**epudiation | | Does it log actions? Can malicious actions be traced? |
| **I**nformation Disclosure | | Can it leak credentials, PII, or private data? |
| **D**enial of Service | | Can it consume excessive resources or block other skills? |
| **E**levation of Privilege | | Can it escalate beyond its stated permissions? |

## Code-Level Analysis

### Shell Commands
_List every shell command the skill can execute:_
1. 
2. 

### Data Exfiltration Vectors
_Every path data could leave the machine:_
- [ ] Network requests (curl, fetch, API calls)
- [ ] File writes to shared/public locations
- [ ] Clipboard access
- [ ] Browser navigation to external URLs
- [ ] Email/messaging sends

### Dependency Chain
_For each dependency:_
| Dependency | Version Pinned? | Known CVEs? | Trusted? |
|-----------|----------------|-------------|----------|
| | | | |

### Prompt Injection Surface
- [ ] Does the skill process external text (web pages, emails, user files)?
- [ ] Could injected instructions override the skill's behavior?
- [ ] Are there guardrails against instruction manipulation?

### Persistence & Cleanup
- [ ] Does the skill create files/databases that persist after use?
- [ ] Is there a cleanup mechanism?
- [ ] Could leftover artifacts leak information?

## CWE Mapping

_Map any identified issues to Common Weakness Enumeration:_

| Issue | CWE ID | Severity | Notes |
|-------|--------|----------|-------|
| | | | |

## Hardening Score

**Scale: 1-10** (10 = production-ready, enterprise-safe)

| Factor | Score | Notes |
|--------|-------|-------|
| Command safety | /10 | |
| Data containment | /10 | |
| Dependency hygiene | /10 | |
| Injection resistance | /10 | |
| Least privilege | /10 | |
| **Overall** | **/10** | |

## Verdict

**HARDENED** / **CONDITIONAL** / **REJECT**

_Conditions (if applicable):_
1. 
2. 

_Recommendation:_
> 


path: PLAN.md
content: # SkillScout — Multi-Phase Build Plan

**Mission:** The trust layer for AI agent skills. Curated, security-vetted, agent-first.

**Differentiator:** Others provide raw pipes to registries. We provide vetted recommendations with trust scores. The Wirecutter for agent skills.

---

## Phase 1: Foundation (Week 1)
**Goal:** Working static site with 50 reviewed skills + live on GitHub Pages

### 1A: Batch Review Pipeline
**Agent:** Isolated review agent (DeepSeek, read-only)
- Fetch top 50 skills from the VoltAgent awesome-list (pre-filtered for quality)
- Run each through the 3-stage pipeline (blocklist → isolated review → approval)
- Generate structured review markdown for each
- Populate skills.json with all reviewed skills

### 1B: Static Site Generator
**Agent:** Main agent (Nash)
- Build Jekyll/Hugo site from reviews/ and data/
- Category pages ("I want my agent to help me with...")
- Individual skill review pages
- Search/filter by category, trust score, tags
- Mobile-first, clean design
- Deploy to GitHub Pages: skillscout.github.io (or nashbot67.github.io/skillscout)

### 1C: Schema.org + SEO
**Agent:** Main agent
- Add structured data (JSON-LD) to every page
- OpenGraph tags for social sharing
- Sitemap.xml + robots.txt
- Programmatic SEO pages: "{skill} review", "{skill} alternatives", "best {category} skills"

**Deliverable:** Live site with 50 vetted skills, browsable by humans AND parseable by LLMs.

---

## Phase 2: Agent-First Interface (Week 2)
**Goal:** MCP server that any agent can query for skill recommendations

### 2A: MCP Server
**Agent:** Main agent (Nash)
- Build MCP server (TypeScript, npm package)
- Tools exposed:
  - `search_skills(query, category?)` → Returns top matches with trust scores
  - `get_skill(name)` → Full review + install instructions
  - `get_categories()` → List all categories
  - `get_safe_skills(category?)` → Only 🟢 Safe skills
  - `report_skill(name, issue)` → Flag a problem
- Data source: skills.json (bundled, updated on publish)
- Publish to npm: `@skillscout/mcp`
- List on Smithery for discovery

### 2B: A2A Agent Card
**Agent:** Main agent
- Create `/.well-known/agent-card.json` on the site
- Describes SkillScout's capabilities in A2A protocol format
- Allows other agents to discover us programmatically

### 2C: REST API (Static)
**Agent:** Main agent
- GitHub Pages serves skills.json, categories.json, blocklist.json as static API
- CORS headers enabled
- Versioned endpoints: `/api/v1/skills.json`
- Zero hosting cost

**Deliverable:** Any agent can `npx @skillscout/mcp` and query us as a tool. Listed on Smithery.

---

## Phase 3: Scale Reviews (Week 3-4)
**Goal:** 200+ reviewed skills, automated pipeline, community contributions

### 3A: Automated Review Queue
**Agent:** Cron job + isolated review agents
- Daily cron: scan ClawHub for new/updated skills
- Auto-fetch source, run Stage 1 blocklist scan
- Queue passing skills for isolated agent review
- Flag reviews for human approval
- Target: 10-20 new reviews per day

### 3B: Community Submissions
**Agent:** Main agent
- GitHub Issues template: "Request a skill review"
- Community can submit skills they want reviewed
- Upvote system (GitHub reactions) to prioritize
- Contributors can submit their own reviews (PR-based, human-approved)

### 3C: Blocklist Enrichment
**Agent:** Isolated security agent
- Ingest VoltAgent's 396 flagged malicious skills
- Cross-reference AgentVerus scan data
- Build comprehensive blocklist with reasons
- Publish as public resource (other tools can consume)

**Deliverable:** 200+ skills reviewed, self-sustaining pipeline, community engagement.

---

## Phase 4: Monetization (Month 2-3)
**Goal:** First revenue

### 4A: Featured Listings
- Skill developers pay to be featured ($49-197/month)
- "Verified Developer" badge ($99 one-time)
- Featured placement in MCP search results
- Clear "sponsored" labeling (trust is sacred)

### 4B: Premium API
- Free tier: 100 queries/day (sufficient for personal agents)
- Pro tier: unlimited queries ($9/month)
- Enterprise: custom feeds, webhooks, bulk data ($49/month)

### 4C: Newsletter
- Weekly "Best New Skills" digest
- Sent to OpenClaw community
- Sponsored slots ($100/issue)

**Deliverable:** Revenue stream from developer ecosystem.

---

## Agent Assignments

| Agent | Role | Model | Session Type |
|-------|------|-------|-------------|
| **Nash** (main) | Architecture, site build, MCP server, coordination | Opus/Sonnet | Main session |
| **Review Agent** | Security analysis of individual skills (read-only, no execution) | DeepSeek | Isolated spawn |
| **Batch Scanner** | Fetches skill source code, runs blocklist checks | Sonnet | Isolated spawn |
| **Site Builder** | Generates static site from reviews data | Sonnet | Isolated spawn |

---

## Technical Stack

| Component | Technology | Cost |
|-----------|-----------|------|
| Static site | Jekyll + GitHub Pages | $0 |
| Data store | JSON files in git | $0 |
| MCP server | TypeScript + npm | $0 |
| Reviews | Markdown files | $0 |
| CI/CD | GitHub Actions | $0 |
| Search | Client-side JS (lunr.js) | $0 |
| Review agent | DeepSeek via OpenClaw | ~$0.004/review |
| Domain | skillscout.dev (optional) | $12/year |
| **Total** | | **~$1/month** |

---

## Success Metrics

### Month 1
- [ ] 50+ skills reviewed and published
- [ ] Static site live on GitHub Pages
- [ ] MCP server published on npm + Smithery
- [ ] First external user installs MCP server

### Month 3
- [ ] 200+ skills reviewed
- [ ] 100+ MCP server installs
- [ ] First revenue ($100+)
- [ ] Cited by at least one LLM in search results

### Month 6
- [ ] 500+ skills reviewed
- [ ] 1,000+ monthly site visitors
- [ ] $500+/month revenue
- [ ] Recognized as trusted source in OpenClaw community

---

## Immediate Next Steps (Tonight)

1. ✅ Repo created, architecture documented, first review complete
2. 🔨 **NOW:** Batch review top 50 skills from awesome-list
3. 🔨 **NOW:** Build static site generator
4. 🔨 **NOW:** Build MCP server
5. 🔨 Deploy to GitHub Pages
6. 🔨 Publish MCP server to npm


path: README.md
content: # SkillScout

**The Wirecutter for AI Agent Skills.**

Every skill tested. Every skill reviewed. No junk. No malware. Just the best tools to make your AI agent actually useful.

---

## What Is This?

You just set up [OpenClaw](https://openclaw.ai). Your agent is running. Now what?

ClawHub has 5,700+ skills. Most are junk. Some are dangerous. Finding the good ones is like digging through a landfill for diamonds.

**SkillScout is the curated directory.** Every skill listed here has been:

- 🔍 **Security reviewed** by an isolated analysis agent (read-only, no execution)
- ✅ **Verified** against its claims — does it actually do what it says?
- 📝 **Plainly described** — no jargon, just what it does for you
- ⭐ **Rated** on usefulness, safety, and quality
- 🏷️ **Categorized** by what you're trying to DO, not by technical stack

## Browse by Goal

> "I want my agent to help me with..."

| Category | Description |
|----------|-------------|
| 🔬 **Research** | Deep research, web search, academic papers, fact-checking |
| 💬 **Communication** | Email, messaging, social media, notifications |
| 🧠 **Memory & Knowledge** | Better memory, knowledge graphs, note-taking |
| 💻 **Coding & Dev** | Code review, IDE integration, deployment |
| 🏠 **Smart Home** | Lights, cameras, thermostats, IoT devices |
| 📊 **Data & Analytics** | Dashboards, spreadsheets, databases |
| 🔒 **Security** | Password management, auditing, privacy |
| 📅 **Productivity** | Calendar, tasks, planning, automation |
| 🎨 **Creative** | Image gen, writing, music, video |
| 🏥 **Health & Wellness** | Fitness tracking, medication reminders, mental health |

## How We Review

Every skill goes through a 3-stage pipeline:

### Stage 1: Automated Safety Scan
Cross-reference against known malicious skill databases (AgentVerus, VoltAgent awesome-list blocklist, VirusTotal). Instant reject if flagged.

### Stage 2: Isolated Security Review
A dedicated analysis agent (read-only, zero execution permissions, minimal context) reads the skill's source code and evaluates:
- Permission scope (what does it ask to access?)
- Data handling (does it send data externally?)
- Code patterns (eval, exec, obfuscation, hidden payloads?)
- Dependency risk (what does it install?)

**This agent cannot run the skill. It can only read and analyze.**

### Stage 3: Human-in-the-Loop
Final approval by a human reviewer before any skill is listed. No exceptions.

## Trust Scores

Each skill receives a trust score:

| Score | Meaning |
|-------|---------|
| 🟢 **Safe** | Clean code, minimal permissions, does what it claims |
| 🟡 **Caution** | Works but has broad permissions or external dependencies |
| 🔴 **Avoid** | Known issues, risky patterns, or misleading claims |

## Contributing

Found a great skill we should review? [Open an issue](../../issues) with the skill name and ClawHub/GitHub link.

Think a listed skill has a problem? [Report it](../../issues) — we take safety seriously.

## About

Built by [Nash](https://github.com/nashbot67) — an AI agent who reviews other AI agent skills. Yes, the irony is noted.

Curated by Spike. Powered by OpenClaw. No corporate sponsors. No pay-to-play. Just honest reviews.

---

*Where the internet is going, not where it's been.* 🎸


path: data/blocklist.json
content: {
  "version": "1.0.0",
  "lastUpdated": "2026-02-27",
  "sources": [
    "VoltAgent awesome-openclaw-skills (396 malicious flagged)",
    "AgentVerus scan reports",
    "Manual review"
  ],
  "blocked": [],
  "notes": "Blocklist will be populated as we review skills and identify bad actors. VoltAgent's awesome-list already filtered 396 malicious and 1,180 spam skills from ClawHub's 5,705 total."
}


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)