# brainstorming-studio > # 🧠 Skill Router (Skill Orchestrator) **An explainable, deterministic meta-skill that decides _which_ skill to use, _how_ to use it, and _whether_ it is safe — before anything runs.** Skill Router operates as a **decision and governance layer above all other skills**. It inventories available skills, scores them transparently, applies safety gates, and orchestrates the optimal execution strategy — always with user visibility and control. > **No black boxes. No silent execution. No hallucinat... - Author: Adam Delisi - Repository: massiveadam/skills - Version: 20260131183437 - Stars: 0 - Forks: 0 - Last Updated: 2026-02-06 - Source: https://github.com/massiveadam/skills - Web: https://mule.run/skillshub/@@massiveadam/skills~brainstorming-studio:20260131183437 --- # 🧠 Skill Router (Skill Orchestrator) **An explainable, deterministic meta-skill that decides _which_ skill to use, _how_ to use it, and _whether_ it is safe — before anything runs.** Skill Router operates as a **decision and governance layer above all other skills**. It inventories available skills, scores them transparently, applies safety gates, and orchestrates the optimal execution strategy — always with user visibility and control. > **No black boxes. No silent execution. No hallucinated APIs.** --- ## 🚀 How to Run (Trigger Phrases) Invoke the Skill Router using natural language: - decide which skill to use - use the best skill for this - route this task automatically - orchestrate my skills - figure out the optimal approach - handle this in the most efficient way - skill router: - orchestrator: --- ## ✅ Checklist — Step by Step ### Step 0 — Task Intake & Normalization - Capture the raw user request verbatim. - Normalize into: - **Goal** — what success looks like - **Constraints** — hard requirements and prohibitions - **Urgency** — LOW / MEDIUM / HIGH - **Environment** — OS, local vs remote, runtime limits - **Risk profile** — LOW / MEDIUM / HIGH / CRITICAL - Identify required actions: - read, write, execute, network, credentials - Detect missing information and mark explicitly. - Never guess missing data. --- ### Step 1 — Skill Inventory - Attempt to list installed skills using official platform APIs. - If unavailable, fall back to: - Directory scanning - Skill manifests (skill.json, manifest.json) - Normalize each skill into: ```json { "id": "string", "name": "string", "description": "string", "supported_actions": [], "required_permissions": [], "risk_level": "LOW | MEDIUM | HIGH | CRITICAL", "cost_latency": { "estimated_ms": 0, "cost_hint": "FREE | LOW | MED | HIGH" }, "failure_modes": [] } If inventory is partial or empty, continue in best-effort / plan-only mode. Step 2 — Task Classification Classify into one or more: Planning / Writing Coding / DevOps Filesystem Operations Security / Auditing Data / Analysis Web / Research Automation Ideation / Brainstorming Identify disallowed actions (e.g. “no internet”, “read-only”). Step 3 — Skill Scoring Model (0–100) Component Weight Task Relevance 0–40 Environment Compatibility 0–15 Permission Fit 0–10 Latency & Cost Efficiency 0–10 Risk Alignment 0–15 Historical Success (local) 0–10 Formula Score = R + E + P + C + A + H Hard Gates Disallowed actions → score = 0 CRITICAL risk mismatch → score capped at 25 unless overridden Step 4 — Strategy Selection Choose exactly one: Single-skill execution Multi-skill pipeline Clarifying question (max 1–2) All decisions are justified. Step 5 — Safety Gates Risk ≥ HIGH → confirmation required Filesystem / Network / Credentials → preview required External APIs → data disclosure + consent Missing permissions → degrade or abort safely Step 6 — Execution & Fallback Execute selected skill(s). On failure: Analyze error Retry with next-best candidate (max 2 attempts) Never escalate risk without new confirmation. Step 7 — Reporting & Learning Generate a structured report. Optionally store a local-only history record. Secrets are always redacted. 📊 Output Format (STRICT) 🧠 Skill Router Report 1. Task Analysis — 2. Skill Candidates — 3. Selection Strategy — 4. Safety Check — 5. Execution Result — 6. Fallback Handling — 7. Learning Log — Scoreboard: Primary: XX/100 Alternative: YY/100 Icons: ✅ PASS ⚠️ WARN ❌ FAIL 🛑 CONFIRM ⏭️ SKIP 🔁 Auto-Action Flow Always display the report first. If confirmation is required, ask: Proceed? (yes / no / pick) yes → execute no → abort pick → user selects skills or steps 🧩 Action Recipes Listing Skills (No API) Scan directories Parse manifests Never infer capabilities Force a Specific Skill override router: Full safety gates still apply Disable a Skill Add to local denylist Excluded from scoring Dry-Run Mode Perform Steps 0–5 only No execution Verbose Diagnostics Full scoring breakdown Inventory source Redaction log Reset History Clears local history only 🧠 Extension Module — Brainstorming Mode (Optional) Multi-Agent Brainstorming Orchestrator: Business / Strategy Agent Market / Execution Agent Rounds: Idea generation Critique & risk Synthesis Requires explicit consent before external API usage. 🔒 Safety & Guarantees No destructive actions without confirmation No silent data exfiltration No automatic skill installation No permission bypass No hallucinated APIs 🚫 What This Skill Does NOT Do Does not replace human judgment Does not train ML models Does not auto-install dependencies Does not bypass permissions 📚 Reference & Rationale Skill Router introduces a deterministic, auditable decision layer for agent skills. It improves: Safety Reliability User trust Execution success rates This is governance for agent skills — done right. --- # ✅ 2️⃣ RESULTADO ✔️ Cria o arquivo **SKILL.md** ✔️ Encoding **UTF-8** ✔️ 100% compatível com **ClawHub / GitHub / GitLab** ✔️ Visual premium (headings, tabelas, blocos, ícones) --- ## 🔥 Próximo passo (se quiser) Posso: - Ajustar para **rating máximo no review ClawHub** - Gerar `README.md` (marketing) - Criar `CONTRIBUTING.md` - Criar checklist de aprovação - Revisar linguagem para **nível enterprise** Só mandar 🚀