Agent routing advisor

Skill tomas-rampas/agentic-framework/skills/agent-routing-advisor

Recommends which framework agent (or multi-agent workflow) should handle a task; use when the user asks which agent to use, how to delegate a piece of work, or how to sequence agents for a multi-domain task.From its SKILL.md

Install

npx -y skills add tomas-rampas/agentic-framework --skill agent-routing-advisor

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

12 stars12 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

7.3 KB, as published. Nobody here has run it

Agent Routing Advisor

Analyze a task and recommend the right agent(s) from this framework's roster, plus a delegation prompt and workflow sequence. Recommendations must reflect the registry (claude.json), never memory or legacy docs.

Ground Truth First

The roster lives in the registry (claude.json) under .sub_agents; each agent's definition is agents/<name>.md; canonical categories are in .agent_categories.
Before recommending an agent, verify it exists in the registry. Never invent agent names. There is no "backend-expert" — backend/API work routes to the language expert matching the stack (csharp-expert, go-expert, python-expert, typescript-expert, java-expert, rust-expert).
If the stack is unknown, inspect the repository (build files, extensions) or ask before picking a language expert.

Canonical Categories

Category	Agents	Route here when
language_experts	rust-expert, csharp-expert, go-expert, java-expert, python-expert, typescript-expert, mql-trading-dev	Implementation in a specific language/stack, including backend/API work
automation_experts	bash-expert, powershell-expert	Long, output-heavy shell runs (selective policy — short commands run inline), shell scripting, OS automation
domain_specialists	database-specialist, frontend-specialist, security-specialist, uiux-specialist	Schema/query work, UI components, security audits, UX/accessibility
infrastructure_operations	devops-orchestrator	CI/CD, containers, IaC, deployment
architecture_planning	system-architect, product-owner	System design, technical decisions; requirements, user stories
quality_analysis	comprehensive-analyst, code-review-gatekeeper, peer-review-critic	Investigation/profiling; code review; final diff-scoped peer review
documentation	technical-docs-writer	Guides, API docs, developer documentation

Single-Agent Routing

Match dominant signals in the task description:

Rust, cargo, tokio → rust-expert. C#, .NET, ASP.NET Core, Azure → csharp-expert. Go, goroutines, gRPC → go-expert. Java, Spring Boot, Maven/Gradle → java-expert. Python, Django/Flask, pandas → python-expert. TypeScript/JavaScript, React/Next.js, Node → typescript-expert. MQL4/MQL5, MetaTrader, Expert Advisors → mql-trading-dev.
"REST API", "backend", "microservice" → the language expert for the project's stack (not a generic backend agent).
Long, output-heavy command-line runs — test batteries, log grinding, paged gh enumerations, multi-step throwaway pipelines — → bash-expert (POSIX/CI) or powershell-expert (Windows); short commands run inline in whichever agent needs them. Bash/Linux script authoring → bash-expert. PowerShell/Windows/cloud scripting → powershell-expert.
Schema, migrations, query optimization, SQL/NoSQL → database-specialist.
UI components, responsive design, CSS → frontend-specialist. Design systems, user flows, accessibility audits → uiux-specialist.
Authentication, encryption, vulnerabilities, compliance → security-specialist.
CI/CD, Kubernetes, Docker, Terraform → devops-orchestrator.
Architecture, scalability, technical trade-offs → system-architect. Requirements, backlog, user stories → product-owner.
Investigate, debug, profile, benchmark, evaluate → comprehensive-analyst (which runs its own commands inline, delegating only long, noisy runs per the selective policy).
Documentation deliverables → technical-docs-writer.
Review of implemented code → code-review-gatekeeper. Final independent review of the branch diff vs base → peer-review-critic (final gate only; see below).

Decision order: (0) the task is purely running/summarizing commands → bash-expert or powershell-expert; (1) single language implementation → that language expert; (2) clearly one specialized domain → that specialist; (3) spans domains → multi-agent workflow; (4) ambiguous or investigative → comprehensive-analyst first.

Review Gates (Mandatory Ending)

Every workflow that produces or changes code ends with, in this order:

code-review-gatekeeper — quality validation, test coverage, standards compliance.
peer-review-critic — the mandatory final gate: independent, diff-scoped review of branch vs base, run after code-review-gatekeeper and after the change is committed. Resolve every BLOCKER/MAJOR finding (or get explicit user sign-off) before declaring the work done.

Never place peer-review-critic mid-workflow, and never end a coding workflow without it.

Multi-Agent Workflow Patterns

Feature development product-owner (stories, acceptance criteria) → system-architect (design) → [language expert] (implementation + tests) → technical-docs-writer (docs) → code-review-gatekeeper → peer-review-critic

Security-critical feature security-specialist (requirements, threat model) → [language expert] (secure implementation) → security-specialist (audit) → code-review-gatekeeper → peer-review-critic

Full-stack feature system-architect (design) → database-specialist (schema, migrations) → [language expert] (API/backend) → frontend-specialist (UI) → uiux-specialist (UX/accessibility validation) → code-review-gatekeeper → peer-review-critic

Performance optimization comprehensive-analyst (profile, identify bottlenecks) → [language expert] (optimizations) → comprehensive-analyst (verify improvement) → code-review-gatekeeper → peer-review-critic

Skip phases that don't apply (e.g., no database-specialist if no schema change), but never skip the two closing review gates when code changed.

Handling Vague Tasks

If the task is underspecified (e.g., "optimize performance", "improve the app"):

Ask what component, what symptom, and what the target outcome is.
Offer a preliminary route: comprehensive-analyst to investigate, then a language expert to implement, then the closing review gates.
Do not guess a language expert without evidence of the stack.

Delegation Template

When handing the recommendation to /agentic-framework:delegate or a Task invocation, structure the prompt as:

Objective: what must be accomplished, in one sentence.
Context: relevant file paths, existing code, dependencies.
Requirements: functional and non-functional requirements.
Constraints: standards, technical limits, patterns to follow.
Deliverables: code, tests, docs — be explicit.
Validation: how to verify (build passes, tests pass, lint clean).

Recommendation Output

Present each recommendation as:

Task analysis: detected language(s), domain(s), complexity.
Primary agent with confidence (high/medium/low) and a one-line rationale.
Supporting agents / workflow if multi-domain, as an ordered sequence ending with code-review-gatekeeper → peer-review-critic.
Delegation prompt filled in from the template above.
Alternatives: when a different agent would be better (e.g., comprehensive-analyst if requirements turn out unclear).

Do not include invented time estimates, pass rates, or cost figures — only what can be derived from the task and the registry.