Detailed model routing role definitions, decision flowchart, model tier grid, and fallback chain best practices. Load when authoring agents or debugging model routing.
3k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
2
stars on the repo
on the repository, not the skill itself
Install
one command, takes just this skill from the repository
Reference for choosing the right model_role when writing agent frontmatter or delegating to sub-agents. There are 13 roles organized into 5 categories.
Quick Decision Flowchart
What does your agent primarily DO?
│
├─ Writes code?
│ ├─ Frontend/UI code (components, layouts, CSS)? → ui-coding
│ ├─ Security vulnerability scanning? → security-audit
│ └─ General code (backend, IaC, tests, debugging)? → coding
│
├─ Thinks deeply / designs systems?
│ ├─ Designing architecture or solving complex problems? → reasoning
│ ├─ Reviewing/critiquing existing work for flaws? → critique
│ └─ Investigating and synthesizing from multiple sources? → research
│
├─ Creates content?
│ ├─ Aesthetic/design direction (visual, brand, style)? → creative
│ └─ Long-form writing (docs, marketing, case studies)? → writing
│
├─ Works with images?
│ ├─ Needs to understand/analyze images? → vision
│ └─ Needs to generate images? → image-gen
│
├─ Orchestrates high-stakes operations?
│ └─ Infrastructure, deployments, shadow environments? → critical-ops
│
├─ Quick utility task (parsing, classification, file ops)?
│ └─ → fast
│
└─ None of the above / genuinely varied work?
└─ → general
Role-by-Role Reference
Foundation Roles
These two roles are required in every matrix and serve as universal fallbacks.
general
Description: Versatile catch-all, no specialization needed
Model tier: Mid (Sonnet, gpt-5.5, Gemini Pro)
When to use: The agent's work is genuinely varied — knowledge experts, ecosystem consultants, integration specialists
When NOT to use: If you can name what the agent primarily does (codes, designs, reviews), use that role instead
Example agents: explorer, foundation-expert, amplifier-expert, core-expert
Example chains:general (terminal — no fallback needed)
When to use: Well-defined, low-ambiguity, high-volume, or latency-sensitive tasks — file operations, git commands, notification triage, data extraction
When NOT to use: If the agent needs judgment calls, synthesis, or quality prose
Example agents: file-ops, git-ops, shell-exec, health-checker, triage-manager
Example chains:fast (terminal — fast agents rarely need fallback)
Model tier: Mid, code-specialized (Sonnet, gpt-5.5, Gemini Pro)
When to use: The agent writes, modifies, or debugs code as its primary activity — bug fixing, feature implementation, test writing, infrastructure-as-code
When NOT to use: If the agent primarily reviews code (use critique), designs UI layouts (use ui-coding), or audits for vulnerabilities (use security-audit)
Example agents: bug-hunter, modular-builder, test-coverage, python-dev, rust-dev
Model tier: Mid, code-specialized (same as coding today — will diverge as visually-tuned models emerge)
When to use: The agent builds user-facing interfaces — components, layouts, responsive design, CSS, accessibility
When NOT to use: If the agent writes backend code that serves a frontend (use coding). If it evaluates design aesthetics without writing code (use creative)
Example agents: component-designer, layout-architect, responsive-strategist
Model tier: Mid, code-specialized + high reasoning
When to use: The agent examines code or systems for security vulnerabilities, reviews authentication flows, assesses attack surfaces
When NOT to use: If the agent is doing general code review (use critique). If it's implementing security features (use coding)
Example agents: security-guardian
Example chains:[security-audit, critique, general]
Cognitive Mode Roles
For agents whose primary value is in HOW they think.
reasoning
Description: Deep architectural reasoning, system design, complex multi-step analysis
Model tier: Heavy (Opus, gpt-5.5-pro, Gemini Pro) with high reasoning effort
When to use: The agent designs systems, plans architectures, breaks complex problems into steps, or needs extended chain-of-thought
When NOT to use: If the agent evaluates existing work (use critique), writes prose (use writing), or generates creative concepts (use creative)
Example agents: zen-architect, brainstormer, plan-writer, recipe-author
Example chains:[reasoning, general]
critique
Description: Analytical evaluation — finding flaws in existing work, not generating solutions
Model tier: Mid with extra-high reasoning effort
When to use: The agent reviews, evaluates, or finds flaws in existing code, architecture, or plans
When NOT to use: If the agent builds something new (use reasoning or coding). If it checks for security vulnerabilities specifically (use security-audit)
Example agents: spec-reviewer, code-quality-reviewer, friction-detector
Example chains:[critique, reasoning, general] or [critique, general]
Model tier: Specialized (gemini-3-pro-image-preview) — sparse provider coverage
When to use: The agent creates images — generating mockups, producing comic panels, visual prototypes
When NOT to use: If the agent analyzes existing images (use vision)
IMPORTANT: Always include a non-image-gen fallback. Google-only in most matrices today.
Example agents: panel-artist, cover-artist
Example chains:[image-gen, creative, general] (NEVER image-gen alone)
Operational Role
critical-ops
Description: High-reliability operational tasks — infrastructure, orchestration, coordination where mistakes are costly
Model tier: Heavy (Opus, gpt-5.5-pro, Gemini Pro)
When to use: The agent orchestrates infrastructure, manages deployments, verifies shadow environments, or performs operational tasks where failures cascade
When NOT to use: If the agent writes IaC as its primary activity (use coding). If it does quick operational checks (use fast)
Example agents: setup-digital-twin, dtu-profile-builder, container-operator
Example chains:[critical-ops, coding, general]
Model Tier Grid
Every role maps to a unique (model-tier x reasoning-config) cell: