// Context-aware router that detects work type (papers, proposals, code, figures, admin) and dispatches to the right domain skill. Works within superpowers' execution phase as the inner decision loop.
| name | my-router |
| description | Context-aware router that detects work type (papers, proposals, code, figures, admin) and dispatches to the right domain skill. Works within superpowers' execution phase as the inner decision loop. |
A routing layer that sits between superpowers (outer workflow) and domain skills (inner execution). It reads the working directory, file types, and prompt to decide which skill to invoke. The user does not need to remember skill names; the router selects automatically.
The router decides this. Not all tasks need superpowers' full ceremony.
| Task shape | Route | Why |
|---|---|---|
| Clear, scoped task with an obvious skill match (e.g., "add citations", "review staged changes", "make a figure") | Direct dispatch — router picks the domain skill and runs it immediately | Brainstorming and planning add no value when the task is already well-defined |
| Open-ended, multi-step, or ambiguous task (e.g., "improve the proposal", "build a new feature", "restructure the related work") | Superpowers first — brainstorm → plan → execute (router dispatches during execute) → verify | These benefit from thinking before doing |
| Quick edit or fix (e.g., "fix the typo on line 42", "rename this variable") | Neither — just do it directly | No routing or workflow needed |
| Effort signal words in prompt (e.g., "extensively", "extensive", "deep", "thorough", "in-depth", "carefully", "comprehensive") | Superpowers + extended thinking — enable extended thinking (Alt+T) and route through superpowers regardless of task shape | The user is explicitly asking for more deliberation |
The rule: if the domain skill is obvious and the scope is clear, skip superpowers and dispatch directly. If the task needs exploration or planning, let superpowers run the outer loop and the router dispatches during execution. If the user signals they want deep effort, always use superpowers with extended thinking enabled.
When superpowers is active, it handles workflow phases: brainstorm → plan → execute → verify. The router activates during the execute phase and dispatches to the right domain skill.
When superpowers is not active (direct dispatch or quick task), the router works standalone.
At dispatch time, the router checks three signals in order:
The user's prompt often contains the clearest signal. Match keywords to skills:
| Keywords in prompt | Skill | Source |
|---|---|---|
| "cite", "citation", "bibliography", "bib", "references" | bibref-filler (or local variant like nsf-bibref-filler if available) | skills/ (shared), check local first |
| "figure", "diagram", "illustration", "schematic", "overview figure" | figure-prompt-builder | skills/ (shared) |
| "mockup", "HTML figure", "HTML mockup", "interactive figure", "dashboard mockup", "Gantt", "screenshotable figure", "capture mode", "skia-canvas", "TikZ figure", "arrow routing" | ci-mockup-figure | skills/ (shared) |
| "review staged", "review changes", "review the diff" | implement-review | skills/ (shared) |
| "two-pass", "first pass", "second pass", "audit" | dual-pass-workflow | skills/ (shared) |
| "polish README", "modernize README", "README audit", "README rewrite", "README badges", "README hero", "GitHub README patterns" | readme-polish | skills/ (shared) |
| "proposal", "nsf", "nih", "grant", "solicitation", "aim", "thrust" | Proposal skills (check for local nsf-*, nih-* skills first) | reference-skills/ (project-local) |
| "review paper", "peer review", "reviewer comments" | cs-paper-review | reference-skills/ (project-local) |
| "meta-review", "area chair", "AC decision" | cs-meta-review | reference-skills/ (project-local) |
| "slides", "presentation", "beamer" | paper-to-beamer or deck-assembler | reference-skills/ (project-local) |
| "cv", "curriculum vitae", "resume" | condense-cv | reference-skills/ (project-local) |
| "reimbursement", "travel claim", "expense" | usc-reimbursement | reference-skills/ (project-local) |
If prompt keywords are ambiguous, inspect the files being worked on:
| Files present | Likely context | Default skill |
|---|---|---|
.tex + .bib in a paper/ or manuscript directory | Paper writing | bibref-filler for citations, implement-review (paper lens) for review |
.tex + .bib in a proposal/ or nsf/ or grant/ directory | Proposal writing | Proposal skills (check for local nsf-* or nih-* skills first), implement-review (ask user which agency lens) for review |
.py, .js, .ts, or other code files | Code | Superpowers handles directly (brainstorm → plan → execute → verify) |
.md slides or presentation files | Presentations | paper-to-beamer or deck-assembler |
| HTML mockups for system/dashboard figures | System figures | ci-mockup-figure |
| HTML mockups for general frontend/demos | Frontend | frontend-design plugin |
.md in a proposal or grant directory | Proposal (Markdown-based) | Proposal skills (check for local skills first) |
| Staged git changes | Review needed | implement-review |
Some projects declare their type in AGENTS.local.md or directory naming:
proposals/, nsf-*, nih-* → proposal contextpapers/, manuscript/, draft/ → paper contextskills/ for any local skill that is a more specific variant of the matched skill (e.g., nsf-bibref-filler over shared bibref-filler, or nsf-figure-builder over shared figure-prompt-builder). If a local variant exists, use it instead.implement-review and local proposal skills) → use implement-review as the outer loop and ask the user which agency lens to apply (NSF, NIH, etc.). Load any local proposal skills as supplementary criteria.In consuming project repos, skills can be project-local, pack-deployed, or bootstrapped from shared config. When dispatching, look for each skill in this order:
skills/<name>/SKILL.md: project-local (highest priority). Projects may have their own custom skills here that are not in the shared config. The router should scan skills/ for any available SKILL.md files, not just the ones listed in the routing table below..claude/skills/<name>/SKILL.md: pack-deployed by anywhere-agents pack install. The .claude/ prefix is a historical Claude Code convention; the SKILL.md contents are agent-agnostic..agent-config/repo/skills/<name>/SKILL.md: bootstrapped from shared config.frontend-design, superpowers, pyright-lsp) provide their own skills and capabilities. Check /skills output for plugin-provided skills alongside the three locations above. Plugin skills may overlap with custom skills; prefer the more specific one (e.g., a project-local nsf-proposal-composer over a generic plugin writing skill).If a project-local skill matches the task better than a pack-deployed or bootstrapped skill, prefer the project-local one. The router itself follows this same lookup order: in the agent-config repo it lives at skills/my-router/; in other projects it lives at .claude/skills/my-router/ or .agent-config/repo/skills/my-router/.
Skills come from three sources with different availability:
| Source | Available where | How |
|---|---|---|
skills/ (shared) | All projects | Copied by bootstrap into .agent-config/repo/skills/ |
| Pack-deployed (third-party packs) | Projects that install the pack | anywhere-agents pack install writes into .claude/skills/<name>/ |
reference-skills/ (domain) | Only projects that have them locally | Copied manually into skills/ in the project repo |
Before invoking a reference skill, check that its SKILL.md exists in the current project (in skills/, .claude/skills/, or .agent-config/repo/skills/). If it does not exist, inform the user: "This task would use [skill name], but it is not available in this project. You can copy it from https://github.com/yzhao062/agent-config/tree/main/reference-skills/."
For tasks that benefit from build-then-audit:
bibref-filler adds citations)implement-review or the domain skill's audit modeThe user can say "two-pass this" and the router will wrap the domain skill in dual-pass-workflow automatically.
When review is needed after domain skill execution:
implement-review with the appropriate lens (paper, proposal, or code)User says: "Add citations to the related work section"
→ Router detects: keyword "citations" → checks for local variant (e.g., nsf-bibref-filler) → if found, uses it; otherwise falls back to shared bibref-filler
User says: "Review this"
→ Router detects: staged changes exist, .tex files in a proposal directory → implement-review, asks user which agency lens (NSF, NIH, etc.)
User says: "Make an overview figure for the proposal"
→ Router detects: keyword "figure" + "proposal" → checks for local nsf-figure-builder → if found, uses it; otherwise falls back to shared figure-prompt-builder
User says: "Help me improve this section"
→ Router detects: .tex in proposal directory, no specific keyword → asks user: "This looks like proposal work. Should I use local proposal skills, or is this general editing?"
User says: "Build the feature and review it"
→ Router detects: code context → superpowers handles the build, then router dispatches to implement-review with code lens
Review loop for staged changes. Detects content type, prepares a review request for Codex (Terminal-relay manual default, opt-in Auto-terminal codex-exec subprocess, or IDE plugin), categorizes feedback, revises, and iterates. Works for code, papers, proposals, or any text-based output.
Audit a GitHub README and rewrite it using modern 2025-2026 patterns — centered header, badges, hero image, GitHub alert callouts, emoji-prefixed features, expandable details, Mermaid diagrams, tables over dense prose. Produces a scannable README that works for a 10-second skim and a deep dive.
Create space-efficient figures for papers and proposals. HTML mockups for systems, dashboards, and timelines; TikZ or skia-canvas for abstract diagrams with arrow routing. Covers tool selection, design, capture, and LaTeX insertion. The primary goal is maximizing information per page — every figure must earn its space.
Build copy-ready prompts for downstream LLM figure generation from source text, figure ideas, prior examples, or rough drafts. Use when Codex needs to decide whether a section needs a figure, distill the figure's core message and required visual elements, draft a model-neutral prompt pack for image-generation models, adapt prompts to a requested tool, or recommend limited cleanup after external generation.
Compose NSF proposal outlines and section drafts from a project idea, prior proposal examples, and solicitation requirements. Use when Codex needs to choose between ecosystem-building and methodology-driven proposal families, turn a brief into a proposal structure, draft or refresh LaTeX sections, introduce an optional cross-section running example for abstract infrastructure proposals, or keep summary, aims, evaluation, and impact sections aligned during proposal writing.
Unified NSF proposal requirements, question-answering, and preflight checking for a single proposal repository. Use when a user has an NSF solicitation PDF/text and needs to (1) ingest and normalize proposal requirements, (2) ask drafting-time questions such as "do we need X?" or "where does this go?", or (3) run a pre-submission gap check against the current proposal files.