| name | skill-navigator |
| description | Skill discovery and invocation guidance skill exclusively by VRIL LABS. Teaches agents the optimal strategy for finding the right skill in the skill-jam repository, determining when skills should be used during a development session, and sequencing skill invocations to maximize output quality while minimizing token expenditure. Invoke when an agent is uncertain which skill to use, when to use a skill at all, or how to discover available skills for a task.
|
Skill Navigator
Exclusively by VRIL LABS
Mastery guide for finding the right skill, at the right moment, in the right sequence. Agents that use skills well produce dramatically higher-quality outputs while consuming far fewer tokens — because they offload structured reasoning to proven skill frameworks rather than re-deriving it from scratch every session. This skill teaches the full discipline of skill-aware development.
When to Use
- Agent is uncertain which skill in the repository applies to a current task
- Agent needs to decide whether to use a skill or proceed with inline reasoning
- A new development session is beginning and the agent should orient to available capabilities
- User explicitly asks "what skills are available?" or "which skill should I use for X?"
- Agent has completed one phase of a task and needs to choose the next skill to chain
- Task quality is suffering and the agent needs to reset and re-approach with structured skill usage
Process
Phase 1 — Orient to the Repository
Before searching for skills, understand the skill-jam layout:
skill-jam/
├── skills/ ← 50 core general skills (flat kebab-case dirs)
├── featured-skills/ ← 10 VRIL LABS 3D visualizer skills
├── skills/vercel-services/ ← Vercel platform skill files
├── skills/cloudflare-services/ ← Cloudflare edge skill files
├── skills/browser-automation/ ← Browser automation skills
├── skills/dev-tools/ ← Developer tool skills
├── skills/search-research/ ← Web & research search skills
├── skills/document-processing/ ← PDF, DOCX, XLSX, PPTX skills
├── skills/security/ ← Security/safety skills
├── skills/blockchain-crypto/ ← Blockchain/crypto skills
├── skills/codebase-recon/ ← VRIL LABS: codebase reconnaissance
├── skills/skill-builder/ ← VRIL LABS: SKILL.md authoring
├── skills/skill-navigator/ ← VRIL LABS: this skill
└── .claude-plugin/marketplace.json ← Full index of all 103+ skills
Fastest orientation: read README.md skills table or scan marketplace.json for the full flat list of skill names and descriptions.
Phase 2 — Determine Whether a Skill Is Needed
Apply this decision filter before searching for skills:
Use a skill when:
- The task has a known structure that a skill encodes (e.g., "review code" → code-reviewer, "research topic" → research-assistant)
- The task is repetitive across sessions and consistency matters
- The task involves external integrations (APIs, platforms, services) — skills encode the right endpoints, auth patterns, and rate-limit handling
- The process would take >5 agent steps to derive from scratch — skills compress this into a proven sequence
- The output needs a specific format that must be consistent across turns or agents
- The task is in a specialized domain (security, blockchain, 3D visualization, browser automation) where background knowledge is dense
Do NOT use a skill when:
- The task is a one-liner the agent can answer directly (e.g., "what's the capital of France?")
- No relevant skill exists and creating one would take more tokens than doing the work inline
- The skill's process is overkill for the scale of the task (e.g., running the full research-assistant process for a single factual lookup)
- The user has explicitly scoped the task to a simple, direct answer
- A skill would duplicate work already done in the current session context
Phase 3 — Discovery: Find the Right Skill
Use this hierarchy, stopping as soon as you have a confident match:
Step 1 — Check the obvious categories first
| Task type | First skill to check |
|---|
| Writing/reviewing code | code-reviewer, code-refactorer, bug-diagnoser |
| Generating tests | test-generator |
| Documentation | documentation-writer |
| CI/CD setup | cicd-pipeline-builder |
| Dependencies/packages | dependency-updater |
| Security vulnerabilities | security-scanner, skills/security/prompt-guard |
| Research a topic | research-assistant |
| Codebase reconnaissance | skills/codebase-recon |
| Web search | skills/search-research/tavily-search or skills/search-research/exa-* |
| Data analysis | data-analyst, data-validator |
| API specification | openapi-generator, api-scaffolder |
| Docker/containers | docker-composer |
| Git operations | git-workflow-automator |
| Performance | performance-profiler, cache-advisor |
| Writing a new skill | skills/skill-builder |
| Cloudflare deployment | skills/cloudflare-services/* |
| Vercel deployment | skills/vercel-services/* |
| Browser automation | skills/browser-automation/* |
| Document processing | skills/document-processing/* |
| Blockchain/crypto | skills/blockchain-crypto/* |
Step 2 — Scan marketplace.json descriptions
If Step 1 yields no match, read the description field of each skill in .claude-plugin/marketplace.json. The description is written to enable this exact lookup. Filter by:
- Keywords from the task (verb + noun: "generate tests", "analyze logs")
- Technology/platform: language, framework, service name
- Output type: the user's desired deliverable
Step 3 — Read the candidate skill's "When to Use" section
Open the SKILL.md of each candidate. The "When to Use" bullets are the authoritative filter. If the current task matches ≥1 bullet, the skill is applicable.
Step 4 — If multiple skills match, chain them
Skills are composable. Common high-performance chains:
| Goal | Chain |
|---|
| Build a feature with confidence | codebase-recon → implement → code-reviewer |
| Research and document | research-assistant → documentation-writer |
| New API endpoint | openapi-generator → api-scaffolder → test-generator |
| Audit a codebase | code-reviewer → security-scanner → bug-diagnoser |
| Deploy new service | docker-composer → cicd-pipeline-builder |
| Create a new skill | skill-navigator → skill-builder |
Phase 4 — Optimal Invocation Timing
Skills are not always most effective at the first available moment. Apply these timing rules:
Invoke at session start when:
codebase-recon — before writing any new code; recon first saves the most tokens and rework
research-assistant — when a decision requires external information before design
dev-environment-setup — at the very start of a new project or onboarding session
Invoke mid-task when:
code-reviewer — after completing a coherent chunk (function, module, PR diff), not line-by-line
bug-diagnoser — when a specific error or unexpected behavior surfaces
security-scanner — after the feature is functionally complete, before final review
test-generator — after implementation is stable, not during early iteration
Invoke at task end when:
documentation-writer — after the implementation is finalized
git-workflow-automator — when preparing to commit, tag, or release
dependency-updater — as a final sweep before shipping
Invoke on-demand (any time) when:
data-analyst, data-validator — whenever structured data appears
text-summarizer — whenever a long document needs to be distilled
language-translator — whenever translation is needed in context
Phase 5 — Token Efficiency Rules
Skills save tokens when used correctly. They waste tokens when misapplied.
Token-saving patterns:
- Invoke
research-assistant or codebase-recon once at the start, then use the output throughout the session without re-searching
- Use
text-summarizer on long documents before passing them to other skills
- Chain
openapi-generator before api-scaffolder to avoid having the scaffolder re-derive the spec
- Read only the "When to Use" and "Process" sections of a skill for invocation decisions; read the full skill only if implementing it for the first time
Token-wasting anti-patterns:
- Invoking
research-assistant multiple times on the same topic within a session
- Running
code-reviewer on every individual file rather than the complete diff
- Using
documentation-writer mid-task before code is stable (will need to re-run)
- Reading the full
SKILL.md of 10 candidates before narrowing to 2–3
Phase 6 — Output the Navigation Decision
Return a clear, concise recommendation:
## Skill Navigation
**Task**: [brief task description]
**Recommended skill(s)**: [skill name(s)]
**Invocation timing**: [now / after X / at task end]
**Rationale**: [1–2 sentence explanation]
**Chain**: [optional: skill A → skill B if chaining applies]
Output Format
## Skill Navigation
**Task**: Implement a JWT authentication middleware for an Express API
**Recommended skills**:
1. `codebase-recon` (now) — find reference implementations before coding
2. `auth-integrator` (now) — provides the JWT/OAuth process scaffold
3. `security-scanner` (after implementation) — validate no auth bypass patterns
4. `test-generator` (after implementation) — generate auth edge-case tests
**Invocation timing**: Start with codebase-recon + auth-integrator in parallel;
run security-scanner and test-generator after the feature is functionally complete.
**Chain**: codebase-recon → auth-integrator → [implement] → security-scanner → test-generator
**Rationale**: auth-integrator encodes the full OAuth/JWT process and common pitfalls.
codebase-recon surfaces battle-tested reference implementations (passport.js, jose, etc.)
before a single line is written. Security review and test generation at the end ensures
the implementation matches both the reference patterns and security standards.
Examples
Example Input
I need to set up automated database migrations for a PostgreSQL database in our Node.js
project. Which skill(s) should I use, and when?
Example Output
## Skill Navigation
**Task**: Automated PostgreSQL database migrations (Node.js)
**Recommended skills**:
1. `codebase-recon` (now) — scout Flyway, golang-migrate, node-pg-migrate, Prisma Migrate patterns
2. `backend-database` (now) — provides PostgreSQL migration process scaffold
3. `cicd-pipeline-builder` (after migration scripts are ready) — wire migrations into the deployment pipeline
4. `test-generator` (after) — generate migration rollback tests
**Chain**: codebase-recon → backend-database → [implement migrations] → cicd-pipeline-builder → test-generator
**Rationale**: database migrations are an area where subtle ordering and rollback bugs are
common; studying reference implementations first (codebase-recon) and using the backend-database
skill's structured process prevents the most frequent failure modes.
Boundaries
- Do NOT recommend a skill unless its "When to Use" section explicitly covers the current task type.
- Do NOT recommend more than 4 skills for a single task — diminishing returns set in quickly.
- Do NOT recommend invoking the same skill twice in a session for the same query — use cached output.
- Do NOT use this skill to evaluate whether a skill is high quality — use the
skill-builder skill's self-review checklist instead.
- Always include invocation timing in the recommendation — "use skill X" without timing is incomplete.
- If no skill matches the task, say so explicitly and recommend inline reasoning rather than forcing a poor fit.
- Always consider the token cost of skill discovery itself — for simple tasks, spend no more than 5 lines of reasoning on navigation before defaulting to inline.