Skill Injector - Smart Skill Selection

Maps task signals to skills from the everything-claude-code catalog and injects only the relevant ones into each agent's prompt. Prevents context bloat by being selective.

When to Activate

• During task routing (called by task-router skill)
• When an agent needs additional skill guidance mid-task

Skill Selection Algorithm

Input

• Task classification (type + complexity) from task-router
• Agent role being dispatched
• Project stack from crew-profile.md
• Skill catalog from crew-skills.json

Selection Rules

Rule 1: Always-Active Skills (injected into every agent) These are universal best practices (kept minimal for token efficiency):

• context-budget

  — monitor token consumption (subsumes strategic-compact)

• verification-loop

  — verify before claiming done

• coding-standards

  — follow project conventions

Note:

iterative-retrieval

moved to bug-fix task-type skills.

search-first

moved to feature task-type skills.

strategic-compact

dropped (redundant with context-budget).

Rule 2: Stack-Specific Skills (based on detected languages)

Stack	Skills
JavaScript/TypeScript	typescript-patterns, backend-patterns
React	react-patterns, react-testing
Next.js	nextjs-patterns
Vue	vue-patterns, nuxt4-patterns
Python	python-patterns
Django	django-patterns, django-security, django-tdd
Flask	python-patterns
Go	golang-patterns
Rust	rust-patterns
Java	java-patterns, springboot-patterns
Kotlin	kotlin-patterns, kotlin-testing
C++	cpp-coding-standards, cpp-testing
C#	csharp-testing, dotnet-patterns
Flutter/Dart	dart-flutter-patterns
Swift	swiftui-patterns, swift-concurrency-6-2
PHP/Laravel	php-patterns, laravel-patterns

Rule 3: Task-Type Skills (based on classified task type)

Task Type	Skills
bug-fix	iterative-retrieval, deep-research, codebase-onboarding
feature	architecture-decision-records, agentic-engineering, blueprint, search-first
refactor	architecture-decision-records, backend-patterns
test	tdd-workflow, e2e-testing, ai-regression-testing
security	security-scanning
docs	article-writing, documentation-lookup
devops	deployment-patterns, docker-patterns, database-migrations, git-workflow
review	verification-loop
performance	cost-aware-llm-pipeline

Rule 4: Agent-Role Skills (specific to the dispatched agent)

Agent	Additional Skills
ceo	agentic-engineering, architecture-decision-records
vp-engineering	architecture-decision-records, hexagonal-architecture
vp-quality	verification-loop, tdd-workflow
senior-dev	(stack skills + task skills)
junior-dev	coding-standards only (keep prompt small for Haiku)
code-reviewer	verification-loop, security-scanning
debugger	iterative-retrieval, deep-research
security-analyst	security-scanning
devops-engineer	deployment-patterns, docker-patterns
doc-writer	article-writing
test-engineer	tdd-workflow, e2e-testing

Output: Skill Injection Payload

For each agent being dispatched, generate a skills section:

## Injected Skills for this Task

### From: {skill-name}
{Condensed key guidance from the skill - NOT the full SKILL.md, just the most relevant rules and patterns for this specific subtask}

### From: {skill-name-2}
{Condensed guidance}

Token Budget per Agent

To prevent context bloat from too many skills:

Agent Model	Max Skill Tokens	Max Skills
Opus (CEO)	3000 tokens	6 skills
Sonnet (leads/senior)	2000 tokens	4 skills
Sonnet (planner in lite mode)	2500 tokens	5 skills
Haiku (junior/devops/docs)	800 tokens	2 skills

Lite mode note: When

--lite

flag is used, no Opus agents are dispatched. The vp-engineering agent takes over planning duties and gets an expanded budget (2500 tokens, 5 skills) to compensate for the extra architectural context it needs.

If selected skills exceed the budget:

1. Prioritize: always-active > task-type > stack > agent-role
2. Truncate to key rules only (skip examples, anti-patterns)
3. Drop lowest-priority skills

Skill Content Condensation

When injecting a skill, don't paste the entire SKILL.md. Extract only:

1. The core rules/principles (2-5 bullet points)
2. The most relevant pattern for this specific task
3. Any critical anti-patterns to avoid

Example condensation:

Full SKILL.md: 200 lines, ~2000 tokens
Condensed injection: 15 lines, ~150 tokens

This keeps agent prompts focused and within token budget.