Claude-skill-registry context-loader
Explains how SpecWeave achieves context efficiency through Claude's native progressive disclosure and sub-agent parallelization. Use when asking about token usage, context management, or how SpecWeave scales with large projects. Leverages Claude's built-in mechanisms without custom caching.
git clone https://github.com/majiayu000/claude-skill-registry
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/context-loader-anton-abyzov-specweave" ~/.claude/skills/majiayu000-claude-skill-registry-context-loader && rm -rf "$T"
skills/data/context-loader-anton-abyzov-specweave/SKILL.mdContext Management in SpecWeave
Overview
SpecWeave achieves efficient context usage through two native Claude Code mechanisms:
- Progressive Disclosure (Skills) - Claude's built-in skill loading system
- Sub-Agent Parallelization - Isolated context windows for parallel work
Important: SpecWeave does NOT use custom context manifests or caching systems. It leverages Claude's native capabilities.
1. Progressive Disclosure (Skills)
How It Works
Claude Code uses a two-level progressive disclosure system for skills:
Level 1: Metadata Only (Always Loaded)
--- name: nextjs description: NextJS 14+ implementation specialist. Creates App Router projects... ---
What Claude sees initially:
- Only the YAML frontmatter (name + description)
- ~50-100 tokens per skill
- All skills' metadata is visible
- Claude can decide which skills are relevant
Level 2: Full Skill Content (Loaded On-Demand)
# NextJS Skill [Full documentation, examples, best practices...] [Could be 5,000+ tokens]
What Claude loads:
- Full SKILL.md content only if skill is relevant to current task
- Prevents loading 35+ skills (175,000+ tokens) when you only need 2-3
- This is the actual mechanism that saves tokens
Example Workflow
User: "Create a Next.js authentication page" ↓ Claude reviews skill metadata (35 skills × 75 tokens = 2,625 tokens) ↓ Claude determines relevant skills: - nextjs (matches "Next.js") - frontend (matches "page") - (NOT loading: python-backend, devops, hetzner-provisioner, etc.) ↓ Claude loads ONLY relevant skills: - nextjs: 5,234 tokens - frontend: 3,891 tokens ↓ Total loaded: 9,125 tokens (vs 175,000+ if loading all skills) Token reduction: ~95%
References
"Skills work through progressive disclosure—Claude determines which Skills are relevant and loads the information it needs to complete that task, helping to prevent context window overload."
2. Sub-Agent Parallelization
How It Works
Sub-agents in Claude Code have isolated context windows:
Main conversation (100K tokens used) ↓ Launches 3 sub-agents in parallel ↓ ├─ Sub-agent 1: Fresh context (0K tokens used) ├─ Sub-agent 2: Fresh context (0K tokens used) └─ Sub-agent 3: Fresh context (0K tokens used)
Benefits:
-
Context Isolation
- Each sub-agent starts with empty context
- Doesn't inherit main conversation's 100K tokens
- Can load its own relevant skills
-
Parallelization
- Multiple agents work simultaneously
- Each with own context budget
- Results merged back to main conversation
-
Token Multiplication
- Main: 200K token limit
- Sub-agent 1: 200K token limit
- Sub-agent 2: 200K token limit
- Effective capacity: 600K+ tokens across parallel work
Example Workflow
User: "Build a full-stack Next.js app with auth, payments, and admin" ↓ Main conversation launches 3 sub-agents in parallel: ↓ ├─ Sub-agent 1 (Frontend) │ - Loads: nextjs, frontend skills │ - Context: 12K tokens │ - Implements: Auth UI, payment forms │ ├─ Sub-agent 2 (Backend) │ - Loads: nodejs-backend, security skills │ - Context: 15K tokens │ - Implements: API routes, auth logic │ └─ Sub-agent 3 (DevOps) - Loads: devops, hetzner-provisioner skills - Context: 8K tokens - Implements: Deployment configs ↓ All 3 work in parallel with isolated contexts ↓ Results merged back to main conversation ↓ Total effective context: 35K tokens across 3 agents (vs 175K+ if loaded all skills in main conversation)
References
Actual Token Savings
Progressive Disclosure Savings
Scenario: User asks about Next.js
Without progressive disclosure:
Load all 35 skills: ~175,000 tokens Context bloat: Massive
With progressive disclosure:
Metadata (all skills): ~2,625 tokens Load relevant (2 skills): ~9,000 tokens Total: ~11,625 tokens Reduction: ~93%
Sub-Agent Savings
Scenario: Complex multi-domain task
Single agent approach:
Load all relevant skills: ~50,000 tokens Main conversation history: ~80,000 tokens Total context used: ~130,000 tokens Risk: Approaching context limit
Sub-agent approach:
Main conversation: ~5,000 tokens (coordination only) Sub-agent 1: ~15,000 tokens (isolated) Sub-agent 2: ~18,000 tokens (isolated) Sub-agent 3: ~12,000 tokens (isolated) Total: ~50,000 tokens across 4 contexts Reduction: ~62% (130K → 50K)
Note: Exact percentages vary by task complexity. These are approximate based on typical usage patterns.
How SpecWeave Leverages These Mechanisms
1. Skill Organization (Progressive Disclosure)
SpecWeave organizes 35+ skills with clear, focused descriptions:
# Good: Focused description --- name: nextjs description: NextJS 14+ App Router specialist. Server Components, SSR, routing. --- # Bad: Vague description --- name: frontend description: Does frontend stuff ---
Why this matters:
- Clear descriptions help Claude identify relevance quickly
- Prevents loading irrelevant skills
- Maximizes progressive disclosure benefits
2. Agent Coordination (Sub-Agent Parallelization)
SpecWeave's role-orchestrator skill automatically:
- Detects multi-domain tasks
- Launches specialized sub-agents (PM, Architect, DevOps, etc.)
- Each sub-agent loads only its relevant skills
- Coordinates results back to main conversation
Example:
User: "/sw:inc 'Full-stack SaaS with Stripe payments'" ↓ role-orchestrator activates ↓ Launches sub-agents in parallel: ├─ PM agent (requirements) ├─ Architect agent (system design) ├─ Security agent (threat model) └─ DevOps agent (deployment) ↓ Each loads only relevant skills in isolated context ↓ Results merged into increment spec
Common Misconceptions
❌ Myth 1: "SpecWeave has custom context manifests"
Reality: No. SpecWeave uses Claude's native progressive disclosure. Skills load based on Claude's relevance detection, not custom YAML manifests.
❌ Myth 2: "SpecWeave caches loaded context"
Reality: No custom caching. Claude Code handles caching internally (if applicable). SpecWeave doesn't implement additional caching layers.
❌ Myth 3: "70-90% token reduction"
Reality: Token savings vary by task:
- Simple tasks: 90%+ (load 1-2 skills vs all 35)
- Complex tasks: 50-70% (load 5-10 skills + use sub-agents)
- Exact percentages depend on task complexity
✅ Truth: "It just works"
Reality: Progressive disclosure and sub-agents are automatic. You don't configure them. Claude handles skill loading, sub-agent context isolation happens automatically when agents are launched.
Best Practices
For Skill Descriptions
Do:
- Be specific about what the skill does
- Include trigger keywords users might say
- List technologies/frameworks explicitly
Don't:
- Write vague descriptions ("helps with coding")
- Omit key activation triggers
- Mix multiple unrelated domains in one skill
For Sub-Agent Usage
When to use sub-agents:
- Multi-domain tasks (frontend + backend + devops)
- Parallel work (multiple features simultaneously)
- Large codebase exploration (different modules)
When NOT to use sub-agents:
- Simple single-domain tasks
- Sequential work requiring shared context
- When main conversation context is already low
Debugging Context Usage
Check Active Skills
When Claude mentions using a skill:
User: "Create a Next.js page" Claude: "🎨 Using nextjs skill..."
This means:
- Progressive disclosure worked
- Only nextjs skill loaded (not all 35)
- Context efficient
Check Sub-Agent Usage
When Claude mentions launching agents:
Claude: "🤖 Launching 3 specialized agents in parallel..."
This means:
- Sub-agent parallelization active
- Each agent has isolated context
- Efficient multi-domain processing
Summary
SpecWeave achieves context efficiency through:
-
Progressive Disclosure (Native Claude)
- Skills load only when relevant
- Metadata-first approach
- 90%+ savings on simple tasks
-
Sub-Agent Parallelization (Native Claude Code)
- Isolated context windows
- Parallel processing
- 50-70% savings on complex tasks
No custom manifests. No custom caching. Just smart use of Claude's native capabilities.