home / skills / anton-abyzov / specweave / context-loader

context-loader skill

/plugins/specweave/skills/context-loader

This skill explains how SpecWeave achieves context efficiency using Claude's progressive disclosure and sub-agent parallelization to scale with large projects.

This is most likely a fork of the sw-context-loader skill from openclaw
npx playbooks add skill anton-abyzov/specweave --skill context-loader

Review the files below or copy the command above to add this skill to your agents.

Files (2)
SKILL.md
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---
name: context-loader
description: 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.
---

# Context Management in SpecWeave

## Overview

SpecWeave achieves efficient context usage through **two native Claude Code mechanisms**:

1. **Progressive Disclosure** (Skills) - Claude's built-in skill loading system
2. **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)

```yaml
---
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)

```markdown
# 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

- [What are Skills?](https://support.claude.com/en/articles/12512176-what-are-skills)
- [Agent Skills Engineering](https://www.anthropic.com/engineering/equipping-agents-for-the-real-world-with-agent-skills)

> "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:**

1. **Context Isolation**
   - Each sub-agent starts with empty context
   - Doesn't inherit main conversation's 100K tokens
   - Can load its own relevant skills

2. **Parallelization**
   - Multiple agents work simultaneously
   - Each with own context budget
   - Results merged back to main conversation

3. **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

- [Sub-Agents Documentation](https://docs.claude.com/en/docs/claude-code/sub-agents)

---

## 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:

```yaml
# 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:

1. **Progressive Disclosure (Native Claude)**
   - Skills load only when relevant
   - Metadata-first approach
   - 90%+ savings on simple tasks

2. **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.**

---

## References

- [Claude Skills Documentation](https://support.claude.com/en/articles/12512176-what-are-skills)
- [Agent Skills Engineering Blog](https://www.anthropic.com/engineering/equipping-agents-for-the-real-world-with-agent-skills)
- [Sub-Agents Documentation](https://docs.claude.com/en/docs/claude-code/sub-agents)

Overview

This skill explains how SpecWeave uses Claude's native progressive disclosure and sub-agent parallelization to achieve context efficiency. It clarifies token savings, when and why skills or sub-agents load, and how SpecWeave organizes skills and coordinates agents without custom caching. Use it to understand context behavior and scale strategies for large projects.

How this skill works

SpecWeave relies on Claude Code's two native mechanisms: progressive disclosure, where only skill metadata is visible initially and full skill content is loaded on demand; and sub-agent parallelization, where isolated agent contexts run in parallel and merge results back to the main conversation. SpecWeave organizes focused skill descriptions so Claude can pick relevant skills quickly, and its role-orchestrator launches specialized sub-agents for multi-domain work.

When to use it

  • When you need to explain token usage or context budgeting for a task
  • When investigating why a specific skill did or did not load
  • When planning large multi-domain work (frontend, backend, devops)
  • When evaluating how SpecWeave scales with growing skill sets or codebases
  • When debugging whether sub-agents were launched for parallel work

Best practices

  • Write clear, focused skill descriptions with trigger keywords and explicit technologies
  • Keep unrelated domains in separate skills to avoid irrelevant loads
  • Use sub-agents for parallel, multi-domain tasks and avoid them for small sequential tasks
  • Rely on Claude's automatic loading—don’t add custom context manifests or caching layers
  • Monitor Claude's runtime messages to confirm which skills or sub-agents were used

Example use cases

  • User asks to build a Next.js auth page: Claude scans metadata, loads only nextjs and frontend skills instead of all skills
  • Large feature: launch frontend, backend, and devops sub-agents in parallel; each loads its own skills and returns isolated results
  • Exploring a large codebase: sub-agents focus on separate modules to avoid context bloat
  • Coordinating a full-stack SaaS spec: role-orchestrator splits work (PM, Architect, Security, DevOps) into isolated agent contexts

FAQ

Does SpecWeave implement custom caching or context manifests?

No. SpecWeave leverages Claude's native progressive disclosure and does not add custom caching or manifest systems.

How much token savings can I expect?

Savings vary by task: simple tasks often see >90% reduction (1–2 skills vs all), complex multi-domain tasks typically see 50–70% improvement using sub-agents; exact numbers depend on task complexity.