ad-spend-optimizer
Analyze paid advertising performance across channels and recommend budget reallocation to maximize ROAS and minimize CAC. Use…
Use when context is growing large (50k+ tokens), performance is degrading, instructions are being ignored mid-conversation, or planning multi-agent workflows. Triggers on "lost context", forgotten instructions, or sessions exceeding 30 minutes.
Claude Code
$ npx -y skills add guia-matthieu/clawfu-skills --skill context-engineering --agent claude-code
Codex
$ npx skills add guia-matthieu/clawfu-skills --skill context-engineering -a codex -y
Cursor
$ npx skills add guia-matthieu/clawfu-skills --skill context-engineering -a cursor -y
Gemini CLI
$ npx skills add guia-matthieu/clawfu-skills --skill context-engineering -a gemini-cli -y
GitHub Copilot
$ npx skills add guia-matthieu/clawfu-skills --skill context-engineering -a github-copilot -y
OpenCode
$ npx skills add guia-matthieu/clawfu-skills --skill context-engineering -a opencode -y
Windsurf
$ npx skills add guia-matthieu/clawfu-skills --skill context-engineering -a windsurf -y
name: context-engineering description: Use when context is growing large (50k+ tokens), performance is degrading, instructions are being ignored mid-conversation, or planning multi-agent workflows. Triggers on "lost context", forgotten instructions, or sessions exceeding 30 minutes. license: MIT metadata: author: ClawFu version: 1.0.0 mcp-server: "@clawfu/mcp-skills"
**Core principle:** Context is a finite resource with diminishing returns. Find the smallest high-signal token set, not the largest.
200K tokens is shared space: system prompt + conversation history + your processing. As context grows, performance degrades predictably.
| Problem | Symptom | Fix | |---------|---------|-----| | **Lost-in-middle** | Mid-conversation instructions ignored | Move critical info to start/end | | **Context poisoning** | Errors compounding, hallucinations referenced | Summarize and reset | | **Context distraction** | Irrelevant info degrading performance | Prune aggressively | | **Context confusion** | Conflicting guidance causing inconsistency | Consolidate instructions |
Information in context middle gets **10-40% lower recall** than edges.
[START - High attention] ↓ [MIDDLE - Low attention zone] ← Instructions here get ignored ↓ [END - High attention]
**Fix:** Strategic placement
Early hallucination gets referenced → compounds → becomes "fact".
**Symptoms:**
**Fix:** Checkpoint and summarize
Every 10-15 exchanges, create explicit checkpoint: "Let me summarize what we've established: 1. [Verified fact] 2. [Verified fact] 3. [Decision made] Continuing from here..."
Irrelevant tokens compete for attention budget.
**Symptoms:**
**Fix:** Aggressive pruning
Multiple conflicting instructions create inconsistent behavior.
**Symptoms:**
**Fix:** Consolidate
Before: "Use TypeScript" (message 3) + "Keep it simple" (message 12) + "Add types everywhere" (message 27) After: "TypeScript with practical typing - types where they help, skip where obvious"
When approaching limits, summarize context sections:
## Session Summary (compacted) **Goal:** [One sentence] **Decisions made:** - [Decision 1] - [Decision 2] **Current state:** [What's done, what's next] **Key constraints:** [Still-active requirements] --- [Continue with fresh context]
Replace verbose tool outputs with compact references:
Before: [500 lines of file content in context] After: "Read src/app/page.tsx - React component with Hero, About, FAQ sections"
Isolate subtasks in separate agents with clean contexts:
Main Agent (orchestrator): - High-level plan - Synthesis of results Subagent 1 (search): Subagent 2 (implement): - Only search context - Only implementation context - Returns summary - Returns code
**Rule:** Subagents get task + minimum required context, NOT full conversation history.
digraph context_management {
"Every 15-20 min" [shape=diamond];
"Context healthy?" [shape=diamond];
"Continue" [shape=box];
"Create checkpoint summary" [shape=box];
"Consider /clear + summary" [shape=box];
"Every 15-20 min" -> "Context healthy?";
"Context healthy?" -> "Continue" [label="yes"];
"Context healthy?" -> "Create checkpoint summary" [label="degrading"];
"Create checkpoint summary" -> "Consider /clear + summary";
}**Health check questions:**
Capture for next session: 1. **Goal state** - What were we trying to achieve? 2. **Current state** - What's done, what's broken? 3. **Key decisions** - Why did we choose X over Y? 4. **Active constraints** - What rules still apply? 5. **Next steps** - Where to pick up?
## Subagent Prompt Template **Task:** [Specific deliverable] **Context:** [ONLY what's needed - 50-200 words max] **Constraints:** [Hard requirements] **Output format:** [What to return] [Do NOT include: conversation history, resolved discussions, unrelated files]
| Anti-Pattern | Why it fails | Better approach | |--------------|--------------|-----------------| | "Include everything just in case" | Dilutes attention, causes distraction | Include only what's needed NOW | | Repeating instructions every message | Wastes tokens, implies they weren't heard | Trust system prompt, reinforce only when ignored | | Long file dumps without summary | Lost-in-middle effect | Read → summarize → reference summary | | Keeping resolved threads active | Context confusion | Summarize resolution, move on |
175 expert marketing methodologies for AI agents. Free. Open source. MIT licensed. Dunford on positioning. Schwartz on copywriting. Cialdini on persuasion. Ogilvy on advertising. Hormozi on offers. Voss on negotiation.
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