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common-context-optimization

Techniques to maximize context window efficiency, reduce latency, and prevent 'lost in middle' issues through strategic masking and compaction.

Skill by wildbitca

IndexedApache-2.0★ 1
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/wildbitca-common-context-optimization

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About

Techniques to maximize context window efficiency, reduce latency, and prevent 'lost in middle' issues through strategic masking and compaction. (triggers: *.log, chat-history.json, reduce tokens, optimize context, summarize history, clear output)

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/common-context-optimization

What's inside

Skill name
common-context-optimization
Description
Techniques to maximize context window efficiency, reduce latency, and prevent 'lost in middle' issues through strategic masking and compaction. (triggers: *.log, chat-history.json, reduce tokens, optimize context, summarize history, clear output)
License
Apache-2.0
Instructions
45 lines in SKILL.md · view on GitHub

Files (3)

  • SKILL.md
  • compaction.md · references/
  • masking.md · references/

SKILL.md (first lines)

## **Priority: P1 (OPTIMIZATION)**

Manage the Attention Budget. Treat context as a scarce resource.

## 1. Observation Masking (Noise Reduction)

**Problem**: Large tool outputs (logs, JSON lists) flood context and degrade reasoning.
**Solution**: Replace raw output with semantic summaries _after_ consumption.

1. **Identify**: outputs > 50 lines or > 1kb.
2. **Extract**: Read critical data points immediately.
3. **Mask**: Rewrite history to replace raw data with `[Reference: <summary_of_findings>]`.
4. **See**: `references/masking.md` for patterns.

## 2. Context Compaction (State Preservation)

**Problem**: Long conversations drift from original intent.
**Solution**: Recursive summarization that preserves _State_ over _Dialogue_.

1. **Trigger**: Every 10 turns or 8k tokens.
2. **Compact**:
    - **Keep**: User Goal, Active Task, Current Errors, Key Decisions.
    - **Drop**: Chat chit-chat, intermediate tool calls, corrected assumptions.
3. **Format**: Update `System Prompt` or `Memory File` with compacted state.
4. **See**: `references/compaction.md` for algorithms.

## 3. KV-Cache Awareness (Latency)

**Goal**: Maximize pre-fill cache hits.

- **Static Prefix**: strict ordering: System -> Tools -> RAG -> User.
- **Append-Only**: Avoid inserting into the middle of history if possible.

## References

- [Observation Masking Patterns](references/masking.md)
- [Compaction Algorithms](references/compaction.md)

## Anti-Patterns

- **No raw tool dumps**: Mask large outputs immediately after extracting data.
- **No append-only growth**: Compact every 10 turns to preserve intent over dialogue.
- **No middle insertions**: Append-only history maximizes KV cache hits.

From wildbitca/ai-resources, Apache-2.0.

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Last commit (this folder)
Oct 23, 2026 (6 days ago)
Last release
Oct 24, 2026 (5 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

common-context-optimization skill. Agent Mart. https://agentmart.dev/skills/wildbitca-common-context-optimization (last updated 2026-10-24)