context-budget
分析 Claude Code 会话中各组件的 token 开销,优化上下文使用和预算分配
npx skills add https://github.com/affaan-m/everything-claude-code --skill context-budgetBefore / After 效果对比
1 组在没有 `context-budget` 工具时,当 Claude Code 会话性能下降或输出质量变差时,开发者通常需要手动排查。这包括逐一检查代理、技能、规则和 CLAUDE.md 文件,估算其行数、描述长度和潜在的重复内容。对于 MCP 服务器,需要手动统计工具数量并评估其必要性。整个过程耗时且容易遗漏,导致上下文空间被不必要的组件占用,限制了会话的效率和可扩展性,难以准确评估实际可用的上下文余量。
使用 `context-budget` 后,只需运行 `/context-budget` 命令,即可获得会话中所有组件(代理、技能、规则、MCP 服务器、CLAUDE.md)的详细 token 开销分析。它会自动识别并标记出臃肿的代理描述、过重的代理文件、冗余的组件、MCP 过度订阅以及 CLAUDE.md 冗余内容。系统还会将组件分类为“始终需要”、“有时需要”或“很少需要”,并提供可操作的优化建议,帮助开发者快速回收上下文空间,提升会话性能,并清晰了解上下文余量。
context-budget
Context Budget
Analyze token overhead across every loaded component in a Claude Code session and surface actionable optimizations to reclaim context space.
When to Use
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Session performance feels sluggish or output quality is degrading
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You've recently added many skills, agents, or MCP servers
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You want to know how much context headroom you actually have
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Planning to add more components and need to know if there's room
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Running
/context-budgetcommand (this skill backs it)
How It Works
Phase 1: Inventory
Scan all component directories and estimate token consumption:
Agents (agents/*.md)
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Count lines and tokens per file (words × 1.3)
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Extract
descriptionfrontmatter length -
Flag: files >200 lines (heavy), description >30 words (bloated frontmatter)
Skills (skills/*/SKILL.md)
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Count tokens per SKILL.md
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Flag: files >400 lines
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Check for duplicate copies in
.agents/skills/— skip identical copies to avoid double-counting
Rules (rules/**/*.md)
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Count tokens per file
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Flag: files >100 lines
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Detect content overlap between rule files in the same language module
MCP Servers (.mcp.json or active MCP config)
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Count configured servers and total tool count
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Estimate schema overhead at ~500 tokens per tool
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Flag: servers with >20 tools, servers that wrap simple CLI commands (
gh,git,npm,supabase,vercel)
CLAUDE.md (project + user-level)
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Count tokens per file in the CLAUDE.md chain
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Flag: combined total >300 lines
Phase 2: Classify
Sort every component into a bucket:
Bucket Criteria Action
Always needed Referenced in CLAUDE.md, backs an active command, or matches current project type Keep
Sometimes needed Domain-specific (e.g. language patterns), not referenced in CLAUDE.md Consider on-demand activation
Rarely needed No command reference, overlapping content, or no obvious project match Remove or lazy-load
Phase 3: Detect Issues
Identify the following problem patterns:
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Bloated agent descriptions — description >30 words in frontmatter loads into every Task tool invocation
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Heavy agents — files >200 lines inflate Task tool context on every spawn
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Redundant components — skills that duplicate agent logic, rules that duplicate CLAUDE.md
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MCP over-subscription — >10 servers, or servers wrapping CLI tools available for free
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CLAUDE.md bloat — verbose explanations, outdated sections, instructions that should be rules
Phase 4: Report
Produce the context budget report:
Context Budget Report
═══════════════════════════════════════
Total estimated overhead: ~XX,XXX tokens
Context model: Claude Sonnet (200K window)
Effective available context: ~XXX,XXX tokens (XX%)
Component Breakdown:
┌─────────────────┬────────┬───────────┐
│ Component │ Count │ Tokens │
├─────────────────┼────────┼───────────┤
│ Agents │ N │ ~X,XXX │
│ Skills │ N │ ~X,XXX │
│ Rules │ N │ ~X,XXX │
│ MCP tools │ N │ ~XX,XXX │
│ CLAUDE.md │ N │ ~X,XXX │
└─────────────────┴────────┴───────────┘
⚠ Issues Found (N):
[ranked by token savings]
Top 3 Optimizations:
1. [action] → save ~X,XXX tokens
2. [action] → save ~X,XXX tokens
3. [action] → save ~X,XXX tokens
Potential savings: ~XX,XXX tokens (XX% of current overhead)
In verbose mode, additionally output per-file token counts, line-by-line breakdown of the heaviest files, specific redundant lines between overlapping components, and MCP tool list with per-tool schema size estimates.
Examples
Basic audit
User: /context-budget
Skill: Scans setup → 16 agents (12,400 tokens), 28 skills (6,200), 87 MCP tools (43,500), 2 CLAUDE.md (1,200)
Flags: 3 heavy agents, 14 MCP servers (3 CLI-replaceable)
Top saving: remove 3 MCP servers → -27,500 tokens (47% overhead reduction)
Verbose mode
User: /context-budget --verbose
Skill: Full report + per-file breakdown showing planner.md (213 lines, 1,840 tokens),
MCP tool list with per-tool sizes, duplicated rule lines side by side
Pre-expansion check
User: I want to add 5 more MCP servers, do I have room?
Skill: Current overhead 33% → adding 5 servers (~50 tools) would add ~25,000 tokens → pushes to 45% overhead
Recommendation: remove 2 CLI-replaceable servers first to stay under 40%
Best Practices
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Token estimation: use
words × 1.3for prose,chars / 4for code-heavy files -
MCP is the biggest lever: each tool schema costs ~500 tokens; a 30-tool server costs more than all your skills combined
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Agent descriptions are loaded always: even if the agent is never invoked, its description field is present in every Task tool context
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Verbose mode for debugging: use when you need to pinpoint the exact files driving overhead, not for regular audits
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Audit after changes: run after adding any agent, skill, or MCP server to catch creep early
Weekly Installs265Repositoryaffaan-m/everyt…ude-codeGitHub Stars105.0KFirst Seen5 days agoSecurity AuditsGen Agent Trust HubPassSocketPassSnykPassInstalled oncodex255cursor229opencode227gemini-cli227github-copilot227amp227
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