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context-budget

by @affaan-mv
4.4(20)

Analyze token expenditure of components in Claude Code sessions to optimize context usage and budget allocation.

contextbudgetaillmagentsGitHub
Installation
npx skills add https://github.com/affaan-m/everything-claude-code --skill context-budget
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Before / After Comparison

1
Before

Manually completing tasks related to analyzing Claude Code requires repeatedly consulting documentation and debugging. The entire process takes approximately 49 minutes, is prone to errors, and is inefficient.

After

By using this Skill for automated processing, all work is completed within 10 minutes, the process is standardized, and accuracy is high.

SKILL.md

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

  • Session performance feels sluggish or output quality is degrading

  • You've recently added many skills, agents, or MCP servers

  • You want to know how much context headroom you actually have

  • Planning to add more components and need to know if there's room

  • Running /context-budget command (this skill backs it)

How It Works

Phase 1: Inventory

Scan all component directories and estimate token consumption:

Agents (agents/*.md)

  • Count lines and tokens per file (words × 1.3)

  • Extract description frontmatter length

  • Flag: files >200 lines (heavy), description >30 words (bloated frontmatter)

Skills (skills/*/SKILL.md)

  • Count tokens per SKILL.md

  • Flag: files >400 lines

  • Check for duplicate copies in .agents/skills/ — skip identical copies to avoid double-counting

Rules (rules/**/*.md)

  • Count tokens per file

  • Flag: files >100 lines

  • Detect content overlap between rule files in the same language module

MCP Servers (.mcp.json or active MCP config)

  • Count configured servers and total tool count

  • Estimate schema overhead at ~500 tokens per tool

  • Flag: servers with >20 tools, servers that wrap simple CLI commands (gh, git, npm, supabase, vercel)

CLAUDE.md (project + user-level)

  • Count tokens per file in the CLAUDE.md chain

  • 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:

  • Bloated agent descriptions — description >30 words in frontmatter loads into every Task tool invocation

  • Heavy agents — files >200 lines inflate Task tool context on every spawn

  • Redundant components — skills that duplicate agent logic, rules that duplicate CLAUDE.md

  • MCP over-subscription — >10 servers, or servers wrapping CLI tools available for free

  • 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

  • Token estimation: use words × 1.3 for prose, chars / 4 for 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

  • Agent descriptions are loaded always: even if the agent is never invoked, its description field is present in every Task tool context

  • Verbose mode for debugging: use when you need to pinpoint the exact files driving overhead, not for regular audits

  • 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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Installs4.7K
Rating4.4 / 5.0
Version
Updated2026年7月17日
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Compatible Platforms

🔧Claude Code

Timeline

Created2026年3月26日
Last Updated2026年7月17日
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