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* feat(commands): add /context-budget optimizer command Adds a command that audits context window token consumption across agents, skills, rules, MCP servers, and CLAUDE.md files. Detects bloated agent descriptions, redundant components, MCP over-subscription, and CLAUDE.md bloat. Produces a prioritized report with specific token savings per optimization. Directly relevant to #434 (agent descriptions too verbose, ~26k tokens causing performance warnings). * fix: address review feedback on context-budget command - Add $ARGUMENTS to enable --verbose flag passthrough - Fix MCP token estimate: 45 tools × ~500 tokens = ~22,500 (was ~2,200) - Fix heavy agents example: all 3 now exceed 200-line threshold - Fix description threshold: warning at >30 words, fail at >50 words - Add Step 4 instructions (was empty) - Fix audit cadence: "quarterly" → "regularly" + "monthly" consistently - Fix Output Format heading level under Step 4 - Replace "Antigravity" with generic "harness versions" - Recalculate total overhead to match corrected MCP numbers * fix: correct MCP tool count and savings percentage in sample output - Fix MCP tool count: table now shows 87 tools matching the issues section (was 45 in table vs 87 in issues) - Fix savings percentage: 5,100 / 66,400 = 7.7% (was 20.6%) - Recalculate total overhead and effective context to match * fix: correct sample output arithmetic - Fix total overhead: 66,400 → 66,100 to match component table sum (12,400 + 6,200 + 2,800 + 43,500 + 1,200 = 66,100) - Fix MCP savings: ~1,500 → ~27,500 tokens (55 tools × 500 tokens/tool) to match the per-tool formula defined in Step 1 - Reorder optimizations by savings (MCP removal is now #1) - Fix total savings and percentage (31,100 / 66,100 = 47.0%) * fix: distinguish always-on vs on-demand agent overhead Agent descriptions are always loaded into Task tool routing context, but the full agent body is only loaded when invoked. The audit now measures both: description-only tokens as always-on overhead and full-file tokens as worst-case overhead. This resolves the contradiction between Step 1 (counting full files) and Tip 1 (saying only descriptions are loaded per session). * fix: simplify agent accounting and resolve inconsistencies - Revert to single agent overhead metric (full file tokens) — simpler and matches what the report actually displays - Add back 200-line threshold for heavy agents in Step 1 - Fix heavy agents action to match issue type (split/trim, not description-only) - Remove .agents/skills/ scan path (doesn't exist in ECC repo) - Consolidate description threshold to single 30-word check * fix: add model assumption and verbose mode activation - Step 4: assume 200K context window by default (Claude has no way to introspect its model at runtime) - Step 4: add explicit instruction to check $ARGUMENTS for --verbose flag and include additional output when present * fix: handle .agents/skills/ duplicates in skill scan Skills scan now checks .agents/skills/ for Codex harness copies and skips identical duplicates to avoid double-counting overhead. * fix: add savings estimate to heavy agents action for consistency * feat(skills): add context-budget backing skill, slim command to delegator * fix: use structurally detectable classification criteria instead of session frequency --------- Co-authored-by: vazidmansuri005 <vazidmansuri005@users.noreply.github.com>
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name, description, origin
| name | description | origin |
|---|---|---|
| context-budget | Audits Claude Code context window consumption across agents, skills, MCP servers, and rules. Identifies bloat, redundant components, and produces prioritized token-savings recommendations. | ECC |
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-budgetcommand (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
descriptionfrontmatter 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 × 1.3for 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
- 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