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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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description
| description |
|---|
| Analyze context window usage across agents, skills, MCP servers, and rules to find optimization opportunities. Helps reduce token overhead and avoid performance warnings. |
Context Budget Optimizer
Analyze your Claude Code setup's context window consumption and produce actionable recommendations to reduce token overhead.
Usage
/context-budget [--verbose]
- Default: summary with top recommendations
--verbose: full breakdown per component
$ARGUMENTS
What to Do
Run the context-budget skill (skills/context-budget/SKILL.md) with the following inputs:
- Pass
--verboseflag if present in$ARGUMENTS - Assume a 200K context window (Claude Sonnet default) unless the user specifies otherwise
- Follow the skill's four phases: Inventory → Classify → Detect Issues → Report
- Output the formatted Context Budget Report to the user
The skill handles all scanning logic, token estimation, issue detection, and report formatting.