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Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when…
Audits Claude Code context window consumption across agents, skills, MCP servers, and rules. Identifies bloat, redundant components, and produces prioritized token-savings recommendations. Use when the context window is filling up too fast and the agents, skills, MCP servers, or
$ npx -y skills add affaan-m/ECC --skill context-budget --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/context-budgetContext preview
The summary Claude sees to decide when to auto-load this skill.
Audits Claude Code context window consumption across agents, skills, MCP servers, and rules. Identifies bloat, redundant components, and produces prioritized token-savings recommendations. Use when the context window is filling up too fast and the agents, skills, MCP servers, or
name: context-budget description: Audits Claude Code context window consumption across agents, skills, MCP servers, and rules. Identifies bloat, redundant components, and produces prioritized token-savings recommendations. Use when the context window is filling up too fast and the agents, skills, MCP servers, or rules consuming it need to be identified. metadata: origin: ECC
Analyze token overhead across every loaded component in a Claude Code session and surface actionable optimizations to reclaim context space.
Scan all component directories and estimate token consumption:
**Agents** (`agents/*.md`)
**Skills** (`skills/*/SKILL.md`)
**Rules** (`rules/**/*.md`)
**MCP Servers** (`.mcp.json` or active MCP config)
**CLAUDE.md** (project + user-level)
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 |
Identify the following problem patterns:
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 │ └─────────────────┴────────┴───────────┘ WARNING: 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.
**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%Your agent can write code, but ECC gives it a coordinated engineering system and toolbox: it plans before it builds, verifies changes with tests, reviews its own work from a fresh context, remembers what matters, and turns repeated wins into reusable skills
Repo: affaan-m/ECC
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