Analyze token overhead across every loaded component in a Claude Code session and surface actionable optimizations to reclaim context space.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versioncontext-budgetExecute the skills CLI command in your project's root directory to begin installation:
Fetches context-budget from affaan-m/everything-claude-code and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate context-budget. Access via /context-budget in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Analyze token overhead across every loaded component in a Claude Code session and surface actionable optimizations to reclaim context space.
/context-budget command (this skill backs it)Scan all component directories and estimate token consumption:
Agents (agents/*.md)
description frontmatter lengthSkills (skills/*/SKILL.md)
.agents/skills/ — skip identical copies to avoid double-countingRules (rules/**/*.md)
MCP Servers (.mcp.json or active MCP config)
gh, git, npm, supabase, vercel)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%
words × 1.3 for prose, chars / 4 for code-heavy filesMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Useful defaults in context-budget — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: context-budget is focused, and the summary matches what you get after install.
context-budget fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added context-budget from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Keeps context tight: context-budget is the kind of skill you can hand to a new teammate without a long onboarding doc.
context-budget has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for context-budget matched our evaluation — installs cleanly and behaves as described in the markdown.
context-budget fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend context-budget for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
context-budget has been reliable in day-to-day use. Documentation quality is above average for community skills.
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