model-usage
Per-model cost summaries from CodexBar CLI logs for Codex or Claude providers.
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What it does
Supports two summary modes: \"current\" (most recent daily model with highest cost) and \"all\" (full model breakdown across all logged days)
Accepts input via live CodexBar CLI invocation, JSON file, or stdin; outputs as plain text or formatted JSON
Requires CodexBar CLI installed locally (macOS only via Homebrew; Linux support pending)
Falls back to last entry in modelsUsed when model breakdowns are u
Installation Guide
How to use model-usage on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
model-usage
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches model-usage from steipete/clawdis and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate model-usage. Access via /model-usage in your agent's command palette.
Security Notice
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.
Documentation
Model usage
Overview
Get per-model usage cost from CodexBar's local cost logs. Supports "current model" (most recent daily entry) or "all models" summaries for Codex or Claude.
TODO: add Linux CLI support guidance once CodexBar CLI install path is documented for Linux.
Quick start
- Fetch cost JSON via CodexBar CLI or pass a JSON file.
- Use the bundled script to summarize by model.
python {baseDir}/scripts/model_usage.py --provider codex --mode current
python {baseDir}/scripts/model_usage.py --provider codex --mode all
python {baseDir}/scripts/model_usage.py --provider claude --mode all --format json --pretty
Current model logic
- Uses the most recent daily row with
modelBreakdowns. - Picks the model with the highest cost in that row.
- Falls back to the last entry in
modelsUsedwhen breakdowns are missing. - Override with
--model <name>when you need a specific model.
Inputs
- Default: runs
codexbar cost --format json --provider <codex|claude>. - File or stdin:
codexbar cost --provider codex --format json > /tmp/cost.json
python {baseDir}/scripts/model_usage.py --input /tmp/cost.json --mode all
cat /tmp/cost.json | python {baseDir}/scripts/model_usage.py --input - --mode current
Output
- Text (default) or JSON (
--format json --pretty). - Values are cost-only per model; tokens are not split by model in CodexBar output.
References
- Read
references/codexbar-cli.mdfor CLI flags and cost JSON fields.
List & Monetize Your Skill
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Use Cases
User Story & Requirements Generation
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
Competitive Analysis
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
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
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
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ 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.
Learning Path
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
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Reviews
- SShikha Mishra★★★★★Dec 16, 2024
I recommend model-usage for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- GGanesh Mohane★★★★★Dec 12, 2024
We added model-usage from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- RRen Martinez★★★★★Dec 8, 2024
Keeps context tight: model-usage is the kind of skill you can hand to a new teammate without a long onboarding doc.
- OOmar Perez★★★★★Dec 4, 2024
Solid pick for teams standardizing on skills: model-usage is focused, and the summary matches what you get after install.
- MMeera Liu★★★★★Nov 27, 2024
model-usage is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- CCharlotte Srinivasan★★★★★Nov 23, 2024
model-usage reduced setup friction for our internal harness; good balance of opinion and flexibility.
- RRen Martin★★★★★Nov 23, 2024
Registry listing for model-usage matched our evaluation — installs cleanly and behaves as described in the markdown.
- SSakshi Patil★★★★★Nov 3, 2024
model-usage fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- CChaitanya Patil★★★★★Oct 22, 2024
Registry listing for model-usage matched our evaluation — installs cleanly and behaves as described in the markdown.
- OOmar Ndlovu★★★★★Oct 18, 2024
Useful defaults in model-usage — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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