Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/janekbaraniewski/openusage/design-featuregit clone --depth 1 https://github.com/janekbaraniewski/openusageWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/janekbaraniewski/openusage/design-feature)<a href="https://agentmods.dev/commands/janekbaraniewski/openusage/design-feature"><img src="https://agentmods.dev/badge/commands/janekbaraniewski/openusage/design-feature.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.00251 |
| Opus 5 | $0.00000 | $0.00125 |
| Sonnet 5 | $0.00000 | $0.00050 |
| Haiku 4.5 | $0.00000 | $0.00025 |
Grade A, and why
design-feature scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Design a new feature "$ARGUMENTS" for the OpenUsage TUI dashboard.
Read and follow the full skill specification in docs/skills/design-feature/SKILL.md.
Follow all phases in order:
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Phase 0 — Quiz: Ask me all 8 questions from the skill doc before doing any design work. If I provided the feature name as "$ARGUMENTS", use that as the starting point but still confirm details. Research the codebase yourself if I don't know an answer.
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Phase 1 — Explore: Read the subsystem map in docs/skills/design-feature/references/subsystem-map.md, then read the primary files for every affected subsystem. Read any overlapping design docs in docs/. Summarize what you learned that affects the design.
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Phase 2 — Design: Write the design doc to docs/<FEATURE_NAME>_DESIGN.md following the template in docs/skills/design-feature/references/design-template.md. Keep it simple — no unnecessary abstractions.
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Phase 3 — Tasks: Break the design into concrete, ordered implementation tasks with specific files and tests. Append to the design doc.
Complete the full checklist at the end of the skill doc before finishing.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 16 lines · 0 tokens per session scan A 5da5b822f91f
design-feature is a command published in the GitHub repository janekbaraniewski/openusage (185 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 251 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.