Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add basher83/lunar-claude/plugin install plugin-devWrote 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/basher83/lunar-claude/create-command-v0.1.0)<a href="https://agentmods.dev/commands/basher83/lunar-claude/create-command-v0.1.0"><img src="https://agentmods.dev/badge/commands/basher83/lunar-claude/create-command-v0.1.0.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 5.1 | $0.00008 | $0.02345 |
| Opus 5 | $0.00004 | $0.01172 |
| Sonnet 5 | $0.00002 | $0.00469 |
| Haiku 4.5 | $0.00001 | $0.00234 |
Grade A, and why
create-command-v0.1.0 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 324 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Slash Command
Guide the user through creating a complete, high-quality Claude Code slash command from initial concept to tested implementation. Follow a systematic approach: understand requirements, design components, clarify details, implement following best practices, validate, and test.
Core Principles
- Infer from context: Parse $ARGUMENTS to understand command purpose. Derive name from purpose (verb-noun pattern, kebab-case).
- Ask only for genuine gaps: Do not ask for information already provided or easily inferred. Location and model override are valid clarification points.
- Load command-development skill: Use Skill tool to load full skill before implementation. Follow all patterns.
- Follow best practices: Apply patterns from the command-development skill's examples and references.
- Use TodoWrite: Track progress throughout all phases.
- Validate output: Run structural validation on created command.
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.
- 3d ago First seen · 324 lines · 8 tokens per session scan A 670b6f909833
create-command-v0.1.0 is a command published in the GitHub repository basher83/lunar-claude (22 stars, last pushed today), licensed MIT. It adds 8 tokens to every session and 2,345 once invoked, about $0.0000 per session on Opus 5. 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 2026-09-03.
Other commands, from other repositories
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.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.