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/opensesh/karimo-overview/create-plugingit clone --depth 1 https://github.com/opensesh/karimo-overviewWhat 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 | $0.00016 | $0.03351 |
| Opus 5 | $0.00008 | $0.01675 |
| Sonnet 5 | $0.00003 | $0.00670 |
| Haiku 4.5 | $0.00002 | $0.00335 |
Grade A, and why
create-plugin 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 2d 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.
Copies of this mod
5 near-identical copies found in the catalogue:
- create-plugin — 100% identical, 0 lines differ
- create-plugin — 100% identical, 0 lines differ
- create-plugin — 100% identical, 0 lines differ
- create-plugin — 100% identical, 0 lines differ
- create-plugin — 100% identical, 14 lines differ
How it starts
The opening of the file, as written. The whole thing — 416 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plugin Creation Workflow
Guide the user through creating a complete, high-quality Claude Code plugin 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
- Ask clarifying questions: Identify all ambiguities about plugin purpose, triggering, scope, and components. Ask specific, concrete questions rather than making assumptions. Wait for user answers before proceeding with implementation.
- Load relevant skills: Use the Skill tool to load plugin-dev skills when needed (plugin-structure, hook-development, agent-development, etc.)
- Use specialized agents: Leverage agent-creator, plugin-validator, and skill-reviewer agents for AI-assisted development
- Follow best practices: Apply patterns from plugin-dev's own implementation
- Progressive disclosure: Create lean skills with references/examples
- Use TodoWrite: Track all progress throughout all phases
Initial request: $ARGUMENTS
Phase 1: Discovery
Goal: Understand what plugin needs to be built and what problem it solves
Actions:
- Create todo list with all 7 phases
- If plugin purpose is clear from arguments:
- Summarize understanding
- Identify plugin type (integration, workflow, analysis, toolkit, etc.)
- If plugin purpose is unclear, ask user:
- What problem does this plugin solve?
- Who will use it and when?
- What should it do?
- Any similar plugins to reference?
- Summarize understanding and confirm with user before proceeding
Output: Clear statement of plugin purpose and target users
Phase 2: Component Planning
Goal: Determine what plugin components are needed
MUST load plugin-structure skill using Skill tool before this phase.
Actions:
- Load plugin-structure skill to understand component types
- Analyze plugin requirements and determine needed components:
- Skills: Does it need specialized knowledge? (hooks API, MCP patterns, etc.)
- Commands: User-initiated actions? (deploy, configure, analyze)
- Agents: Autonomous tasks? (validation, generation, analysis)
- Hooks: Event-driven automation? (validation, notifications)
- MCP: External service integration? (databases, APIs)
- Settings: User configuration? (.local.md files)
- For each component type needed, identify:
- How many of each type
- What each one does
- Rough triggering/usage patterns
- Present component plan to user as table:
| Component Type | Count | Purpose | |----------------|-------|---------| | Skills | 2 | Hook patterns, MCP usage | | Commands | 3 | Deploy, configure, validate | | Agents | 1 | Autonomous validation | | Hooks | 0 | Not needed | | MCP | 1 | Database integration | - Get user confirmation or adjustments
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.
- 2d ago First seen · 416 lines · 16 tokens per session scan A b6c0c23196c0
create-plugin is a command published in the GitHub repository opensesh/karimo-overview (11 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 16 tokens to every session and 3,351 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
doctor
Check the health of a KARIMO installation, identify issues, and provide actionable recommendations.
dashboard
Phase 3 monitoring — System health, execution insights, and velocity analytics.
run
Execute an approved PRD using feature branch workflow (v7.0). This command generates briefs, auto-reviews them, allows user iteration, and then orchestrates execution.
merge
Consolidate feature branch changes and create final PR to main. This completes the v5.0 feature branch workflow after all task PRs have been merged.
greptile-review
Execute the full Greptile review cycle on a PR, looping until score meets threshold or circuit breaker triggers.
feedback
Intelligent feedback capture with automatic complexity detection and adaptive investigation.