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/aphrody-code/bxc/create-plugingit clone --depth 1 https://github.com/aphrody-code/bxcWhat 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 yesterday.
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.
This is a copy
100% identical to create-plugin — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
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.
- yesterday First seen · 416 lines · 16 tokens per session scan A b6c0c23196c0
create-plugin is a command published in the GitHub repository aphrody-code/bxc (2 stars, last pushed yesterday), 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. It is 100% identical to create-plugin, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
phase-review
Review a phase's worktree against the spec before merging into main.
release
Cut a Uni-CLI release from a clean main.
verify
Run the full Uni-CLI verification gate and report the outcome.
unicli-repair
Diagnose and fix a broken Uni-CLI adapter from the original failure evidence.
unicli-search
Search any supported website or platform using Uni-CLI.
feature
End-to-end feature/bug-sweep workflow for ui-debugger-mcp — understand, reproduce against a real target, explore in parallel, split into path-disjoint slices, build with a hive of agents in this ONE checkout (never worktrees), gate green, PR, merge, release to npm. Tracks in GitHub issues. Reads intent from the prompt.