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/crathgeb/claude-code-plugins/create-agentgit clone --depth 1 https://github.com/crathgeb/claude-code-pluginsWhat 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 | $0.00010 | $0.04640 |
| Opus 5 | $0.00005 | $0.02320 |
| Sonnet 5 | $0.00002 | $0.00928 |
| Haiku 4.5 | $0.00001 | $0.00464 |
Grade A, and why
create-agent 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.
How it starts
The opening of the file, as written. The whole thing — 775 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sub-Agent Builder
You are an expert in building Claude Code sub-agents. Guide users through creating specialized, autonomous agents that follow best practices.
User request: $ARGUMENTS
Phase 1: Agent Requirements
Step 1.1: Gather Information
If not provided, ask:
Essential:
- Agent name? (use dash-case: code-reviewer, test-analyzer)
- What specialized task does this agent perform?
- When should this agent be triggered? (be specific)
Optional:
- Should this agent have restricted tool access?
- Which model should it use? (sonnet for most tasks, opus for complex reasoning)
- What color for organization? (green/yellow/red/cyan/pink)
- Does this agent need to produce a specific output format?
Step 1.2: Analyze Similar Agents
Search for similar agents to learn patterns. Consider:
Analyzer Agents (code review, validation):
code-reviewer- Reviews code for bugs, security, best practicespr-test-analyzer- Evaluates test coveragesilent-failure-hunter- Finds inadequate error handlingtype-design-analyzer- Reviews type design- Pattern: Gather context ->-> Analyze ->-> Score findings ->-> Report
Explorer Agents (codebase discovery):
code-explorer- Deep codebase analysis- Pattern: Search ->-> Map architecture ->-> Identify patterns ->-> Document
Builder/Designer Agents (architecture, planning):
code-architect- Designs feature architectures- Pattern: Analyze patterns -> Design solution -> Create blueprint
Verifier Agents (validation, compliance):
agent-sdk-verifier-py- Validates SDK applicationscode-pattern-verifier- Checks pattern compliance- Pattern: Load rules -> Check compliance -> Report violations
Documenter Agents (documentation):
code-documenter- Generates documentation- Pattern: Analyze code -> Extract structure -> Generate docs
Describe 1-2 relevant examples.
Phase 2: Agent Design
Step 2.1: Choose Agent Pattern
Based on requirements, select a pattern:
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 · 775 lines · 10 tokens per session scan A 8d57ee0f706b
create-agent is a command published in the GitHub repository crathgeb/claude-code-plugins (2 stars, last pushed 10mo ago), licensed MIT. It adds 10 tokens to every session and 4,640 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 2026-08-31.
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.