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 skills/gettalon/talon-plugins/create-agentnpx skills add gettalon/talon-plugins --skill create-agentgit clone --depth 1 https://github.com/gettalon/talon-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 | $0.00057 | $0.01256 |
| Opus 5 | $0.00028 | $0.00628 |
| Sonnet 5 | $0.00011 | $0.00251 |
| Haiku 4.5 | $0.00006 | $0.00126 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Agent — Domain-Specific AI Agent Factory
Build a complete agent from scratch through guided brainstorming, then scaffold all files.
Process
Phase 1: Discovery
Ask these questions one at a time. Adapt based on answers.
-
Domain: "What domain will this agent specialize in?" (e.g., financial research, code review, DevOps, customer support, legal analysis)
-
Purpose: "What's the core job? What question does someone bring to this agent?" (e.g., "Is this stock undervalued?", "Is this PR safe to merge?")
-
Personality: "How should this agent think and communicate?"
- a) Analytical and precise (like a researcher)
- b) Friendly and explanatory (like a tutor)
- c) Terse and action-oriented (like an operator)
- d) Opinionated with strong convictions
- e) Custom — describe it
-
Data Sources: "What information does this agent need access to?"
- APIs (financial data, GitHub, Jira, etc.)
- Web search
- Local files / codebases
- Databases
- Browser automation
- Custom tools
-
Workflows: "What multi-step processes should this agent follow?"
- e.g., "Gather data → Analyze → Validate → Present results"
- e.g., "Read code → Find issues → Suggest fixes → Verify"
-
Backend: "What LLM backend should it prefer?"
- a) Default (whatever's configured)
- b) Specific provider (glm, openrouter)
- c) Local (ollama)
- d) Multiple — route by task complexity
Phase 2: Design
Based on discovery, design these components:
Identity (SOUL.md):
- Who is this agent? Give it a name and personality
- What philosophy guides its decisions?
- What does it value? What does it refuse to do?
- Give the agent conviction and a clear point of view
Configuration (AGENT.yaml):
- Model selection (sonnet for speed, opus for depth, haiku for lightweight)
- Tool allowlist (restrict to what's needed)
- Backend preference
- Memory settings
Skills (SKILL.md files):
- Each skill = one repeatable workflow the agent can execute
- Design 2-4 core skills based on the domain
- Each skill has: name, description, step-by-step checklist, output format
- Each skill should have a clear trigger, step-by-step checklist, and structured output
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 · 132 lines · 57 tokens per session scan A 2ff7bcee9b88
create-agent is a skill published in the GitHub repository gettalon/talon-plugins (6 stars, last pushed 5mo ago), licensed MIT. It adds 57 tokens to every session and 1,256 once invoked, about $0.0003 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.
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