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 skills add majiayu000/claude-skill-registry --skill agent-authoringgit clone --depth 1 https://github.com/majiayu000/claude-skill-registryWrote 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/skills/majiayu000/claude-skill-registry/agent-authoring)<a href="https://agentmods.dev/skills/majiayu000/claude-skill-registry/agent-authoring"><img src="https://agentmods.dev/badge/skills/majiayu000/claude-skill-registry/agent-authoring/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/majiayu000/claude-skill-registry/agent-authoring"><img src="https://agentmods.dev/badge/skills/majiayu000/claude-skill-registry/agent-authoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 161 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Data Exfiltration · line 299 Code scans file system directories looking for sensitive files. This could be reconnaissance for credential theft.Fix: Remove unnecessary filesystem scanning. If file access is needed, use explicit, scoped paths. Avoid reading ~/.ssh, ~/.aws, or credential directories.
- medium Rogue Agent · line 323 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Excessive Agency · line 479 Skill grants unrestricted tool access without appropriate constraints. An agent with unfettered tool access can perform arbitrary actions including file modification, network requests, and code execution.Fix: Restrict tool access to only the tools required for the skill's stated purpose. Use an explicit allowlist rather than granting blanket access.
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 | $0.00038 | $0.03339 |
| Opus 5 | $0.00019 | $0.01670 |
| Sonnet 5 | $0.00008 | $0.00668 |
| Haiku 4.5 | $0.00004 | $0.00334 |
Grade A, and why
agent-authoring 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 9d 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 — 546 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reference Files
Advanced agent authoring guidance:
- design-patterns.md - Proven agent patterns with examples
- examples.md - Complete agent examples with analysis
- agent-decision-guide.md - Deciding when to use agents vs skills vs commands
- comparison-with-official.md - Comparison with Anthropic's official agents
About Agents
Agents are specialized AI assistants that run in separate subprocesses with focused expertise. They have:
- Specific focus areas - Clearly defined areas of expertise
- Model choice - Sonnet, Opus, or Haiku depending on complexity
- Tool restrictions - Limited to only the tools they need
- Permission modes - Control over how they interact with the system
- Isolated context - Run separately from the main conversation
When to use agents:
- Task requires specialized expertise
- Need different model than main conversation
- Want to restrict tools for security/focus
- Task benefits from isolated context
- Can be invoked automatically or manually
Core Principles
1. Clear Focus Areas
Focus areas define what the agent is expert in. They should be:
Specific, not generic:
- ❌ "Python programming"
- ✅ "FastAPI REST APIs with SQLAlchemy ORM and pytest testing"
Concrete, with examples:
- ❌ "Best practices"
- ✅ "Defensive programming with strict error handling"
5-15 focus areas that cover the agent's expertise comprehensively.
Example from evaluator agent:
## Focus Areas
- YAML Frontmatter Validation
- Markdown Structure
- Tool Permissions
- Description Quality
- File Organization
- Progressive Disclosure
- Integration Patterns
2. Model Selection (Keep It Simple)
Sonnet (default choice for most agents):
- Balanced cost and capability
- Handles most programming tasks
- Good for analysis and code generation
- Use unless you have a specific reason not to
Haiku (for simple, fast tasks):
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 546 lines · 38 tokens per session scan A ef96e72d629d
agent-authoring is a skill published in the GitHub repository majiayu000/claude-skill-registry (606 stars, last pushed today), licensed MIT. It adds 38 tokens to every session and 3,339 once invoked, about $0.0002 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.
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