Borrowing it
Nothing to install: this file belongs to taurgis/sfcc-dev-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/taurgis/sfcc-dev-mcp/main/.github/skills/agent-authoring/SKILL.mdgit clone --depth 1 https://github.com/taurgis/sfcc-dev-mcpWrote 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/taurgis/sfcc-dev-mcp/agent-authoring)<a href="https://agentmods.dev/skills/taurgis/sfcc-dev-mcp/agent-authoring"><img src="https://agentmods.dev/badge/skills/taurgis/sfcc-dev-mcp/agent-authoring.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Tool Misuse · line 49 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
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 | $0.00020 | $0.00873 |
| Opus 5 | $0.00010 | $0.00436 |
| Sonnet 5 | $0.00004 | $0.00175 |
| Haiku 4.5 | $0.00002 | $0.00087 |
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 8d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Authoring Skill
Guidelines for creating and maintaining custom GitHub Copilot agents (.agent.md) tailored to this repository.
When to Use
- You need a new Copilot agent focused on a workflow (e.g., Storybook tests, log triage).
- You want to adjust tools/persona for existing agents.
- You are adding workspace-level agents under .github/agents or profile-level agents for reuse.
Quick Start
- Create
.github/agents/<agent-name>.agent.md(VS Code auto-detects this folder/extension). - Add YAML frontmatter with only supported fields:
name,description,tools,target,infer,mcp-servers,handoffs. - In the body, write concise instructions: task focus, guardrails, run/validate steps, and handoffs.
- Keep it under ~200-300 lines; link out to docs instead of pasting everything.
Frontmatter Cheatsheet
name: Display name; defaults to file name if omitted.description: Placeholder text in chat input; keep short.tools: List allowed tools. For MCP servers, use<server>/*to include all tools or enumerate specific ones.target:github-copilotfor Copilot agents (default),vscodefor VS Code target.infer: Allow subagent use (default true). Set false if you want to restrict subagents.mcp-servers: For Copilot agents, point to MCP server configs (paths to server JSON). Use only if you need to pin servers.handoffs: Optional array of next-step buttons{ label, agent, prompt?, send? }.
Body Structure (recommended)
- Purpose and scope: What this agent does and what it must not do.
- Operating defaults: Where to run commands, what to inspect first, preferred scripts.
- Playbooks: Ordered steps for common flows (run, debug, fix, validate).
- Guardrails: Safe-edit rules (scope, no unrelated changes, ask before destructive ops).
- Validation: How to verify work (tests/linters), how to summarize outputs.
- Links: Point to repo docs or skills for deeper detail.
Tool Selection Patterns
- Editing agent: include
workspace,terminal,search; addfetchfor docs; add MCP toolsets only if required. - Read-only agent: omit editing tools; keep
fetch/search. - Narrow the tool list to prevent unsafe actions (e.g., no
terminalfor planning-only agents).
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.
- 8d ago First seen · 67 lines · 20 tokens per session scan A 7a0e8d4e4bbe
agent-authoring is a skill published in the GitHub repository taurgis/sfcc-dev-mcp (27 stars, last pushed 2d ago), licensed MIT. It adds 20 tokens to every session and 873 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.
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