Borrowing it
Nothing to install: this file belongs to timothywarner-org/copilot-cert-prep. 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/timothywarner-org/copilot-cert-prep/main/.github/prompts/gh300-practice-lab.prompt.mdgit clone --depth 1 https://github.com/timothywarner-org/copilot-cert-prepWrote 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/commands/timothywarner-org/copilot-cert-prep/gh300-practice-lab)<a href="https://agentmods.dev/commands/timothywarner-org/copilot-cert-prep/gh300-practice-lab"><img src="https://agentmods.dev/badge/commands/timothywarner-org/copilot-cert-prep/gh300-practice-lab/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/commands/timothywarner-org/copilot-cert-prep/gh300-practice-lab"><img src="https://agentmods.dev/badge/commands/timothywarner-org/copilot-cert-prep/gh300-practice-lab.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00421 |
| Opus 5.5 | $0.00008 | $0.00168 |
| Sonnet 5.5 | $0.00004 | $0.00084 |
| Haiku 4.5 | $0.00002 | $0.00042 |
Grade A, and why
gh300-practice-lab 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 1mo 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.
What it actually says
GH-300 Practice Exercise
Generate ONE short, self-validating GH-300 hands-on exercise.
Use this skill
You must follow the workspace skill gh300-lab-creator for exercise structure, guardrails, workflow, output format, and delivery rules.
Inputs (from chat)
- Skill area: ${input:skillArea:Pick a GH-300 skill area (or leave blank and the agent picks one)}
- Objective: ${input:objective:Specific objective to practice (optional)}
- Tool preference: ${input:toolPreference:VS Code | GitHub.com | CLI (default VS Code)}
- Timebox: ${input:timebox:Duration in minutes (default 15)}
Grounding and validation rules
- Ground the exercise in Microsoft Learn using the Microsoft Learn MCP server.
- If command syntax is included, confirm it with
microsoft_code_sample_searchwhen possible. - Provide Microsoft Learn URLs in the References section.
Key rules
- Randomize the fictional company name from
references/fictional-companies.md. - Follow all style rules from
references/style-guide.md. - Default to VS Code + Copilot Chat if no tool preference is specified.
- All product names must use current terminology.
- No contractions. Rollback is mandatory.
Output format
Use the YAML output format defined in the gh300-lab-creator skill exactly. The output must include: title, objective, skill_area, estimated_time, prerequisites, starting_state, tasks (each with steps and validation), troubleshooting, cleanup, and references.
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.
- 1mo ago Changed · +4 lines 7dcb215f2575
- 1mo ago First seen · 42 lines · 20 tokens per session scan A 8c73cdb6acbf
gh300-practice-lab is a command published in the GitHub repository timothywarner-org/copilot-cert-prep (97 stars, last pushed 1mo ago), licensed MIT. It adds 20 tokens to every session and 421 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-08.
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