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-study-planner.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-study-planner)<a href="https://agentmods.dev/commands/timothywarner-org/copilot-cert-prep/gh300-study-planner"><img src="https://agentmods.dev/badge/commands/timothywarner-org/copilot-cert-prep/gh300-study-planner/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-study-planner"><img src="https://agentmods.dev/badge/commands/timothywarner-org/copilot-cert-prep/gh300-study-planner.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 | $0.00373 |
| Opus 5.5 | $0.00008 | $0.00149 |
| Sonnet 5.5 | $0.00004 | $0.00075 |
| Haiku 4.5 | $0.00002 | $0.00037 |
Grade A, and why
gh300-study-planner 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 Study Planner
Generate a personalized GH-300 study plan based on your confidence across the six exam skill areas.
Use this skill
You must follow the workspace skill gh300-study-planner for workflow, output format, and delivery rules.
Inputs (from chat)
- Responsible AI confidence: ${input:responsibleAI:Strong | Moderate | Weak | Unknown}
- Copilot features confidence: ${input:features:Strong | Moderate | Weak | Unknown}
- Data and architecture confidence: ${input:dataArchitecture:Strong | Moderate | Weak | Unknown}
- Prompt engineering confidence: ${input:prompting:Strong | Moderate | Weak | Unknown}
- Developer productivity confidence: ${input:productivity:Strong | Moderate | Weak | Unknown}
- Privacy and exclusions confidence: ${input:privacy:Strong | Moderate | Weak | Unknown}
Grounding and validation rules
- Ground all Microsoft Learn module links using the Microsoft Learn MCP server. Do not invent URLs.
- Use the GH-300 exam outline from
references/gh300-objectives.mdfor objective mapping. - Prioritize weak areas first. Within equal confidence levels, prioritize by exam weight.
Key rules
- All product names must use current terminology.
- No contractions.
- Do not skip any skill area, even if rated Strong.
- Treat "Unknown" the same as "Weak."
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 e149eb7f6960
- 1mo ago First seen · 39 lines · 20 tokens per session scan A 4e363484beae
gh300-study-planner 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 373 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.
Other commands, from other repositories
learn-story-flow
Learn story-flow concepts with interactive guidance for junior developers.
start-10-1
A guided lesson on setting up clasp, a command-line tool for managing Google Apps Script projects, and connecting it to Google’s Apps Script API.
start-0-8
A Japanese-language command that displays the current project setup progress.
setup-m365cli.es
Lesson command — Setup de M365 CLI.
prep-role
Deep prep for a specific role's interview process. The user wants to know what to expect, how to win, and what kills candidates at their level.
setup-vercel.es
Command "setup-vercel.es" from minicoohei/ai-agent-camp, covering configuración de vercel cli, step 0: verificar progreso de configuración, lo que hará en esta sesión, verificación de preparación and step 1: crear cuenta de vercel.