agent-academy-stargazers
- Repo stars 2,528
- Author updated Live
- Author repo agent-academy
- Domain
- AI
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @microsoft · no license declared
- Token usage
- Lean
- Setup complexity
- Plug-and-play
- External API key
- Not required
- Operating systems
- macOS
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Network behavior
- External requests
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools，默认拥有全部工具权限。
---
name: agent-academy-stargazers
description: > This skill fetches the list of users who have starred the microsoft/agent-academy repository o…
category: ai
runtime: no special runtime
---
# agent-academy-stargazers output preview
## PART A: Task fit
- Use case: > This skill fetches the list of users who have starred the microsoft/agent-academy repository on GitHub. If the user provides a GitHub username, it also checks whether that specific user has starred the repo. makes outbound network calls. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “🏁 Prerequisites / 🛠️ Skill Flow / 📜 Rules” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “> This skill fetches the list of users who have starred the microsoft/agent-academy repository on GitHub. If the user provides a GitHub username, it also checks whether that specific user has starred the repo. makes outbound network calls. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “🏁 Prerequisites / 🛠️ Skill Flow / 📜 Rules” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; may access external network resources; usually needs no extra API key.
## Running Rules
- read files, write/modify files; may access external network resources; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. Choose the trigger
The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Provide inputs and boundaries
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files.
Validate with a small run
Start with a small task and check whether the result follows “🏁 Prerequisites / 🛠️ Skill Flow / 📜 Rules”. Inspect diffs, logs, previews, or tests before expanding scope.
Review before delivery
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: agent-academy-stargazers
description: > This skill fetches the list of users who have starred the microsoft/agent-academy repository o…
category: ai
source: microsoft/agent-academy
---
# agent-academy-stargazers
## When to use
- > This skill fetches the list of users who have starred the microsoft/agent-academy repository on GitHub. If the user…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “🏁 Prerequisites / 🛠️ Skill Flow / 📜 Rules” and keep inference separate from source facts.
- read files, write/modify files; may access external network resources; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. Evidence boundary and execution chain
The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "agent-academy-stargazers" {
input -> user goal + target files + boundaries + acceptance criteria
context -> 🏁 Prerequisites / 🛠️ Skill Flow / 📜 Rules
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files | may access external network resources
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
}Agent Academy Stargazers
This skill fetches the list of users who have starred the microsoft/agent-academy repository on GitHub. If the user provides a GitHub username, it also checks whether that specific user has starred the repo.
🏁 Prerequisites
Before running, verify the gh CLI is installed and authenticated:
- Run
gh --versionto confirm it is installed. If not, install it (e.g.,brew install ghon macOS, or the appropriate package manager for the user's OS). - Run
gh auth statusto confirm it is authenticated. If not, rungh auth loginand guide the user through the interactive authentication flow.
Do not proceed with the rest of the skill until both checks pass.
🛠️ Skill Flow
- Verify the
ghCLI is installed and authenticated (see Prerequisites above). - Fetch the full list of stargazers for the
microsoft/agent-academyrepository usinggh apiwith the--paginateflag to automatically retrieve all pages (the API returns at most 100 results per page, so pagination is required for repos with more than 100 stargazers). Use--jqto select only thelogin,type, andurlfields from each stargazer object. - Save the filtered list to
temp/stargazers.jsonin the repository root. - Tell the user how many stargazers were found and that the list was saved to
temp/stargazers.json. - If the user provided a GitHub username, check whether that username appears in the stargazer list and tell the user the result (e.g., "✅ @username has starred the repo" or "❌ @username has not starred the repo").
📜 Rules
- Always use
gh api --paginateto fetch stargazers formicrosoft/agent-academy, ensuring all pages are retrieved (useper_page=100for efficiency). - Always use
--jq '[.[] | {login, type, url}]'to limit the response to only thelogin,type, andurlfields. Do not store any other fields. - Always save the result to
temp/stargazers.jsonrelative to the repository root, creating thetempdirectory if it does not exist. - Always fetch fresh data from GitHub — never rely on previously fetched results or conversation history.
- If the
ghCLI is not installed, install it using the appropriate package manager for the user's OS (e.g.,brew install ghon macOS) before proceeding. - If the
ghCLI is not authenticated, rungh auth loginand guide the user through authentication before proceeding. - If the API request fails (e.g., network error, repo not found), report the error clearly to the user and do not write a partial or empty file.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review