Agent skill

vardoger-analyze

Use when the user asks to personalize the GitHub Copilot CLI assistant, adapt Copilot to their style, use vardoger, or analyze their Copilot CLI conversation history. Reads the local session directory at `~/.copilot/session-state/`, extracts recurring preferences and conventions, and writes a fenced personalization block into `~/.copilot/copilot-instructions.md`. Runs entirely on the user's machine via the local `vardoger` CLI (`pipx install vardoger`); no network calls and no uploads. Triggers: 'personalize my copilot', 'analyze my copilot history', 'tailor copilot to me', 'run vardoger', 'up

GitHub68,948★ · +463/wk · 2 repos on radarProfile →
copilotMIT
Install
npx skills add github/awesome-copilot --skill vardoger-analyze --agent copilot

Same command for any agent — swap --agent for claude-code, codex, cursor.

Facts
Files in the skill folder: 1
SKILL.md size: 5 KB
Bundled scripts: none
Path: skills/vardoger-analyze/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 37,432 · +281 this week
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Analyze Copilot CLI history and generate personalized instructions Drive the local `vardoger` CLI to read the user's GitHub Copilot CLI conversation history, extract behavioral patterns, and write a personalization block into `~/.copilot/copilot-instructions.md`. ## How it works `vardoger` prepares the history in batches. You (the assistant) summarize each batch for behavioral signals, then synthesize all summaries into a final personalization. `vardoger` writes the result, fenced by `<!-- vardoger:start -->` / `<!-- vardoger:end -->` markers so any hand-authored rules in the same file are preserved. ## Sandbox note (read before running any command) `vardoger` reads and writes files **outside** the current workspace: - Reads Copilot CLI history from `~/.copilot/session-state/`. - Writes a checkpoint state file to `~/.vardoger/state.json` (created on first run). - Writes the final personalization to `~/.copilot/copilot-instructions.md`. When the host asks to approve a `vardoger` command, grant it write access beyond the workspace. Otherwise the first `vardoger prepare` call will fail with `PermissionError: ... ~/.vardoger/state.tmp` because the sandbox blocks writes outside the cu

What's inside
Steps it walks through
  1. How it works
  2. Sandbox note (read before running any command)
  3. Workflow
  4. Steps
  5. 1. Verify vardoger is installed
  6. 2. Check if a refresh is needed
  7. 3. Get batch metadata
  8. 4. Summarize each batch
  9. 5. Get the synthesis prompt
  10. 6. Synthesize the personalization
  11. 7. Write the result
  12. 8. Report to the user
  13. When to use
Commands it runs
if ! command -v vardoger >/dev/null 2>&1; then
cat <<'INSTALL_EOF'
exit 1
fi
vardoger status --platform copilot --json
vardoger prepare --platform copilot
vardoger prepare --platform copilot --batch 1
vardoger prepare --platform copilot --synthesize
echo "YOUR_PERSONALIZATION_HERE" | vardoger write --platform copilot --scope global
More from awesome-copilot
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About this skill
What does the vardoger-analyze skill do?

Use when the user asks to personalize the GitHub Copilot CLI assistant, adapt Copilot to their style, use vardoger, or analyze their Copilot CLI conversation history. Reads the local session directory at `~/.copilot/session-state/`, extracts recurring preferences and conventions, and writes a fenced personalization block into `~/.copilot/copilot-instructions.md`. Runs entirely on the user's machine via the local `vardoger` CLI (`pipx install vardoger`); no network calls and no uploads. Triggers: 'personalize my copilot', 'analyze my copilot history', 'tailor copilot to me', 'run vardoger', 'up

How do I install it?

Run `npx skills add github/awesome-copilot --skill vardoger-analyze --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From github/awesome-copilot, a repository with 37,432 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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