Vardoger Analyze

Vardoger Copilot history analysis

Drive the local vardoger CLI to summarize GitHub Copilot CLI conversation history in batches, synthesize durable behavioral instructions, and write an idempotent fenced block into the user's Copilot instructions file.

When to invoke

• "Personalize my Copilot from my CLI history."
• "Analyze my Copilot history with vardoger."
• "Tailor GitHub Copilot to my style."
• "Run vardoger and update my Copilot instructions."
• "Make Copilot learn my style from previous sessions."

Prerequisites and context

• vardoger must be installed locally. Recommended install: pipx install vardoger; non-install execution can use uvx vardoger --help.
• The workflow runs entirely on the user's machine with no network calls and no uploads.
• vardoger reads GitHub Copilot CLI history from ~/.copilot/session-state/.
• It writes checkpoint state to ~/.vardoger/state.json, creating it on first run.
• It writes global personalization to ~/.copilot/copilot-instructions.md between <!-- vardoger:start --> and <!-- vardoger:end -->, preserving hand-authored rules outside that block.
• For project scope, write with --scope project --project <path> instead of --scope global.

Sandbox and permission rule

vardoger reads and writes outside the current workspace. When the host asks to approve a vardoger command, grant write access beyond the workspace. Without that approval, the first vardoger prepare call can fail with PermissionError: ... ~/.vardoger/state.tmp because the sandbox blocks writes outside the project.

Procedure

1. Verify vardoger is on PATH:

if ! command -v vardoger >/dev/null 2>&1; then
  cat <<'INSTALL_EOF'
vardoger CLI is not installed.

This skill calls the vardoger CLI to read your Copilot CLI history and
write a personalization file, so the CLI must be on PATH.

Install options:

  # Recommended:
  pipx install vardoger

  # Or run without installing:
  uvx vardoger --help

If you do not have pipx, see https://pipx.pypa.io/stable/.

Project page: https://github.com/dstrupl/vardoger

After installing, re-run the personalization request.
INSTALL_EOF
  exit 1
fi

2. Check staleness:

vardoger status --platform copilot --json

If the output shows "is_stale": false, report that personalization is fresh and stop unless the user explicitly asked to force a rerun.

3. Get batch metadata:

vardoger prepare --platform copilot

This returns JSON such as {"batches": 3, "total_conversations": 29}. Record the batch count and total conversations.

4. For each batch number from 1 to N, run:

vardoger prepare --platform copilot --batch 1

Read the summarization prompt and conversation data, then write a concise bullet summary of behavioral signals. Repeat with --batch 2, --batch 3, and so on.

5. Get the synthesis prompt:

vardoger prepare --platform copilot --synthesize

6. Combine all batch summaries into one clean markdown personalization that follows the synthesis prompt.

7. Write the result:

echo "YOUR_PERSONALIZATION_HERE" | vardoger write --platform copilot --scope global

Replace YOUR_PERSONALIZATION_HERE with the actual markdown. Use --scope project --project <path> only when the user requested project-scoped personalization.

8. Report what was written, where it was written, and that reruns are idempotent because the fenced vardoger block is replaced.

Personalization content rules

Troubleshooting

Command forms

Use the exact batch command form vardoger prepare --platform copilot --batch <N> in generalized instructions, then substitute the concrete number when executing. Use the exact synthesis command vardoger prepare --platform copilot --synthesize. Each batch summary should be a bullet-point summary so synthesis can compare behavioral signals consistently.

Output template

## Vardoger personalization result

**Status:** written | fresh | blocked
**Scope:** global | project
**History source:** `~/.copilot/session-state/`
**Destination:** `~/.copilot/copilot-instructions.md` or `<project path>`

### Batch summary
| Batch | Conversations | Behavioral signals |
| --- | --- | --- |
| `<n>` | `<count>` | `<concise summary>` |

### Written personalization
<summary of durable instructions written; do not paste sensitive conversation content>

### Validation
- `vardoger status --platform copilot --json`: <result>
- `vardoger prepare --platform copilot`: <result>
- `vardoger write --platform copilot --scope <scope>`: <result>

Quality gate

• vardoger installation was verified before running prepare or write commands.
• Staleness was checked with vardoger status --platform copilot --json.
• Every batch from vardoger prepare --platform copilot was summarized before synthesis.
• The synthesis prompt was fetched with --synthesize before writing.
• The write used vardoger write --platform copilot --scope global or an explicitly requested project scope.
• The report states the destination file and idempotent fenced block behavior.
• No sensitive data, credentials, or raw private conversation content is pasted into the final report.

References

• pipx documentation
• vardoger project