使用方法
- 复制安装命令,在自己的智能体环境安装前先检查源码包。
- 从原始文档核对所需工具、凭据和支持的宿主。
- 说明输入材料与期望交付物,并对照来源检查输出。
npx skills add https://github.com/gasserane/personal-skills --skill capture-desktop开始前需了解
- 安装不包含模型订阅、API 额度或访问文件的权限。
- 仓库星数和安装量反映活跃情况,不等于独立质量或安全测试。
按源仓库内容呈现,保留标题、案例、代码、表格、链接以及原文引用的演示图片。
Capture Desktop Session
The device-side mirror of scripts/check_desktop_sync.py. That script governs device-to-cloud sync. This skill governs cloud-to-device capture. claude.ai has no API, so capture is paste-driven: Ane pastes a finished Desktop session and this skill routes its content to the right places on disk.
Step 1 — Get the content
Ask Ane to paste the Desktop conversation, or accept a file path if she gives one. If the paste is long, write it to a temp file first to avoid truncation.
Step 2 — Stage the transcript
Run the helper to stage a verbatim, deduplicated transcript:
python scripts/capture_desktop.py stage --input <tempfile> --title "<short title>"- Exit 0: prints the transcript path. Continue.
- Exit 3:
[DUP] already captured— this session was captured before. Tell Ane
and stop unless she confirms she wants to re-route it anyway.
Transcripts are local-only (gitignored, OneDrive-backed). The staged transcript IS the "full log" bucket — no further action for that bucket.
Step 3 — Classify the content
Read the staged transcript. Sort its substantive content into four buckets:
- Deliverables — documents, analyses, tables, drafts Ane produced.
- Decisions / rules / lessons — locked decisions, framework calls, guidance
on how the system should work, feedback on your behaviour. Capture successes as well as corrections: an approach the transcript shows Ane praised, reused, or locked is a success worth banking as a feedback memory (with Why: and How to apply:) so /improve-system trends confirmed successes, not only corrections.
- Project-knowledge changes — edits that belong in canonical sources
(mel_wiki/ pages, ~/.claude/CLAUDE.md).
- Full log — already staged in Step 2. No action.
If a bucket is empty, say so. Do not invent content to fill it.
Step 4 — Route each bucket
Deliverables (auto-file). Propose a path under the work folder, save with the Write tool, and name it in the summary. Apply mel_wiki/wiki/concepts/edit-preservation-protocol.md when target file exists.
Decisions / rules / lessons (confirm each). For each item, propose the target — a memory file under the memory dir, a wiki entry, or a feedback memory — and show the exact content you will write. Get a yes/no from Ane before writing. Apply mel_wiki/wiki/concepts/edit-preservation-protocol.md when target file exists.
Project-knowledge changes (confirm each). For each item, propose the exact edit to the canonical source and get a yes/no. Apply the change with the Edit tool, scope-bounded. Apply mel_wiki/wiki/concepts/edit-preservation-protocol.md when target file exists.
- For
mel_wiki/edits: stage for the work-folder commit in Step 5. - For
~/.claude/CLAUDE.mdedits: after applying, commit cross-repo by running
bash ~/.claude-config-clone/scripts/sync-from-local.sh --auto "capture-desktop: <one-line reason>". This copies live CLAUDE.md into the claude-config clone, reconciles, commits, and pushes. It exits 0 silently if nothing changed.
Step 5 — Close the loop and commit
If any canonical source was edited (wiki or CLAUDE.md), run the sync check so the re-upload flag for the Desktop project fires:
python scripts/check_desktop_sync.pyReport any [DRIFT] it surfaces. Then commit the work-folder changes (deliverables and mel_wiki/ edits only — transcripts are gitignored). Stage by name, never git add -A:
git add <deliverable paths> <mel_wiki paths>
git commit -m "feat(capture): desktop session <slug> — <what landed>"
git pushStep 6 — Report
Deliver a tight summary:
CAPTURE-DESKTOP — <date>
Transcript: desktop-captures/<slug>/transcript.md (local)
Deliverables: <list or none>
Decisions/rules written: <list or none>
Canonical edits: <list or none> (CLAUDE.md pushed to claude-config: yes/no)
Sync check: <in sync / N drift flagged>
Commit: <short-SHA> pushed / nothing to commit

