replay
关于
The replay skill helps developers find, analyze, and share AI coding session histories from tools like Cursor or Claude Code. It generates shareable summaries and artifacts, and attaches polished session context to PRs. Use it when a user requests a session replay, needs to find a past session, or wants to include session context in code reviews.
快速安装
Claude Code
推荐npx skills add tuo-lei/vibe-replay -a claude-code/plugin add https://github.com/tuo-lei/vibe-replaygit clone https://github.com/tuo-lei/vibe-replay.git ~/.claude/skills/replay在 Claude Code 中复制并粘贴此命令以安装该技能
技能文档
Session Replay and Search
This skill helps agents find local AI coding sessions, generate shareable replay artifacts, and paste polished session context into PRs. It uses vibe-replay for the raw session discovery, parsing, redaction, analytics, and export work, then uses agent judgment for review, cleanup, and sharing decisions.
What this skill is for
Use this skill when the user asks to:
- Generate a replay or GitHub-ready summary of an AI coding session.
- Attach Claude Code, Cursor, or Codex session context to a PR.
- Find a previous session, transcript, replay, branch discussion, bug investigation, PR, or design thread.
- Remember what happened in a past agent conversation.
- Run a retro on prompt quality, tool usage, errors, compactions, cost, or agent efficiency.
- Compare sessions or choose which session should be replayed/shared.
Plain text summaries of an AI session - stats, tool breakdown, per-prompt details - are hard for an agent to write from scratch. Delegate that to vibe-replay, then use agent reasoning to handle the things a CLI cannot decide well:
- Ranking session search results - choosing the likely match from metadata and brief scan signals.
- Reviewing flagged credentials - deciding whether a regex hit is a real secret or a false positive.
- Translating session prompts that are not in the audience's language.
- Softening tone in prompts written when the user was frustrated.
- Appending to PRs safely - preserving existing PR descriptions instead of overwriting them.
Each cleanup step is opt-in. Ask the user before rewriting their content.
Step 1 - Choose the session
Prefer structured discovery over manually browsing local history.
If the user provides a session path
Use the provided path. Infer the provider when possible:
- Cursor transcripts usually live under
~/.cursor/projects/.../agent-transcripts/.... - Claude Code transcripts usually live under
~/.claude/projects/.../*.jsonl. - Codex sessions are discoverable through
vibe-replay sessions; if the path is not obviously Claude or Cursor, pass the provider returned by search or ask the user.
If this is the current Claude Code session
Find the current session file with ${CLAUDE_SESSION_ID}:
grep -l '"sessionId":"${CLAUDE_SESSION_ID}"' ~/.claude/projects/*/*.jsonl 2>/dev/null
If multiple files match (normal after /resume), pick the oldest. vibe-replay auto-discovers related files by slug/project.
If the user describes a past or fuzzy session
Use vibe-replay sessions first. Prefer --json so results can be ranked without scraping terminal text:
npx vibe-replay sessions --query "<terms>" --limit 10 --json
Useful filters:
npx vibe-replay sessions --project "vibe-replay" --json
npx vibe-replay sessions --provider cursor --query "auth bug" --json
npx vibe-replay sessions --query "codex parser" --scan --json
npx vibe-replay sessions --query "PR review CI" --any --brief --dedupe --json
Search workflow:
- Start shallow with
--queryor--project,--limit 10, and--json. - Rank matches by timestamp, project, title/first prompt match quality, provider, and user intent.
- If a remembered query has several loose terms and returns nothing, retry with
--any. - Add
--briefwhen the user asks a fuzzy retrospective question; it addsmatchQuality, matched/unmatched terms,whyMatched,brief,signals, andsuggestedNextAction. - Add
--dedupewhen repeated long-prompt sessions from multiple workspaces clutter results. - Only add plain
--scanfor a narrowed candidate set when the user asks about retro, efficiency, prompt quality, cost, tool usage, compactions, API errors, files modified, or session quality.
Avoid broad --scan over many sessions. It is intentionally available, but expensive compared with metadata search.
If --json returns an empty array, verify vibe-replay is installed and accessible:
npx vibe-replay --version
Then broaden or drop the query, retry with --any, filter by project/provider, or ask the user for a session path directly.
For search results, return a short ranked list with provider, timestamp, project, title or first prompt preview, slug/session id, why it matched, and whether deeper scan/replay is recommended. Do not dump full raw prompts unless the user asks.
After choosing a session, branch by intent:
- PR sharing or replay export - continue with Steps 2-5, then Step 7.
- Session retro or efficiency analysis - skip PR artifact cleanup and use Step 6.
Step 2 - PR sharing path: generate the artifacts
Once you have a session path and provider, run vibe-replay with the provider when known:
npx vibe-replay --provider <provider> --session <PATH> --github
For Claude Code, --provider claude-code may be omitted because it is the default, but include the provider when it came from vibe-replay sessions. For Cursor, use --provider cursor. For Codex, use --provider codex.
This writes to ~/.vibe-replay/<slug>/:
github-summary.md- the markdown summary to paste into the PR.redactions.json- credential audit report.session-preview.gif/.svg- preview animations; skip unless the user explicitly asks.
If the user asks for an interactive local replay instead of PR artifacts, run:
npx vibe-replay --provider <provider> --session <PATH> --open
Step 3 - Review credential redactions
Read redactions.json. It has two fields:
alreadyRedactedCount- how many secretsvibe-replayalready replaced with[REDACTED]automatically. Just report this number to the user.leftoverFindings- regex hits in the final markdown thatvibe-replaywas not confident enough to auto-redact.
If leftoverFindings is empty, say so and move on.
If leftoverFindings is non-empty, present the findings to the user. For each one:
- Show: rule (e.g. "GitHub Token"), context snippet (one line of surrounding text), and your judgment of whether it looks real
- Note that some matches are false positives - commit hashes, UUIDs, version strings, package names can look like tokens. Use the surrounding context to judge.
- Offer choices: "Redact all", "Review one-by-one", "Keep as-is" (if you believe they're false positives), or "Cancel"
If the user chooses to redact any finding, first copy the original to a working file. Do not overwrite github-summary.md:
cp ~/.vibe-replay/<slug>/github-summary.md ~/.vibe-replay/<slug>/github-summary.clean.md
Then apply replacements to github-summary.clean.md. The original stays intact so the user can recover the unedited version. All later steps (translation, tone) also operate on the .clean.md copy. Create it on the first edit, then keep using it.
Step 4 - Offer translation
Read the working file (github-summary.clean.md if it exists from step 3, otherwise github-summary.md):
cat ~/.vibe-replay/<slug>/github-summary.clean.md 2>/dev/null || cat ~/.vibe-replay/<slug>/github-summary.md
Detect the language of the user-prompt sections. If the dominant language is not English (or does not match the repo's primary language - check README.md if unsure), ask:
"The prompts are in {detected language}. Translate to {target language} before sharing? [Yes / No]"
If yes, apply this prompt to the user-prompt sections of the markdown (always write the result to github-summary.clean.md, creating it from a copy of the original if it doesn't exist yet):
You are a translation assistant for AI coding sessions.
Translate the following user prompts from {source} to {target}.
Rules:
- Only translate natural language text
- Preserve code blocks, file paths, variable names, CLI commands verbatim
- Preserve markdown formatting
- Keep technical jargon in English (API, endpoint, middleware, etc.)
- Maintain the original intent and tone
- If a prompt is already in {target}, return it unchanged
Only rewrite the prompt text. Do not touch tool-call output, file diffs, or stats.
Step 5 - Offer tone softening
Scan the user-prompt sections for harsh language, profanity, frustration, or passive-aggressive tone toward the AI. If you find any, ask:
"Some prompts contain {brief example, e.g. 'frustrated language'}. Soften the tone before sharing? [Professional / Neutral / Friendly / Skip]"
If the user picks a style, apply this prompt to the affected user prompts (write the result to github-summary.clean.md, same rule as step 3):
You are a tone adjustment assistant for AI coding sessions.
Rewrite the following user prompts to be more {style}.
Rules:
- Preserve the EXACT technical meaning and intent
- Remove frustration, harsh language, profanity, or passive-aggressive tone
- Keep code references, file paths, and technical terms unchanged
- If a prompt is already appropriate, return it unchanged
- Do NOT add excessive politeness or corporate-speak - keep it natural
Style guide:
- Professional: direct but respectful, suitable for work sharing
- Neutral: factual and unemotional, like documentation
- Friendly: warm and collaborative, like messaging a teammate
Step 6 - Alternative path: session retro guidance
If the user asked for a session retro instead of PR sharing, do not generate or clean github-summary.md. Narrow the candidate set first, then use scan-backed results:
npx vibe-replay sessions --project "<project>" --limit 5 --scan --json
If the user gave search terms instead of a project, use a narrowed query:
npx vibe-replay sessions --query "<terms>" --limit 5 --scan --json
Separate observations from recommendations.
For efficiency analysis, look at:
- Prompt count and whether the user had to repeat intent.
- Tool calls per prompt and edit count per prompt.
- Long duration, API errors, compactions, and subagent count.
- First prompt clarity: goal, constraints, files, expected verification, and merge/review instructions.
Prefer actionable advice such as "the first prompt had a clear goal but missed verification criteria" or "the session became expensive because it searched broadly before narrowing to one file."
Step 7 - Preview and paste
Show the user the final markdown (or a diff against the original if changes were made). Ask:
"Paste into a PR now? [Append to current PR's body / Replace current PR's body / Open new PR / Just save the file / Cancel]"
Important: gh pr edit --body-file <file> replaces the entire PR body. If the user already has a hand-written summary, checklist, or screenshots in the PR body, replacing wipes them silently. Default to appending under a ## Session Replay heading instead.
To append (recommended default):
# Read existing body, then write existing + separator + cleaned summary
gh pr view --json body --jq .body > /tmp/pr-body.md
SUMMARY=$(ls ~/.vibe-replay/<slug>/github-summary.clean.md 2>/dev/null || echo ~/.vibe-replay/<slug>/github-summary.md)
echo "" >> /tmp/pr-body.md
echo "---" >> /tmp/pr-body.md
echo "" >> /tmp/pr-body.md
echo "## Session Replay" >> /tmp/pr-body.md
echo "" >> /tmp/pr-body.md
cat "$SUMMARY" >> /tmp/pr-body.md
gh pr edit --body-file /tmp/pr-body.md
To replace, only if the user explicitly chooses this, confirm out loud what is about to be lost first:
gh pr edit --body-file ~/.vibe-replay/<slug>/github-summary.clean.md
If saving locally only, the cleaned version is already at ~/.vibe-replay/<slug>/github-summary.clean.md from earlier steps. Just report the path. If no cleanup steps ran, copy the original first so the user has a .clean.md to share without touching the source.
Notes
- The skip-the-image rule still applies: by default, do NOT include the GIF reference (first line of the original markdown) when pasting into a PR. Committing a binary GIF bloats git history. Only include it if the user explicitly asks for the GIF.
github-summary.clean.mdis the only shareable markdown file the skill edits. The originalgithub-summary.mdis treated as read-only so the user can always recover the raw output.- The literal
${CLAUDE_SESSION_ID}is interpolated by the Claude Code harness when this skill runs. If it is empty or no file matches, ask the user which session to use or search withvibe-replay sessions. - Session data may contain private code, credentials, internal links, or frustrated wording. Quote only the minimum needed.
- Treat
vibe-replay sessionsas metadata/subsequence search, not semantic search. If results are weak, broaden terms, filter by project/provider, or inspect a small number of returned transcripts.
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