Modeling Conversion Metrics
PostHog/posthog
Build reusable conversion models — funnel/step conversion rates, drop-off, and time-to-convert — on either PostHog data-warehouse views (HogQL) or an external dbt project.
Recover and review local human-AI conversations from Claude Code, Codex, opencode, Grok Build, and Cursor.
Apache-2.0Auto-check passed
Install Review AI Conversations
$ npx skills add shareAI-lab/lab-skills --skill review-ai-conversations -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install shareAI-lab/lab-skills review-ai-conversations --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/shareAI-lab/lab-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/research-analysis/review-ai-conversations .claude/skills/review-ai-conversations && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "review-ai-conversations" agent skill from https://github.com/shareAI-lab/lab-skills/tree/main/research-analysis/review-ai-conversations into .claude/skills/review-ai-conversations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-ai-conversations", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/shareAI-lab/lab-skills/tree/main/research-analysis/review-ai-conversationsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add shareAI-lab/lab-skills --skill review-ai-conversations -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install shareAI-lab/lab-skills review-ai-conversations --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shareAI-lab/lab-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/research-analysis/review-ai-conversations .agents/skills/review-ai-conversations && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "review-ai-conversations" agent skill from https://github.com/shareAI-lab/lab-skills/tree/main/research-analysis/review-ai-conversations into .agents/skills/review-ai-conversations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-ai-conversations", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add shareAI-lab/lab-skills --skill review-ai-conversations -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install shareAI-lab/lab-skills review-ai-conversations --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shareAI-lab/lab-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/research-analysis/review-ai-conversations .cursor/skills/review-ai-conversations && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "review-ai-conversations" agent skill from https://github.com/shareAI-lab/lab-skills/tree/main/research-analysis/review-ai-conversations into .cursor/skills/review-ai-conversations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-ai-conversations", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/shareAI-lab/lab-skills.git --path research-analysis/review-ai-conversations--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add shareAI-lab/lab-skills --skill review-ai-conversations -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install shareAI-lab/lab-skills review-ai-conversations --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shareAI-lab/lab-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/research-analysis/review-ai-conversations .gemini/skills/review-ai-conversations && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "review-ai-conversations" agent skill from https://github.com/shareAI-lab/lab-skills/tree/main/research-analysis/review-ai-conversations into .gemini/skills/review-ai-conversations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-ai-conversations", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install shareAI-lab/lab-skills review-ai-conversationsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add shareAI-lab/lab-skills --skill review-ai-conversations -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/shareAI-lab/lab-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/research-analysis/review-ai-conversations .github/skills/review-ai-conversations && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "review-ai-conversations" agent skill from https://github.com/shareAI-lab/lab-skills/tree/main/research-analysis/review-ai-conversations into .github/skills/review-ai-conversations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-ai-conversations", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add shareAI-lab/lab-skills --skill review-ai-conversations -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install shareAI-lab/lab-skills review-ai-conversations --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shareAI-lab/lab-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/research-analysis/review-ai-conversations .opencode/skills/review-ai-conversations && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "review-ai-conversations" agent skill from https://github.com/shareAI-lab/lab-skills/tree/main/research-analysis/review-ai-conversations into .opencode/skills/review-ai-conversations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-ai-conversations", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
review-ai-conversations- GitHub stars
- 315
- Token cost
- ~1.1k tokens
- SKILL.md length
- 447 words
- Files
- 12 (incl. references)
- Skills in repo
- 10
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Recover and review local human-AI conversations from Claude Code, Codex, opencode, Grok Build, and Cursor.
- Works in 4 steps: Read references/retrieval.md completely. → Read only the matching product adapter… → Read references/lineage-and-intent.md only → …
- The user wants to revisit
- SKILL.md covers Interpret ordinary-language…, Load only the required guidance, Preserve the requested truth and Avoid low-value behavior, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Review AI Conversations is an agent skill from shareAI-lab/lab-skills. Recover and review local human-AI conversations from Claude Code, Codex, opencode, Grok Build, and Cursor. Use when the user wants to revisit, search, extract, summarize, or compare work across Agent session stores, time ranges, projects, or named conversations. Follow the user's requested output; question clustering, problem-space mapping, artifact review, drift analysis, and insights are optional lenses.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including reference files (for example `references/adapter-maintenance-evidence.md`, `references/analysis-lenses.md` and `references/lineage-and-intent.md`).
The repository describes itself as: Skills distilled from the Lab's real work and collaboration practices. The licence is Apache-2.0.
When your agent uses it
- The user wants to revisit
- Compare work across Agent session stores
- Named conversations
Example prompts
- “/review-ai-conversations”
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Read references/retrieval.md completely.
- Read only the matching product adapter completely
- Read references/lineage-and-intent.md only
- Read references/analysis-lenses.md only when the
What it can do on your machine
Read from SKILL.md and the folder at commit becee99. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Review AI Conversations loads about 1.1k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 108 tokens; SKILL.md has 447 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from shareAI-lab/lab-skills at commit becee99, republished under its Apache-2.0 licence (© shareAI-lab). 447 words, ~1,067 tokens.
Download SKILL.mdSave it as
.claude/skills/review-ai-conversations/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.- name
- review-ai-conversations
- description
- Recover and review local human-AI conversations from Claude Code, Codex, opencode, Grok Build, and Cursor. Use when the user wants to revisit, search, extract, summarize, or compare work across Agent session stores, time ranges, projects, or named conversations. Follow the user's requested output; question clustering, problem-space mapping, artifact review, drift analysis, and insights are optional lenses.
Review AI Conversations
Recover the actual conversation bodies, then perform only the review, search, extraction, summary, comparison, or synthesis the user requested.
scope -> recover human + visible AI turns -> requested result
|
`-> optional deeper analysis only when requestedThe user's original messages are authoritative for intent. AI replies, summaries, and generated artifacts are useful prior work, not automatic proof that an interpretation or factual claim is correct.
Interpret ordinary-language scope
Infer four things when supplied: Agent or location, time range or conversation IDs, content to find or analyze, and desired output. The user may specify any subset. Ask only when two plausible scopes would materially change the recovered conversations or answer. An explicit file, Store path, session ID, or named conversation does not need time-index discovery.
Load only the required guidance
If the user supplied conversation text directly, analyze it without Store references.
When local Stores must be read:
- Read
references/retrieval.mdcompletely. - Read only the matching product adapter completely:
- Read
references/lineage-and-intent.mdonly when forks, child Agents, copied history, context rollover, or intent drift matter. - Read
references/analysis-lenses.mdonly when the user requests question clustering, problem-space mapping, artifact/conclusion review, brainstorming, open questions, or insights.
For several products, recover each Store independently. Combine recovered
conversation families only after applying each product's identity and lineage rules.
Do not load unrelated product adapters. Do not read
adapter-maintenance-evidence.md during
ordinary review; read it only when maintaining or re-verifying adapters.
Preserve the requested truth
- Keep accepted human-authored text and visible assistant replies in order.
- Preserve an exact message reference with every important extracted passage.
- Distinguish active conversation, abandoned branch, derived summary, delegated child task, and missing history when the distinction affects the request.
- Inspect an actual document or code artifact instead of relying only on an AI claim when the user requested artifact, decision, implementation, or factual verification.
Show full SKILL.md (151 more words)Show less
Avoid low-value behavior
- Do not stop at file discovery, session counts, or an intermediate transcript export.
- Do not merge duplicate projections, copied fork prefixes, child prompts, or compaction summaries into new human intent.
- Do not force clustering, diagrams, insights, open minds, or next actions when the user requested simple recovery, search, extraction, or summary.
- Do not hide uncertainty when the Store cannot distinguish two plausible timelines.
Report to the requested depth
Follow the user's requested format first. For a substantial synthesis, lead with the answer, keep the structure compact, and use Markdown box-line diagrams only when they make relationships materially clearer. Roughly 3,000-5,000 Chinese characters may be useful for a requested deep review, but is never a target for ordinary recovery.
The task is complete when the selected conversation text was recovered faithfully and the requested review or extraction was answered without silently promoting derived AI context into original human intent.
© shareAI-lab, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 11 other files (references) in research-analysis/review-ai-conversations of shareAI-lab/lab-skills.
- SKILL.md
- references/adapter-maintenance-evidence.md
- references/analysis-lenses.md
- references/lineage-and-intent.md
- references/retrieval.md
- references/sources/claude-code.md
- references/sources/codex.md
- references/sources/cursor-cli.md
- references/sources/cursor-ide.md
- references/sources/cursor.md
- references/sources/grok-build.md
- references/sources/opencode.md
Open the folder on GitHubat commit becee99
Compare with similar skills
Review AI Conversations next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Review AI Conversations this skillshareAI-lab/lab-skills | 315 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Modeling Conversion MetricsPostHog/posthog | 40k | — | ~1.4k | Automated safety check: Pass | Custom licence | |
| Cost Conversationruvnet/ruflo | 74k | — | ~407 | Automated safety check: Notes | MIT | |
| Conversation Memorydavila7/claude-code-templates | 33k | 4 repos | ~440 | Automated safety check: Pass | MIT | |
| Conversation Archivegarrytan/gbrain | 31k | — | ~5.6k | Automated safety check: Pass | MIT | |
| Landing Page Conversion Auditgithub/awesome-copilot | 40k | 1 repos | ~1.8k | Automated safety check: Pass | MIT |
Similar skills
- Official
Cost Conversation
ruvnet/ruflo
Per-conversation cost view — list every session in cost-tracking with started-at, message count, top model, and total cost
Conversation Memory
davila7/claude-code-templates
Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory Use when: conversation memory, remember, memory persistence, long-term memory, chat history.
Conversation Archive
garrytan/gbrain
Import AI-assistant chat exports (ChatGPT, Claude, Perplexity) and agent session transcripts into the brain as one dated page per conversation under conversations/, validate each page against the…
- Official
Landing Page Conversion Audit
github/awesome-copilot
Audit a landing page, sales page or checkout page for conversion leaks and return a fix list ordered by expected revenue impact.
Capture Conversation
outline/outline
Save the current conversation, a decision, or a set of notes as a document in an Outline collection; use when the user wants to keep what was discussed in their knowledge base.
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Questions about Review AI Conversations
What does Review AI Conversations do?
Recover and review local human-AI conversations from Claude Code, Codex, opencode, Grok Build, and Cursor. Review AI Conversations is an agent skill from shareAI-lab/lab-skills. Recover and review local human-AI conversations from Claude Code, Codex, opencode, Grok Build, and Cursor.
When should I use Review AI Conversations?
Review AI Conversations fits situations like: the user wants to revisit; compare work across Agent session stores; named conversations.
How do I install Review AI Conversations in Claude Code?
Run `npx skills add shareAI-lab/lab-skills --skill review-ai-conversations -a claude-code`. Or copy the skill folder (research-analysis/review-ai-conversations in shareAI-lab/lab-skills) into .claude/skills/review-ai-conversations in your project. Claude Code loads it when a task matches its description.
How do I install Review AI Conversations in Codex?
Run `npx skills add shareAI-lab/lab-skills --skill review-ai-conversations -a codex`. Or copy the skill folder (research-analysis/review-ai-conversations in shareAI-lab/lab-skills) into .agents/skills/review-ai-conversations in your project. Codex loads it when a task matches its description.
Can I use Review AI Conversations in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add shareAI-lab/lab-skills --skill review-ai-conversations -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/review-ai-conversations, .gemini/skills/review-ai-conversations, .github/skills/review-ai-conversations and .opencode/skills/review-ai-conversations in your project.
What does Review AI Conversations need to run?
SKILL.md names no scripts, command-line tools or credentials: Review AI Conversations is instructions for the agent only.
Does Review AI Conversations access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Review AI Conversations safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Review AI Conversations use?
Review AI Conversations is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Review AI Conversations use?
About 1.1k tokens (SKILL.md is roughly 4.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 9.9k tokens, read only when the agent opens those files.
What are the alternatives to Review AI Conversations?
Skills that share tags, products or a category with Review AI Conversations: Modeling Conversion Metrics (PostHog/posthog, 40k stars), Cost Conversation (ruvnet/ruflo, 74k stars), Conversation Memory (davila7/claude-code-templates, 33k stars) and Conversation Archive (garrytan/gbrain, 31k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Review AI Conversations?
shareAI-lab (a GitHub organization) maintains it in shareAI-lab/lab-skills, which has 315 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on September 16, 2026.
Source: shareAI-lab/lab-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.