Weekly Engineering Retro
garrytan/gstack
Builds a weekly engineering retrospective from git history: commit counts, per-person contributions, work patterns and code quality numbers over a chosen window.
Coach leaders and managers to prepare, run, and review high-bandwidth meetings that advance real work and decisions.
$ npx skills add shareAI-lab/lab-skills --skill meeting-coach-leader -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install shareAI-lab/lab-skills meeting-coach-leader --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/team-collaboration/meeting-coach-leader .claude/skills/meeting-coach-leader && 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 "meeting-coach-leader" agent skill from https://github.com/shareAI-lab/lab-skills/tree/main/team-collaboration/meeting-coach-leader into .claude/skills/meeting-coach-leader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meeting-coach-leader", 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/team-collaboration/meeting-coach-leaderType 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 meeting-coach-leader -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install shareAI-lab/lab-skills meeting-coach-leader --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/team-collaboration/meeting-coach-leader .agents/skills/meeting-coach-leader && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "meeting-coach-leader" agent skill from https://github.com/shareAI-lab/lab-skills/tree/main/team-collaboration/meeting-coach-leader into .agents/skills/meeting-coach-leader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meeting-coach-leader", 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 meeting-coach-leader -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install shareAI-lab/lab-skills meeting-coach-leader --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/team-collaboration/meeting-coach-leader .cursor/skills/meeting-coach-leader && 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 "meeting-coach-leader" agent skill from https://github.com/shareAI-lab/lab-skills/tree/main/team-collaboration/meeting-coach-leader into .cursor/skills/meeting-coach-leader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meeting-coach-leader", 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 team-collaboration/meeting-coach-leader--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 meeting-coach-leader -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install shareAI-lab/lab-skills meeting-coach-leader --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/team-collaboration/meeting-coach-leader .gemini/skills/meeting-coach-leader && 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 "meeting-coach-leader" agent skill from https://github.com/shareAI-lab/lab-skills/tree/main/team-collaboration/meeting-coach-leader into .gemini/skills/meeting-coach-leader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meeting-coach-leader", 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 meeting-coach-leaderInstalls 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 meeting-coach-leader -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/team-collaboration/meeting-coach-leader .github/skills/meeting-coach-leader && 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 "meeting-coach-leader" agent skill from https://github.com/shareAI-lab/lab-skills/tree/main/team-collaboration/meeting-coach-leader into .github/skills/meeting-coach-leader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meeting-coach-leader", 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 meeting-coach-leader -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 meeting-coach-leader --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/team-collaboration/meeting-coach-leader .opencode/skills/meeting-coach-leader && 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 "meeting-coach-leader" agent skill from https://github.com/shareAI-lab/lab-skills/tree/main/team-collaboration/meeting-coach-leader into .opencode/skills/meeting-coach-leader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "meeting-coach-leader", 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.
meeting-coach-leaderCoach leaders and managers to prepare, run, and review high-bandwidth meetings that advance real work and decisions.
Meeting Coach Leader is an agent skill from shareAI-lab/lab-skills. Coach leaders and managers to prepare, run, and review high-bandwidth meetings that advance real work and decisions. Use for meeting retrospectives, employee work reviews, decision meetings, agenda and question design, direct feedback, meeting-quality diagnosis, or repeated low-value discussions. Preserve direct standards without taking over the worker's work or degrading the truth signal.
Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `agents/openai.yaml`, `references/manager-playbook.md` and `references/templates.md`).
It sits in Product & Project Management, covering Retrospectives. The repository describes itself as: Skills distilled from the Lab's real work and collaboration practices. The licence is Apache-2.0.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit becee99. It shows what the files ask for, not the result of running them.
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.
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.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Meeting Coach Leader loads about 2.2k tokens when it runs, and up to ~3.6k if it reads all its reference files. Until then it costs about 103 tokens; SKILL.md has 1,207 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.
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.
The full file from shareAI-lab/lab-skills at commit becee99, republished under its Apache-2.0 licence (© shareAI-lab). 1,207 words, ~2,236 tokens.
.claude/skills/meeting-coach-leader/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.Optimize meetings for truth, decisions, learning, and executable work. Do not confuse intensity, duration, or manager airtime with progress.
Keep the default answer practical. Read manager-playbook.md for deeper feedback language and anti-patterns. Read templates.md only when a reusable agenda, review, or follow-up note would help.
When recent meetings or transcripts are supplied, read the complete relevant corpus and trace:
Prefer raw transcripts over AI-generated minutes when they conflict. Separate meeting claims, verified facts, inferences, and proposals. Do not diagnose personality or intent from one artifact.
Before planning an agenda, state one primary outcome:
Avoid silently mixing all of them. If several are necessary, name the transition and allocate time deliberately.
Ask whether a meeting is needed at all. Prefer an async document when the work is mainly background reading, fact collection, or straightforward status. Use synchronous time for ambiguity, disagreement, trade-offs, feedback, and decisions.
Prepare:
Do not hide acceptance criteria in the manager's head. For complex work, tell the employee beforehand what question the work must answer and what evidence matters. Ask the employee to restate the assignment when misunderstanding would be costly.
Use a simple flow:
If the work is not ready, say so early. Use the remaining time to identify the smallest correction that makes the next review worthwhile.
Prefer questions such as:
Avoid repeating rhetorical questions after the gap is already clear. Repetition increases pressure but often produces no new information.
Do not lower the standard, hide an invalid result, or pretend work is ready. Also do not use sarcasm, global ability labels, public humiliation, or prolonged interrogation as substitutes for precise feedback.
Use this pattern:
Example:
This cost conclusion is not reviewable because the unit conversion and workload assumption cannot be reproduced. Rebuild it from the official price, show one formula and three workload scenarios, compare it with a dedicated-server baseline, and send the calculation before writing the recommendation.
Employee experience matters because fear, confusion, and unpredictability reduce the accuracy of the information reaching the manager. Respect does not mean comfort at all times. It means clear standards, a real chance to explain, specific correction, and no avoidable degradation.
The manager does not need to suppress legitimate frustration or absorb failed work. State the consequence plainly, pause a meeting that no longer creates value, and return responsibility to the employee with a clear correction.
When the manager discovers a missing analysis:
If the same failure repeats after expectations and support are clear, treat it as a performance or role-fit signal rather than adding more meeting explanation.
Judge whether the meeting created:
Look for low-bandwidth patterns:
Recommend the smallest change that improves the next meeting. Do not respond to process problems by creating excessive ceremony.
The current agent must inspect the actual meeting and work evidence. Never score meeting or employee quality from keywords, speaking time alone, tone alone, required headings, or a fixed template.
For large or disputed cases, use independent subagents when available to examine manager expectations, employee evidence, and meeting dynamics separately. Give them raw artifacts. The primary agent must reconcile their findings and own the final recommendation.
Keep the answer compact unless the user asks for a full analysis:
© 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
SKILL.md and 3 other files (references) in team-collaboration/meeting-coach-leader of shareAI-lab/lab-skills.
Open the folder on GitHubat commit becee99
Meeting Coach Leader 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 |
|---|---|---|---|---|---|---|
| Meeting Coach Leader this skillshareAI-lab/lab-skills | 315 | — | ~2.2k | Automated safety check: Pass | Apache-2.0 | |
| Weekly Engineering Retrogarrytan/gstack | 136k | — | ~2.4k | Automated safety check: Pass | MIT | |
| Dough Execute Planterryyin/lizard | 2.5k | — | ~4.3k | Automated safety check: Pass | Custom licence | |
| Oral Paper SkillAdkid-Zephyr/oral-paper-skill | 357 | — | ~1.9k | Automated safety check: Pass | None | |
| Deck Retroasheshgoplani/agent-deck | 1.1k | — | ~1.8k | Automated safety check: Pass | MIT | |
| Dough Execution Retrospectiveterryyin/lizard | 2.5k | — | ~4k | Automated safety check: Pass | Custom licence |
garrytan/gstack
Builds a weekly engineering retrospective from git history: commit counts, per-person contributions, work patterns and code quality numbers over a chosen window.
terryyin/lizard
Executes one selected story or bounded retrospective correction through an executable plan, or one authorized planless slice from a selected simple story or a contextual instruction, with…
Adkid-Zephyr/oral-paper-skill
Help authors learn from exemplary ICLR, ICML, and NeurIPS papers through source-linked manuscript comparisons, concrete writing and experiment suggestions, and guided reflection.
asheshgoplani/agent-deck
Run a fully local agent-deck retrospective over the user's own transcripts, Recall index and logs.
terryyin/lizard
Reviews planned, completed planless quick, or quick-to-planned execution against original intent, aggregate commits, current whole-product architecture, and tests, including after cleanup.
HughYau/qiushi-skill
批评与自我批评:在工作完成、阶段验收、收到批评或同类错误反复出现时,对成果和过程做诚实、具体、基于事实的审视,输出可执行的改进项,并处理外来批评而不辩解。触发信号包括 review、复盘、审查、"帮我看看有没有问题"、"你确定吗";任务刚开始或只是单步查询时不触发。
shareAI-lab/lab-skills
Helps design and build AI agents for any domain around a minimal loop of capabilities, knowledge and context, adding planning or subagents only when needed.
shareAI-lab/lab-skills
Deeply research technical architecture, source code, mechanisms, SDKs, frameworks, project comparisons, and system-design options across repositories, history, official docs, issues, discussions…
shareAI-lab/lab-skills
Research why neural architectures and training methods work through forward computation, geometry, gradients, optimization dynamics, historical experiments, and competing explanations.
shareAI-lab/lab-skills
Recover and review local human-AI conversations from Claude Code, Codex, opencode, Grok Build, and Cursor.
shareAI-lab/lab-skills
Evaluate Agent Skill design quality with an opinionated, practice-derived rubric informed by public specifications and examples.
shareAI-lab/lab-skills
Reconstruct and report long-running or multi-turn research, architecture questions, reviews, decisions, completion results, and status as a clear, self-contained brief.
Categories
Coach leaders and managers to prepare, run, and review high-bandwidth meetings that advance real work and decisions. Meeting Coach Leader is an agent skill from shareAI-lab/lab-skills. Coach leaders and managers to prepare, run, and review high-bandwidth meetings that advance real work and decisions.
Meeting Coach Leader fits situations like: meeting retrospectives; employee work reviews; decision meetings; agenda and question design.
Run `npx skills add shareAI-lab/lab-skills --skill meeting-coach-leader -a claude-code`. Or copy the skill folder (team-collaboration/meeting-coach-leader in shareAI-lab/lab-skills) into .claude/skills/meeting-coach-leader in your project. Claude Code loads it when a task matches its description.
Run `npx skills add shareAI-lab/lab-skills --skill meeting-coach-leader -a codex`. Or copy the skill folder (team-collaboration/meeting-coach-leader in shareAI-lab/lab-skills) into .agents/skills/meeting-coach-leader in your project. Codex loads it when a task matches its description.
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 meeting-coach-leader -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/meeting-coach-leader, .gemini/skills/meeting-coach-leader, .github/skills/meeting-coach-leader and .opencode/skills/meeting-coach-leader in your project.
SKILL.md names no scripts, command-line tools or credentials: Meeting Coach Leader is instructions for the agent only.
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.
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.
Meeting Coach Leader 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.
About 2.2k tokens (SKILL.md is roughly 8.9k 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 1.3k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Meeting Coach Leader: Weekly Engineering Retro (garrytan/gstack, 136k stars), Dough Execute Plan (terryyin/lizard, 2.5k stars), Oral Paper Skill (Adkid-Zephyr/oral-paper-skill, 357 stars) and Deck Retro (asheshgoplani/agent-deck, 1.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
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.