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(beta) Manage engineers with yeaboi: 1:1 prep from real delivery data, 1:1 completion summaries with tracked action items, periodic performance reviews, and quick notes. Use when the user wants to prepare for a 1:1, write up a held 1:1, draft a performance review, or record an observation about an engineer.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/yeaboi-ai/yeaboi.ai --skill performance命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
CI/CD workflow internals, version management and auto-bump mechanics, PyPI publish flow, and Dependabot auth quirks. Use when modifying .github/workflows, releasing, versioning, or debugging CI/publish/Dependabot behaviour.
Ask Niko, yeaboi's global assistant, a question that spans modes — what to look at next, what the AI coding agents cost, where a feature lives, is anything waiting for approval. Read-only: Niko looks things up across planning, standups, retros, poker, performance, reporting, ship, the agentwatch family, ceremonies, provenance and LLM usage, and names the screen that does a thing. Use when the question spans several modes or you don't know which one holds the answer; use the specific tool when you already do.
Full annotated module map of src/yeaboi/ (incl. the MCP server, roadmap, analysis, and agent/headless.py), app flow, the complete CLI flags + subcommands, all environment variables, and the MCP server internals + Claude Code plugin. Use when navigating unfamiliar modules, adding CLI flags/subcommands, changing env/config, or working on the MCP server or plugin.
正在显示 SKILL.md
| name | performance |
| description | (beta) Manage engineers with yeaboi: 1:1 prep from real delivery data, 1:1 completion summaries with tracked action items, periodic performance reviews, and quick notes. Use when the user wants to prepare for a 1:1, write up a held 1:1, draft a performance review, or record an observation about an engineer. |
Beta. Performance mode is in beta — its output is not yet verified against real delivery data. Treat every 1:1 prep, summary and review as a draft to edit, not a verdict, and say so when you present it to the user.
Know the roster. Call perf_roster to list the engineers derived from
recent Jira/Azure DevOps assignees — these are the names every other tool
accepts. If it's empty, no tracker is configured (point at yeaboi --setup).
Pick the workflow from what the user asked:
perf_one_on_one_prep with the engineer's name. Present
the talking points, feedback, goals and growth areas conversationally —
it already folds in the open action items from their previous 1:1.perf_one_on_one_complete. Leave deliver false — you present the
summary; only set deliver: true (emails it via the configured SMTP) if
the user explicitly asks. The action items are tracked and carried into
the next prep automatically.perf_six_month_review (set period_months if they
name a different window). It synthesises past 1:1s, delivery history and
the competency framework. Frame the output as a draft for the lead to
edit, never a verdict.perf_note_add with the engineer and the
note. Notes feed future preps and reviews.Surface warnings (the beta caveat, tracker 401s, missing SMTP, LLM
fallback) so the user knows what informed — or didn't inform — the output.
Every perf tool now returns the beta caveat as its first warning.
Sensitive data. This is personnel material: keep it in the conversation,
don't post it anywhere external unless explicitly asked. Exports auto-save
under ~/.yeaboi/exports/performance/<engineer>/.
Every tool returns {ok, llm_mode, warnings, data}. If ok is false, relay
error.message and its hint (usually credentials — yeaboi --setup); don't
retry blindly. llm_mode: "fallback" means no LLM was reachable and the artifact
is a deterministic skeleton — suggest yeaboi --setup.