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lavine888lavine888/career-alpha/skills/build/SKILL.md

build

Skill0 starsChanged 3 months agoMITView on GitHub

Career Alpha Proof-of-Work 项目构建器。用于把趋势或职业楔子变成 2–7 天可以真正完成、展示和验证的小型项目;当用户问应该做什么项目、如何快速补齐某能力证据、如何把新趋势变成作品集,或需要一个可交给 Codex / Claude Code 执行的项目任务书时使用。

156 other projects use a version of this.

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Projects with it also use backprop, finances and 10 more.

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  • JuliusBrusseeSkill

    backprop

    Bug → spec protocol. When a bug is found or a test fails, trace the cause, decide whether a new §V invariant would catch recurrence, append to §B. This is the one non-obvious thing SDD does that plan-then-execute doesn't. Triggers on test failure, bug report, post-mortem, or explicit user ask.

    Also in 4 projects that use this

  • GerardoRdz96Skill

    finances

    Use when Gera talks about his money — logging an expense ("I spent X on Y"), checking where he stands this pay-period, closing a period, planning debt payoff, onboarding his financial picture, or asking for budgeting/finance opinions. Servy's financial brain. Triggers — "I spent", "log this expense", "where am I this period", "close the period", "how's my budget", "debt plan", "should I pay off", "finances onboard", "/finances".

    Also in 3 projects that use this

  • cpiprintSkill

    favicon

    Generate favicons from a source image

    Also in 3 projects that use this

  • madeehahassanSkill

    Go-Live

    Pre-launch checklist. Use before making any app public, sharing a link externally, or announcing a product launch. Adapts to Claude Code, claude.ai, and Cowork.

    Also in 3 projects that use this

  • JuliusBrusseeSkill

    deepen

    Optional design-improvement pass for when you have spare usage to drain. Finds the shallowest modules in the code the spec touches, researches a deeper design, and proposes refactors that shrink interfaces and hide decisions — behavior held constant, tests green before and after. Proposes §I/§V/§T edits, never silent rewrites. Triggers when the user says "deepen this", "improve the design", "this module feels shallow", "pull complexity down", "use spare budget on the codebase", or invokes /ck:deepen. Leans on the codebase-design skill's deep-module vocabulary when present.

    Also in 3 projects that use this

  • synaptiaiSkill

    gate

    Create a BDSK review_gate artifact. Defines a checkpoint that controls whether generated output may proceed toward acceptance. Use when defining quality, security, or scope gates for execution plans.

    Also in 5 projects that use this

The file

Files
SKILL.md

/build — Build the Evidence

/build 的目标不是“再做一个项目”,而是把 /wedge 的职业假设转成 一段新的、可验证的事实。

核心原则:

Project exists to prove a claim. The claim does not exist to decorate the project.


1. Read the upstream hypothesis

优先读取:

  • /wedge 选出的方向;
  • 用户当前证据缺口;
  • cheapest test;
  • kill criteria;
  • 目标岗位 / 公司类型;
  • 用户可用时间与工具。

如果用户没有经过 /wedge,也可以直接从目标岗位出发,但必须先问自己:

这个项目完成后,简历里会多出哪一条以前不能诚实说的话?

如果答案只是“我也做过一个 X”,项目价值通常偏低。


2. Define ONE primary career claim

项目必须有一个主要主张,例如:

  • 能设计 Agent Eval;
  • 能系统分析 tool-use failure;
  • 能做真实数据 pipeline;
  • 能优化 latency / cost 并说明 tradeoff;
  • 能把模型能力变成完整 workflow;
  • 能读懂并扩展真实开源代码库。

可以产生多个 secondary claims,但 scope 由 primary claim 决定。

Bad

做一个完整 AI SaaS,展示产品、前端、后端、算法、增长、商业化能力。

Better

用一个可复现 benchmark 证明我能设计 Agent Reliability Eval。


3. Choose the right project archetype

读取 Project Archetypes。优先从以下类型选择:

  • Benchmark;
  • Reliability / failure analysis;
  • Vertical workflow;
  • Integration;
  • Cost / latency optimization;
  • Open-source extension;
  • Reproduction / replication。

不要默认做“全栈网站”。

如果最有价值的证据来自现有开源生态,应考虑把任务转给 /contributor,而不是重新造一个平行项目。


4. Baseline before intervention

除非项目本质无法比较,否则先定义 baseline。

Baseline 至少说明:

  • 当前实现 / naïve approach;
  • 任务集 / 数据;
  • primary metric;
  • dependency / model version;
  • 已知限制。

没有 baseline 的“优化”“提升”“更可靠”通常无法安全写进简历。


5. Evaluation before polishing

项目早期就定义:

  • success metric;
  • secondary metrics;
  • sample / task set;
  • failure taxonomy;
  • 是否需要 repeated trials;
  • 哪些变量需要固定;
  • 哪些结果会被视为 failure。

先测对,再做漂亮。

如果结果不可量化,也至少要有可验证 outcome,例如:

  • merged PR;
  • deployed workflow;
  • external review;
  • user feedback;
  • reproduced bug;
  • working integration with tests。

6. Scope control

使用 Mission Brief Template。

每个 2–7 天任务必须写:

In scope

只保留直接服务 primary career claim 的内容。

Non-goals

强制列出不会做的东西,例如:

  • 不做完整登录系统;
  • 不做漂亮 dashboard;
  • 不支持所有模型;
  • 不做 production-scale infra;
  • 不做商业化。

Non-goals 是 Career Alpha 的重要部分,因为时间应该花在证据密度最高的地方。


7. 72h-first execution

默认先给 72h 版本,除非任务天然需要外部等待。

Day 1 — Honest baseline

目标:先产生第一份 raw evidence。

常见动作:

  • 建 repo;
  • 固定数据 / tasks;
  • 跑 baseline;
  • 保存原始结果;
  • 建 failure taxonomy;
  • 写第一版 README。

Exit criterion: baseline 可重复,不靠口头解释。

Day 2 — Intervention

  • 实现最小核心改动;
  • 跑相同 evaluation;
  • 保存 raw outputs;
  • 记录 regression;
  • 不提前筛掉难看的结果。

Exit criterion: 能比较 before / after,哪怕结果没有提升。

Day 3 — Interviewability

  • ablation / failure analysis;
  • architecture / decision log;
  • README reproduction;
  • cleanup;
  • demo / screenshots;
  • 明确 limitations。

Exit criterion: 另一个工程师能理解“问题—选择—证据—限制”。


8. Definition of Done

Definition of Done 必须可观察。

Bad

  • 项目基本完成;
  • UI 比较完整;
  • 效果不错。

Good

  • 50-task eval 从一条命令跑完;
  • raw output 保存在 results/;
  • README 写清 baseline 与 intervention;
  • 至少 5 个 failure cases 分类;
  • architecture diagram 存在;
  • 所有结果能对应到 commit / version;
  • 用户反馈有原始记录。

9. Evidence capture plan

在开始前规定需要保存:

  • repo URL;
  • commit hashes;
  • changed files;
  • benchmark / CSV;
  • logs;
  • model / dependency versions;
  • screenshots / demo;
  • test commands;
  • user feedback;
  • failed attempts;
  • scope / ownership notes。

不要项目做完后再凭记忆补证据。


10. Failure is still evidence

Career Alpha 项目不是比赛作品,结果没有提升也可能有价值。

例如:

Context compression reduced cost 22% but caused a measurable regression on long-horizon tasks.

这比无证据地写“optimized context efficiency”更能展示工程判断。

所以默认记录:

  • what worked;
  • what failed;
  • regressions;
  • unexpected behavior;
  • next experiment。

11. Anti-demo rules

以下默认降级:

  • 只换 prompt 的 ChatGPT clone;
  • 无数据、无 evaluation 的普通 RAG;
  • 照教程逐行复刻;
  • 只有漂亮 landing page;
  • “多 Agent 系统”但没有任务、metric 或 failure analysis;
  • 一个大型平台,却没有任何用户或可复现结果;
  • 自动生成大量代码,但用户无法解释关键 decision。

Rescue path

如果用户已经有这种项目,不一定丢掉。尝试增加:

  • benchmark;
  • real user workflow;
  • failure taxonomy;
  • deployment;
  • external contribution;
  • cost / latency / quality tradeoff;
  • architecture rationale。

12. Execution prompt for coding agents

当用户要交给 Codex / Claude Code 执行时,输出一个独立执行块,至少包含:

Goal
Career claim to prove
Repository structure
Baseline
Implementation tasks
Evaluation
Definition of Done
Non-goals
Evidence to capture
Validation commands
Do not fabricate results

Coding agent 可以实现和测试,但不能预先写“提升 30%”之类尚未发生的结果。


13. Default output

Mission Brief

  • Career claim to prove
  • User / problem
  • Why now
  • Project archetype
  • Baseline
  • Intervention
  • Evaluation
  • Scope
  • Non-goals

72h / 7-day Plan

按 milestone + exit criterion 写,不只是 todo list。

Repo / artifact plan

说明哪些文件最终构成证据。

Definition of Done

必须全部可验证。

Evidence Capture

提前列出要保存什么。

Failure modes

预判 3–5 个可能让项目证据价值下降的风险。

Coding-agent prompt

用户需要时输出。


14. Handoff to /proof

按 Cross-skill Handoff Contract 传递:

career_claim:
verified_artifacts:
baseline:
results:
ownership:
failures:
limitations:
planned_but_not_completed:
recommended_next_skill: /proof

未完成内容必须保留 PLANNED / IN PROGRESS,不能因为 Mission Brief 写得完整就当作已经做完。

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