Agent skill

Spark Prairie Fire

by HughYau in HughYau/qiushi-skill

星火燎原:从零起步、资源极少时,先评估客观条件,选定一个能站稳、能复用、能扩展的"根据地"(最小切入点),扎根后再逐步扩张,拒绝四处出击的流寇主义。当启动新项目、做 MVP / pilot、面对宏大目标不知从何下手、或做了很多零散事却没有积累时触发;项目已有稳固基础、只是修改现有系统时不触发。

MITAuto-check passed

Install Spark Prairie Fire

skills CLI
$ npx skills add HughYau/qiushi-skill --skill spark-prairie-fire -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install HughYau/qiushi-skill spark-prairie-fire --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/HughYau/qiushi-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/spark-prairie-fire .claude/skills/spark-prairie-fire && rm -rf skills-src

Use ~/.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/

Facts

Skill name
spark-prairie-fire
GitHub stars
3.8k
Token cost
~414 tokens
SKILL.md length
44 words
Files
2
Skills in repo
11
Repo updated
First seen
Licence
MIT

At a glance

星火燎原:从零起步、资源极少时,先评估客观条件,选定一个能站稳、能复用、能扩展的"根据地"(最小切入点),扎根后再逐步扩张,拒绝四处出击的流寇主义。当启动新项目、做 MVP / pilot、面对宏大目标不知从何下手、或做了很多零散事却没有积累时触发;项目已有稳固基础、只是修改现有系统时不触发。

  • Works in 5 steps: 评估客观条件:需求是否真实存在(有没有干柴)?环境是否允许发展?方向对不对?有没有… → 选根据地:一个具体切入点,满足四要素:核心功能可靠、可复用、有明确扩展路径、经验证… → 扎根:在这一点做深,产出可复用的基础设施与认识。 → …
  • Daunting goals with no obvious first step
  • SKILL.md covers 用 / 不用, 操作规程, 输出模板 and 纪律, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Spark Prairie Fire is an agent skill from HughYau/qiushi-skill. 星火燎原:从零起步、资源极少时,先评估客观条件,选定一个能站稳、能复用、能扩展的"根据地"(最小切入点),扎根后再逐步扩张,拒绝四处出击的流寇主义。当启动新项目、做 MVP / pilot、面对宏大目标不知从何下手、或做了很多零散事却没有积累时触发;项目已有稳固基础、只是修改现有系统时不触发。 English: Spark a prairie fire. When starting from almost nothing, assess the conditions, choose one base area (a minimal foothold that can hold, be reused, and expand), dig in, then grow step by step instead of scattering effort. Trigger for new projects, MVPs, pilots, daunting goals with no obvious first step, or busy work that accumulates nothing; skip when a solid…

Its SKILL.md is about 410 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `original-texts.md`).

The repository describes itself as: Qiushi-Skill: Build agents that investigate first, focus on the main contradiction, validate in practice, and keep pushing until the work is actually done… The licence is MIT.

When your agent uses it

  • Daunting goals with no obvious first step
  • Busy work that accumulates nothing
  • Skip when a solid base already exists
  • The task modifies an existing system

Example prompts

  • “/spark-prairie-fire”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. 评估客观条件:需求是否真实存在(有没有干柴)?环境是否允许发展?方向对不对?有没有哪怕很小的可依托基础?条件不足 → 先 investigation-first 或调整方向,不急于动手。
  2. 选根据地:一个具体切入点,满足四要素:核心功能可靠、可复用、有明确扩展路径、经验证稳固。选你最有优势、最能站稳的地方。
  3. 扎根:在这一点做深,产出可复用的基础设施与认识。
  4. 流寇主义检查(每次扩展前必须通过)
  5. 三步路线图:只规划三步,每步有成功标志,前一步稳固后才走下一步。

What it can do on your machine

Read from SKILL.md and the folder at commit 5ace717. 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

Spark Prairie Fire loads about 414 tokens when it runs. Until then it costs about 149 tokens; SKILL.md has 44 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~149
When it runs · the whole SKILL.md, loaded when a task matches
~414

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 HughYau/qiushi-skill at commit 5ace717, republished under its MIT licence (© HughYau). 44 words, ~414 tokens.

Download SKILL.mdSave it as .claude/skills/spark-prairie-fire/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
spark-prairie-fire
description
星火燎原:从零起步、资源极少时,先评估客观条件,选定一个能站稳、能复用、能扩展的"根据地"(最小切入点),扎根后再逐步扩张,拒绝四处出击的流寇主义。当启动新项目、做 MVP / pilot、面对宏大目标不知从何下手、或做了很多零散事却没有积累时触发;项目已有稳固基础、只是修改现有系统时不触发。 English: Spark a prairie fire. When starting from almost nothing, assess the conditions, choose one base area (a minimal foothold that can hold, be reused, and expand), dig in, then grow step by step instead of scattering effort. Trigger for new projects, MVPs, pilots, daunting goals with no obvious first step, or busy work that accumulates nothing; skip when a solid base already exists or the task modifies an existing system.

星火燎原

"现在虽只一点小小的力量,但是它的发展会是很快的。" —— 《星星之火,可以燎原》

小不等于没前途;关键是建根据地,不做流寇。

用 / 不用

用:

  • 从零开始一个新项目、新领域、新能力
  • 资源极度有限,大目标看起来不可能
  • 正在做很多零散的事但没有积累
  • 需要用最小投入验证一个想法

不用:

  • 已有稳固基础,处于扩展阶段
  • 用户已明确切入点,只需执行
  • 修改现有系统:现有代码就是根据地

操作规程

  1. 评估客观条件:需求是否真实存在(有没有干柴)?环境是否允许发展?方向对不对?有没有哪怕很小的可依托基础?条件不足 → 先 investigation-first 或调整方向,不急于动手。
  2. 选根据地:一个具体切入点,满足四要素:核心功能可靠、可复用、有明确扩展路径、经验证稳固。选你最有优势、最能站稳的地方。
  3. 扎根:在这一点做深,产出可复用的基础设施与认识。
  4. 流寇主义检查(每次扩展前必须通过):
    • 上一个切入点已验证稳固?
    • 这次扩展是从根据地自然延伸,不是跳跃?
    • 新增内容可复用,不是一次性的?
  5. 三步路线图:只规划三步,每步有成功标志,前一步稳固后才走下一步。

输出模板

条件评估:需求真实 [是 / 否 / 不确定],依据 ……;可依托基础 ……;主要障碍 ……
结论:具备发展条件 / 条件不足,需先 ……

根据地:……
- 我在这里的优势:……
- 能站稳的证据:……
- 向外扩展的路径:……

路线图:
第 1 步:…… → 成功标志:……
第 2 步:…… → 成功标志:……(第 1 步稳固后)
第 3 步:…… → 成功标志:……(第 2 步稳固后)

纪律

  • 禁止根据地未稳就扩张;禁止不断换方向浅尝辄止。
  • 既反悲观("这点资源做不了什么"),也反冒险("先干起来再说,到处出击")。

交接

  • 根据地上集中力量 → concentrate-forces
  • 每步扩展的验证 → practice-cognition
  • 纳入长期阶段框架 → protracted-strategy

原著依据:original-texts.md

© HughYau, MIT. 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 1 other file in skills/spark-prairie-fire of HughYau/qiushi-skill.

  • SKILL.md
  • original-texts.md

Open the folder on GitHubat commit 5ace717

Compare with similar skills

Spark Prairie Fire 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.

Spark Prairie Fire compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Spark Prairie Fire this skillHughYau/qiushi-skill3.8k—~414Automated safety check: PassMIT
Apache Spark Optimizationwshobson/agents40k9 repos~789Automated safety check: PassMIT
Apache Spark EngineerJeffallan/claude-skills12k1 repos~1.7kAutomated safety check: PassMIT
Spark Environment Setupwshobson/agents40k—~2kAutomated safety check: PassMIT
DGX Spark Training Gotchaswshobson/agents40k—~2kAutomated safety check: PassMIT
DGX Spark Memory and Thermal Opswshobson/agents40k—~2kAutomated safety check: PassMIT

Similar skills

  • Speed up slow Apache Spark jobs by tuning partitions, shuffles, data skew, caching and executor memory, with do and don't rules for PySpark code.

    40k GitHub starsUsed in 9 repos~789 tokens
    Data & AnalyticsAuto-check passed
  • Apache Spark Engineer

    Jeffallan/claude-skills

    Guides writing and tuning Apache Spark jobs: DataFrame and RDD code, Spark SQL, partitioning, caching, shuffle tuning and structured streaming.

    12k GitHub starsUsed in 1 repo~1.7k tokens
    Data & AnalyticsAuto-check passed
  • Set up a working ML training/inference environment on NVIDIA DGX Spark (GB10, aarch64, CUDA 13).

    40k GitHub stars~2k tokensUpdated 6 days ago
    AI & LLM EngineeringAuto-check passed
  • Preflight checks and diagnosis for ten known failure modes of ML training on NVIDIA DGX Spark's GB10, spanning launch errors, memory, thermals, bandwidth and precision.

    40k GitHub stars~2k tokensUpdated 6 days ago
    AI & LLM EngineeringAuto-check passed
  • Plans memory headroom, works through out-of-memory failures and watches temperature and power during long ML training jobs on NVIDIA DGX Spark.

    40k GitHub stars~2k tokensUpdated 6 days ago
    AI & LLM EngineeringAuto-check passed
  • Discovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine).

    21k GitHub stars~4.4k tokensUpdated yesterday
    Data & AnalyticsAuto-check passed

More from HughYau/qiushi-skill

All 11 skills in this repo
  • Concentrate Forces

    HughYau/qiushi-skill

    集中兵力:多件事同时争抢时间、注意力或预算时,列出全部待办,选定唯一主攻目标并公开锁定,彻底解决、验证后再转向下一个。当待办过多、推进分散、"每件都做了一点但都没做完"、需要决定先做什么时触发;只有一个任务、任务彼此独立可并行、用户明确要求同时推进时不触发。

    3.8k GitHub stars~379 tokensUpdated 10 days ago
    Auto-check passed
  • Contradiction Analysis

    HughYau/qiushi-skill

    矛盾分析法:把复杂问题拆成若干对立面,找出规定其他矛盾的主要矛盾及其主要方面,判定对抗性 / 非对抗性,并据此选择处理方式。当问题头绪多、多个因素互相牵制、优先级不清、根因不明、反复修不好、trade-off 说不清时触发;直接执行类任务或用户已定方案时不触发。

    3.8k GitHub stars~485 tokensUpdated 10 days ago
    Auto-check passed
  • Criticism Self Criticism

    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。

    3.8k GitHub stars~423 tokensUpdated 10 days ago
    Auto-check passed
  • Investigation First

    HughYau/qiushi-skill

    调查研究:在下判断、做决策、给建议之前,先用第一手材料弄清现状,产出「事实 / 推断 / 未知」三栏调查结论。当上下文不完整、证据薄弱、领域陌生、用户说"先别动手"、或你发现自己在凭印象作答时触发;已充分调查后的执行阶段不要重复触发。

    3.8k GitHub stars~425 tokensUpdated 10 days ago
    Auto-check passed
  • Mass Line

    HughYau/qiushi-skill

    群众路线:从持有真实情况的多方(用户、使用者、代码库、日志、运行结果)收集分散意见,系统化为方案,再带回去对齐与检验,循环改进。当多方意见分歧、需要汇总零散反馈、方案要拿回给真实使用者确认、或你发觉自己在闭门造车时触发;信息源单一且完整、处于执行阶段时不触发。

    3.8k GitHub stars~467 tokensUpdated 10 days ago
    Auto-check passed
  • Overall Planning

    HughYau/qiushi-skill

    统筹兼顾:当多个目标、指标或利益方相互制约、优化一项会伤害另一项时,识别全部辩证关系对,检查片面性,为每对关系定出当前阶段的侧重与底线,评估系统性影响,并设失衡预警。触发信号包括 trade-off、目标冲突、速度 vs 质量、短期 vs 长期、"顾此失彼";只有单一目标、用户已定取舍、或属硬性二选一时不触发。

    3.8k GitHub stars~416 tokensUpdated 10 days ago
    Auto-check passed

Questions about Spark Prairie Fire

What does Spark Prairie Fire do?

星火燎原:从零起步、资源极少时,先评估客观条件,选定一个能站稳、能复用、能扩展的"根据地"(最小切入点),扎根后再逐步扩张,拒绝四处出击的流寇主义。当启动新项目、做 MVP / pilot、面对宏大目标不知从何下手、或做了很多零散事却没有积累时触发;项目已有稳固基础、只是修改现有系统时不触发。. Spark Prairie Fire is an agent skill from HughYau/qiushi-skill. 星火燎原:从零起步、资源极少时,先评估客观条件,选定一个能站稳、能复用、能扩展的"根据地"(最小切入点),扎根后再逐步扩张,拒绝四处出击的流寇主义。当启动新项目、做 MVP / pilot、面对宏大目标不知从何下手、或做了很多零散事却没有积累时触发;项目已有稳固基础、只是修改现有系统时不触发。 English: Spark a prairie fire.

When should I use Spark Prairie Fire?

Spark Prairie Fire fits situations like: daunting goals with no obvious first step; busy work that accumulates nothing; skip when a solid base already exists; the task modifies an existing system.

How do I install Spark Prairie Fire in Claude Code?

Run `npx skills add HughYau/qiushi-skill --skill spark-prairie-fire -a claude-code`. Or copy the skill folder (skills/spark-prairie-fire in HughYau/qiushi-skill) into .claude/skills/spark-prairie-fire in your project. Claude Code loads it when a task matches its description.

How do I install Spark Prairie Fire in Codex?

Run `npx skills add HughYau/qiushi-skill --skill spark-prairie-fire -a codex`. Or copy the skill folder (skills/spark-prairie-fire in HughYau/qiushi-skill) into .agents/skills/spark-prairie-fire in your project. Codex loads it when a task matches its description.

Can I use Spark Prairie Fire 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 HughYau/qiushi-skill --skill spark-prairie-fire -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/spark-prairie-fire, .gemini/skills/spark-prairie-fire, .github/skills/spark-prairie-fire and .opencode/skills/spark-prairie-fire in your project.

What does Spark Prairie Fire need to run?

SKILL.md names no scripts, command-line tools or credentials: Spark Prairie Fire is instructions for the agent only.

Does Spark Prairie Fire 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 Spark Prairie Fire 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 Spark Prairie Fire use?

Spark Prairie Fire is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Spark Prairie Fire use?

About 414 tokens (SKILL.md is roughly 1.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Spark Prairie Fire?

Skills that share tags, products or a category with Spark Prairie Fire: Apache Spark Optimization (wshobson/agents, 40k stars), Apache Spark Engineer (Jeffallan/claude-skills, 12k stars), Spark Environment Setup (wshobson/agents, 40k stars) and DGX Spark Training Gotchas (wshobson/agents, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Spark Prairie Fire?

HughYau (a GitHub user) maintains it in HughYau/qiushi-skill, which has 3,812 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on October 1, 2026.

Source: HughYau/qiushi-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.