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hamburger-oshamburger-os/PraxFlow/skills/survey/SKILL.md

survey

Skill1 starsChanged 2 months agoMITView on GitHub

Rapidly map the parts of an unfamiliar codebase or technical project that matter to the current goal. Use before deeper investigation when you need entry points, boundaries, relevant components, likely dependencies, existing docs/tests, and high-value unknowns without reading the whole repository.

21 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use daily-arxiv, exp-eval and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • LambenthanSkill

    daily-arxiv

    每日从 arXiv 拉取新论文,过滤相关性,auto-ingest 高优先级论文,检测 SOTA 更新

    Also in 5 projects that use this

  • LambenthanSkill

    exp-eval

    实验判决门:Review LLM 独立评判实验结果 → 4 种判决路径 → 自动更新 claims confidence、ideas status、graph edges

    Also in 5 projects that use this

  • skyllwtSkill

    exp-pilot-eval

    Pilot result evaluation — read pilot results, apply success criteria, update idea page (pilot_result, failure_reason if failed), generate PILOT_VERDICT_REPORT. Called by /ideate Phase 5 after /exp-pilot-run.

    Also in 4 projects that use this

  • skyllwtSkill

    exp-pilot-run

    Pilot experiment execution — read Pilot Spec YAML, write pilot code, run experiment(Confirm with the user before operation and require the applicant to conduct manual inspection), return results. Called by /ideate Phase 5. Does NOT modify wiki pages or judge pass/fail.

    Also in 4 projects that use this

  • phanghonghaoSkill

    poster

    HTML/CSS A4 海报生成。从沙龙/活动 Markdown 文件生成科技风 A4 海报 PDF/PNG。Use when user mentions: poster, 海报, 海报生成, make poster, generate poster, 活动海报, 沙龙海报.

    Also in 4 projects that use this

  • +6 more from Lambenthan
  • +1 more from skyllwt

The file

We split this skill into the rules it gives an agent

11 rules. 0 are common, 10 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 16 edited versions we read keep these.

  • 10

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Do not widen the scope merely because more files are available.

    line 26
  2. Distinctive:

    Prefer low-cost structural evidence first:

    line 30
  3. Distinctive:

    Use search rather than sequentially reading directories.

    line 39
  4. Distinctive:

    Do not present a provisional inference as established architecture.

    line 70
  5. Distinctive:

    Ask: which unknown, if resolved, would most change the next engineering decision?

    line 74
  6. Distinctive:

    Stop when the map is sufficient for the current task.

    line 88
  7. Very specific:

    If one behavior needs deeper reconstruction, use trace when available instead of widening the whole survey.

    line 90
  8. Distinctive:

    read the entire repository by default.

    line 95
  9. Distinctive:

    ask the user where code lives when you can search for it.

    line 97
  10. Distinctive:

    treat directory names or README claims as authoritative when code evidence contradicts them.

    line 98
  11. Distinctive:

    Keep the result compact unless the user explicitly asks for a full architecture assessment.

    line 102

“Common” is measured: kept by at least 6 in 10 of the 16 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Survey

Build a goal-directed provisional map of the project. Do not attempt to understand the whole repository unless the user's goal genuinely requires it.

Method

1. State the investigation goal

Translate the user's task into what you need to understand.

Examples:

  • “fix first-request 401” → auth/session initialization and first authenticated request path;
  • “add reconnect” → connection lifecycle, state machine, retry behavior, ownership;
  • “review this migration” → changed schema, readers/writers, compatibility, rollback.

Do not widen the scope merely because more files are available.

2. Orient cheaply

Prefer low-cost structural evidence first:

  • README and project docs relevant to the goal;
  • top-level directories;
  • build/package manifests;
  • obvious entry points;
  • tests near the target behavior;
  • configuration and interfaces connected to the goal.

Use search rather than sequentially reading directories.

3. Locate likely boundaries

Identify the smallest set of components that plausibly participate in the target behavior.

Look for:

  • entry points;
  • ownership boundaries;
  • module/service/process/thread boundaries;
  • external dependencies;
  • persistent state;
  • public contracts;
  • test seams;
  • relevant project capabilities.

4. Build a provisional map

Separate what is observed from what is inferred.

A useful lightweight map may include:

Relevant areas
Current behavior model
Known constraints
Important unknowns
Recommended next investigation

Do not present a provisional inference as established architecture.

5. Identify high-value unknowns

Ask: which unknown, if resolved, would most change the next engineering decision?

Prefer unknowns about:

  • lifecycle or ownership;
  • state transitions;
  • data/control flow;
  • interfaces and compatibility;
  • concurrency/async boundaries;
  • error paths;
  • verification path.

6. Stop or deepen selectively

Stop when the map is sufficient for the current task.

If one behavior needs deeper reconstruction, use trace when available instead of widening the whole survey.

Do not

  • summarize every directory;
  • read the entire repository by default;
  • generate an architecture document just because you inspected the project;
  • ask the user where code lives when you can search for it;
  • treat directory names or README claims as authoritative when code evidence contradicts them.

Output

Keep the result compact unless the user explicitly asks for a full architecture assessment.

Prefer:

## Relevant areas
...

## Working model
...

## Constraints / evidence
...

## Unknowns
...

## Next investigation
...

The working model is allowed to be incomplete. Make important uncertainty visible rather than filling gaps with guesses.

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