siisee11/understanding-everything

understanding-everything

Research, scope, build, and verify a self-contained interactive learning page from an open-ended question, unfamiliar topic, URL, article, paper, document, GitHub repository, or local codebase.

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仓库原始内容

按源仓库内容呈现,保留标题、案例、代码、表格、链接以及原文引用的演示图片。

Understanding Everything

Turn curiosity into a small learning environment. Treat research, editorial selection, interaction design, implementation, and verification as one workflow. Do not merely decorate a prose article or summarize a repository.

Route the request

  1. Read scope-and-routing.md.
  2. Classify the evidence input:
  • Topic or question only: read topic-research.md.
  • Supplied URL, article, paper, transcript, or document: read

source-intake.md.

  • GitHub URL, repository, or source files: read

codebase-investigation.md.

  • Mixed input: read every applicable intake reference and name the evidence

hierarchy before drafting.

  1. Ask a scope question only when the request fails the scope test. Ask one

concise question at a time and offer a recommended option. Do not ask about visual taste, framework choice, filenames, or safe implementation defaults.

  1. Read production-profiles.md and choose

one dominant profile. Honor a profile explicitly requested by the user.

Establish the learning contract

Before building, write a private working brief containing:

  • Audience and assumed prerequisite knowledge.
  • One-sentence learning objective.
  • The spine: the single causal path, mechanism, decision, or mental model.
  • In-scope concepts and explicit out-of-scope branches.
  • A concrete opening situation that matters before terminology appears.
  • One prediction, trace, comparison, or playable goal.
  • Vocabulary budget and optional depth.
  • Evidence sources and freshness requirements.
  • Chosen production profile and why it fits.
  • Planned learner actions, visible responses, and intended discoveries.
  • For a model-driven profile: state variables, invariants, assumptions, and

deterministic reference cases.

For every interaction answer:

  1. What does the learner change or do?
  2. What visibly changes in response?
  3. What relationship or insight becomes observable?
  4. What equivalent text or control supports a learner who cannot use the visual?

Remove any interaction that cannot answer all four. Read learning-and-interaction-design.md and discovery-first-explanation.md before storyboarding.

Apply the selected profile

  • For editorial-v1, read

declaude-editorial-style.md and start from explainer-template.html.

  • For simulation-essay-v1, read

simulation-essay-profile.md and model-and-scene-engineering.md, then start from simulation-essay-template.html.

  • For playable-post-v1, read

playable-post-profile.md and model-and-scene-engineering.md, then start from playable-post-template.html.

Treat benchmark pages as evidence of general techniques, not assets or layouts to copy. Keep prose, visuals, code, characters, and interaction choreography original to the topic.

Investigate before explaining

  • Read supplied material or the real implementation instead of relying on names.
  • Use current web research for time-sensitive, high-stakes, or unfamiliar

claims. Prefer primary sources and official documentation.

  • Treat supplied articles as narrative leads, not automatic ground truth.
  • For code, resolve branch and commit, trace actual entry points and call paths,

and anchor claims to file and line evidence.

  • Keep research read-only unless the user separately requests repository changes.

Build the page

  1. Follow the chosen profile's narrative unit: editorial steps, connected

simulation scenes, or playable stages. Do not target a scene count for its own sake.

  1. Prefer semantic HTML for text and discrete state; SVG for inspectable

relationships; Canvas or WebGL only for dense, spatial, or continuous models.

  1. Keep calculations and state transitions separate from rendering. A complex

page may be developed as modules, but bundle the delivered artifact into a self-contained HTML file unless the user requests another packaging format.

  1. Write original prose in the user's language. Use concrete actors, actions,

states, and consequences before abstractions. Introduce a term only after its meaning is visible, cite important claims near their use, and end with sources.

  1. Keep inferred audience, reading time, and generic labels such as beginner,

advanced, or educational simplification out of the visible masthead unless requested. Put specific assumptions beside the model they qualify.

  1. Make the first render useful before interaction and preserve a readable

explanation when JavaScript is unavailable.

  1. Use a user-specified output location. Otherwise use a durable task-owned

artifact directory outside product source when available. Never overwrite an existing explainer without approval.

Verify and deliver

  1. Read fact-checking.md and resolve every

unsupported or contradicted claim.

  1. Run scripts/validate-explainer.mjs against the final HTML. It detects the

explainer-profile marker and applies common plus profile-specific checks.

  1. Read browser-and-accessibility-qa.md.

Exercise every interaction at desktop and narrow mobile widths with pointer and keyboard input. Fix console errors, overflow, stale states, inaccessible controls, and broken representative or extreme states.

  1. For simulations and playable models, independently verify formulas,

invariants, seeded scenarios, and displayed reference values outside the rendering path.

  1. Do not claim verification that was not performed. State exact limitations.
  2. Deliver the absolute page path, selected profile, learning objective,

principal sources or code revision, verification performed, and material limitations. Do not publish or deploy unless the user requests it.