agentleFS
VoTruongDanhVoTruongDanh/Skills-Agent/.claude/skills/preview/SKILL.md

preview

Skill4 starsChanged 33 days agoMITView on GitHub

Preview expected output, UX flows, copy, interaction design, or generated content before implementing. Use when the user wants to see what something will look like. Triggers: preview, mockup, show me, xem trước, thử xem, mô phỏng.

We split this skill into the rules it gives an agent

11 rules. 0 are common, 4 are distinctive, and 7 are very specific to this project.

  • 0

    Common

    Most of the 7 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 7

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    START: Read .ai-memory.md from project root.

    line 10
  2. Very specific:

    END: Update .ai-memory.md using Memory Compaction Rules with: what was previewed, assumptions, feedback, and confirmed decisions.

    line 11
  3. Very specific:

    If previewing UI/UX → read .kiro/skills/agents/agents/frontend-specialist.md and apply its knowledge

    line 17
  4. Very specific:

    If previewing documentation → read .kiro/skills/agents/agents/documentation-writer.md and apply its knowledge

    line 18
  5. Very specific:

    If previewing API response → read .kiro/skills/agents/agents/backend-specialist.md and apply its knowledge

    line 19
  6. Distinctive:

    If any answer is unclear, ASK before proceeding.

    line 26
  7. Distinctive:

    Keep previews realistic and consistent with the current project.

    line 48
  8. Distinctive:

    Avoid implying broad code changes.

    line 50
  9. Distinctive:

    Always read and update the memory file.

    line 51
  10. Very specific:

    After completing, read .kiro/skills/_scripts/checklist.md for cross-cutting quality checks.

    line 54
  11. Very specific:

    All code snippets and example files referenced or produced by this skill must be UTF-8 encoded.

    line 62

“Common” is measured: kept by at least 6 in 10 of the 7 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

Memory Protocol

START: Read .ai-memory.md from project root. Check UI patterns, design decisions, existing previews, brand guidelines, and user flow notes. END: Update .ai-memory.md using Memory Compaction Rules with: what was previewed, assumptions, feedback, and confirmed decisions.

Goal

Show the user what the result will look or feel like before full implementation.

Agent Routing

  • If previewing UI/UX → read .kiro/skills/agents/agents/frontend-specialist.md and apply its knowledge
  • If previewing documentation → read .kiro/skills/agents/agents/documentation-writer.md and apply its knowledge
  • If previewing API response → read .kiro/skills/agents/agents/backend-specialist.md and apply its knowledge

Socratic Gate

Before previewing, verify:

  1. What artifact is being previewed? (UI, API output, document, flow?)
  2. What level of fidelity is expected? (wireframe, mockup, full sample?)
  3. Any specific requirements or constraints? If any answer is unclear, ASK before proceeding.

Workflow

  1. Read Memory — Load .ai-memory.md for project context and design history.
  2. Infer the artifact being previewed: UI, API output, document, message, workflow, or report.
  3. Produce a faithful mock, sample output, walkthrough, or structured preview.
  4. Highlight assumptions behind the preview.
  5. Identify what could change during implementation.
  6. Update Memory — Save preview details and decisions to .ai-memory.md.

Checklist

  • Artifact type identified
  • Preview is realistic and faithful
  • Assumptions clearly labeled
  • Mock data marked as illustrative
  • Implementation differences noted
  • Memory file updated
  • Clean code chuẩn (Standard clean code applied)
  • Cập nhật đầy đủ tất cả các file liên quan (All related files fully updated)

Rules

  • Keep previews realistic and consistent with the current project.
  • Label illustrative content clearly when it is mock data.
  • Avoid implying broad code changes; if the preview would require major refactor, CALL IT OUT and ASK before implementation.
  • Always read and update the memory file.

Quality Gate

After completing, read .kiro/skills/_scripts/checklist.md for cross-cutting quality checks.

Related Skills

  • /create → read .kiro/skills/create/SKILL.md — Implement the previewed design
  • /ui-ux-pro-max → read .kiro/skills/ui-ux-pro-max/SKILL.md — Advanced UI/UX design
  • /plan → read .kiro/skills/plan/SKILL.md — Plan implementation of previewed feature

Encoding

All code snippets and example files referenced or produced by this skill must be UTF-8 encoded. When applicable, include encoding: "UTF-8" in SKILL.md front-matter and ensure saved files use UTF-8 (no BOM).

Download now (ZIP)

  • Other versions15 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 15

    1. getcompanion-ai/feynman★ 10ksame name
    2. advaitpaliwal/feynman★ 10ksame name
    3. companion-inc/feynman★ 10ksame name
    4. nextflow-io/training★ 275same name
    5. typv/nest-turbo-starter★ 224same name
    6. Kangentic/kangentic★ 139same name
    7. kv0906/pm-kit★ 138same name
    8. spmtitsolution/OpenBA-Kit★ 38same name
    9. sanghun0724/cmux-claude-skills★ 33same name
    10. evelan-de/claude-code-plugins★ 3same name

    5 more not listed

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • Used alongsideProjects with it also use ml-training-recipe, replication 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.
    • advaitpaliwalSkill

      ml-training-recipe

      Find implementable ML training recipes from papers, datasets, docs, and code. Use when the user wants to fine-tune, train, reproduce, or choose a practical ML method, dataset, hyperparameter setup, or benchmark recipe.

      Also in 3 projects that use this

    • advaitpaliwalSkill

      replication

      Plan a replication of a paper, claim, or benchmark, and execute only after an explicit environment choice. Use when the user asks to replicate results, reproduce an experiment, verify a claim empirically, or build a replication package.

      Also in 3 projects that use this

    • JaimeParkerSkill

      paper-code-audit

      Perform three-way cross-validation of a research paper by comparing the original paper text (via Zotero), official code implementation (via Git), and personal Obsidian notes. Use this skill whenever the user wants to "audit a paper", "verify paper claims against code", "cross-check notes with implementation", "triangulate paper + code + notes", "find discrepancies between paper and code", or mentions wanting a deep, structured comparison of a paper's claims against its implementation and their own notes. Also trigger when the user asks to "analyze this paper thoroughly" with code available, or when they want to systematically reconcile what the paper says, what the code does, and what their notes claim.

      Also in 3 projects that use this

    • brainbytes-devSkill

      alpha-research

      Also in 3 projects that use this

    • JimLiuSkill

      pdf-explore

      Use this skill when the user has attached a PDF, paper, report, or other document and the answer needs content from more than one place in it: summarize the methods or any other section, compare sections, find where a topic is discussed, read a value or label off a figure or chart, or find/list/extract every instance of something across the whole document (datasets, benchmarks, citations, figures, table rows, accession numbers — including appendices). Skip it only for a single lookup of 1–4 pages quoted in your very next response — `read_file(pages=[...])` attaches pages as images that are dropped from context after one turn, so multi-section answers end up re-reading the same ranges repeatedly. Parses the PDF once in the Python kernel: `pdf_pages` (pages as persistent text), `pdf_outline` (TOC), `pdf_scan` (rank pages by relevance), `pdf_map`/`pdf_extract` (per-page summary / structured fields via parallel haiku calls). For PDF creation/manipulation, use reportlab/pypdf directly.

      Also in 3 projects that use this

    • KISHOR403Skill

      session-search

      This skill should be used when searching Claude Code session transcripts with semantic understanding. Triggers on queries like "find sessions about X", "when did I work on Y", "search previous conversations". Supports natural language queries with synonym matching.

      Also in 3 projects that use this

    • +1 more from advaitpaliwal
  • In this repository96 other files it gives its agents.

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.