본문으로 건너뛰기
cccskills
무료GitHub에 공개

render-icon-pipeline

Run the viz pipeline to render icons from existing glyphs. Entry point for the viz subproject covering palette generation, data building, manifest creation, and icon rendering for skills, agents, and teams. Always use build.sh as the pipeline entry point — never call Rscript directly.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

연동 도구Docker
설치 방법 보기

포함된 파일(1)

  • SKILL.md8.0 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Render Icon Pipeline

Run the viz pipeline end-to-end to render icons from existing glyphs. Covers palette generation, data building, manifest creation, and icon rendering for skills, agents, and teams.

Canonical entry point: bash viz/build.sh [flags] from the project root, or bash build.sh [flags] from viz/. This script handles platform detection (WSL, Docker, native), R binary selection, and step ordering. Never call Rscript directly for build scripts — that path is only for MCP server configuration.

When to Use

  • After creating or modifying glyph functions
  • After adding new skills, agents, or teams to registries
  • When icons need re-rendering for new or updated palettes
  • For a full pipeline rebuild (e.g., after infrastructure changes)
  • When setting up the viz environment for the first time

Inputs

  • Optional: Entity type — skill, agent, team, or all (default: all)
  • Optional: Palette — specific palette name or all (default: all)
  • Optional: Domain filter — specific domain for skill icons (e.g., git, design)
  • Optional: Render mode — full, incremental, or dry-run (default: incremental)

Procedure

Step 1: Verify Prerequisites

Ensure the environment is ready for rendering.

  1. Confirm viz/build.sh exists:
    ls -la viz/build.sh
    
  2. Verify Node.js is available:
    node --version
    
  3. Check that viz/config.yml exists (platform-specific R path profiles):
    ls viz/config.yml
    

build.sh handles R binary resolution automatically — you do not need to verify R paths manually. On WSL it uses /usr/local/bin/Rscript (WSL-native R), on Docker it uses the container R, and on native Linux/macOS it uses Rscript from PATH.

Expected: build.sh, Node.js, and config.yml are present.

On failure: If config.yml is missing, the pipeline falls back to system defaults. If Node.js is missing, install via nvm.

Step 2: Run the Pipeline

build.sh executes 5 steps in order:

  1. Generate palette colors (R) → palette-colors.json + colors-generated.js
  2. Build data (Node) → skills.json
  3. Build manifests (Node) → icon-manifest.json, agent-icon-manifest.json, team-icon-manifest.json
  4. Render icons (R) → icons/ and icons-hd/ WebP files
  5. Generate terminal glyphs (Node) → cli/lib/glyph-data.json

Full pipeline (all types, all palettes, standard + HD):

bash viz/build.sh

Incremental (skip icons that already exist on disk):

bash viz/build.sh --skip-existing

Single domain (skills only):

bash viz/build.sh --only design

Single entity type:

bash viz/build.sh --type skill
bash viz/build.sh --type agent
bash viz/build.sh --type team

Dry run (preview without rendering):

bash viz/build.sh --dry-run

Standard size only (skip HD):

bash viz/build.sh --no-hd

All flags after build.sh are passed through to build-all-icons.R.

Expected: Icons rendered to viz/public/icons/<palette>/ and viz/public/icons-hd/<palette>/.

On failure:

  • renv hang on NTFS: The viz .Rprofile bypasses renv/activate.R and sets .libPaths() directly. Ensure you run from viz/ (build.sh does this automatically via cd "$(dirname "$0")")
  • Missing R packages: Run Rscript -e "install.packages(c('ggplot2', 'ggforce', 'ggfx', 'ragg', 'magick', 'future', 'furrr', 'digest'))" from the R environment that build.sh selects
  • No glyph mapped: The entity needs a glyph function — use the create-glyph skill before rendering

Step 3: Verify Output

Confirm the render completed successfully.

  1. Check file counts match expectations:
    find viz/public/icons/cyberpunk -name "*.webp" | wc -l
    find viz/public/icons-hd/cyberpunk -name "*.webp" | wc -l
    
  2. Check for reasonable file sizes (2-80 KB per icon)
  3. Run the audit-icon-pipeline skill for a comprehensive check

Expected: File counts match manifest entry counts. File sizes in expected range.

On failure: If counts don't match, some glyphs may have errored during rendering. Check the build log for [ERROR] lines.

CLI Flag Reference

All flags are passed through build.sh to build-all-icons.R:

FlagDefaultDescription
--type <types>allComma-separated: skill, agent, team
--palette <name>allSingle palette or all (9 palettes)
--only <filter>noneDomain (skills) or entity ID (agents/teams)
--skip-existingoffSkip icons with existing WebP files
--dry-runoffList what would be generated
--size <n>512Output dimension in pixels
--glow-sigma <n>4Glow blur radius
--workers <n>autoParallel workers (detectCores()-1)
--no-cacheoffIgnore content-hash cache
--hdonEnable HD variants (1024px)
--no-hdoffSkip HD variants
--strictoffExit on first sub-script failure

What build.sh Does Internally

For reference only — do NOT run these steps manually:

cd viz/
# 1. Platform detection: sets R_CONFIG_ACTIVE (wsl, docker, or unset)
# 2. R binary selection: WSL → /usr/local/bin/Rscript, Docker → same, native → Rscript
# 3. $RSCRIPT generate-palette-colors.R
# 4. node build-data.js
# 5. node build-icon-manifest.js --type all
# 6. $RSCRIPT build-all-icons.R "$@"  (flags passed through)
# 7. node build-terminal-glyphs.js

Docker Alternative

The pipeline can also run in Docker:

cd viz
docker compose up --build

This runs the full pipeline in an isolated Linux environment and serves the result on port 8080.

Validation Checklist

  • Ran bash viz/build.sh (not bare Rscript)
  • Palette colors generated (JSON + JS)
  • Data files built from registries
  • Manifests generated from data
  • Icons rendered for target types and palettes
  • File counts match expectations
  • File sizes in expected range (2-80 KB)

Common Pitfalls

  • Calling Rscript directly: Never run Rscript build-icons.R or Rscript generate-palette-colors.R manually. Always use bash build.sh [flags]. Direct Rscript calls bypass platform detection and may use the wrong R binary (Windows R via ~/bin/Rscript wrapper instead of WSL-native R at /usr/local/bin/Rscript). Note: the Windows R path in CLAUDE.md and guides is for MCP server configuration only, not for build scripts.
  • Wrong working directory: build.sh CDs to its own directory automatically (cd "$(dirname "$0")"), so you can call it from anywhere: bash viz/build.sh from project root works correctly.
  • Stale manifests: build.sh runs Steps 1-5 in order, so manifests are always regenerated before rendering. If you only need manifests without rendering, use node viz/build-data.js && node viz/build-icon-manifest.js (the Node steps don't need R).
  • renv not activated: The .Rprofile workaround requires running from viz/ — build.sh handles this. Using --vanilla flag or running R from another directory will skip it.
  • Parallel on Windows: Windows doesn't support fork-based parallelism — the pipeline auto-selects multisession via config.yml.

Related Skills

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Execute structural metamorphosis using strangler fig migration, chrysalis phases, and interface preservation. Covers transformation planning, parallel running, progressive cutover, rollback design, and post-metamorphosis stabilization for system architecture evolution. Use when assess-form has classified the system as READY for transformation, when migrating from monolith to microservices, when replacing a core subsystem while dependents continue operating, or when any architectural change must be gradual rather than big-bang.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

pjt222/agent-almanac422026년 10월 22일 업데이트

adaptic

무료

Master skill composing the 5-step synoptic cycle for panoramic synthesis across multiple domains. Orchestrates meditate, expand-awareness, observe, awareness, integrate-gestalt, and express-insight into a coherent process that produces unified understanding rather than sequential compromise. Use when a problem genuinely spans 3+ domains and the interactions between domains matter more than depth in any one, when sequential analysis feels like compromise rather than integration, or before major architectural decisions affecting multiple stakeholders.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

pjt222/agent-almanac422026년 10월 22일 업데이트

Scaffold a new puzzle type across all 10+ pipeline integration points in jigsawR. Creates the core puzzle module, wires it into the unified pipeline (generation, positioning, rendering, adjacency), adds ggpuzzle geom/stat layers, updates DESCRIPTION and config.yml, extends the Shiny app, and creates a comprehensive test suite. Use when adding a completely new puzzle type to the package or following the 10-point integration checklist to ensure nothing is missed end-to-end.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

pjt222/agent-almanac422026년 10월 22일 업데이트

Add Rcpp or RcppArmadillo integration to an R package for high-performance C++ code. Covers setup, writing C++ functions, RcppExports generation, testing compiled code, and debugging. Use when an R function is too slow and profiling confirms a bottleneck, when you need to interface with existing C/C++ libraries, or when implementing algorithms (loops, recursion, linear algebra) that benefit from compiled code.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

pjt222/agent-almanac422026년 10월 22일 업데이트

aikido

무료

Practice aikido as a defensive martial art emphasizing harmony, redirection, and controlled resolution. Covers centering and grounding, ukemi (safe falling and rolling), core techniques (irimi-nage, shiho-nage, kote-gaeshi, ikkyo), blending and tai sabaki (body movement), randori (multiple attacker practice), weapons awareness, and applying principles off the mat. Use when learning a defensive martial art that prioritizes de-escalation, developing the ability to redirect aggression without causing unnecessary harm, building safe falling skills, or cultivating calm centeredness under physical pressure.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

pjt222/agent-almanac422026년 10월 22일 업데이트

Analyze an arbitrary codebase to identify functions, APIs, and data sources suitable for exposure as MCP tools, producing a tool specification document. Use when planning an MCP server for an existing project, auditing a codebase before wrapping it as an AI-accessible tool surface, comparing what a codebase can do versus what is already exposed via MCP, or generating a tool spec to hand off to scaffold-mcp-server.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

pjt222/agent-almanac422026년 10월 22일 업데이트

pjt222의 스킬 모두 보기

이 스킬의 문제 신고