Skip to main content

design-judge-skills

Evidence-driven agent skills for design award research, evaluation, matching, entry preparation, and submission checks across 11+ major design awards

Ir a la instalación

Datos de origen

Repositorio
reason-machines/design-skills
Última actividad en el origen
30 de julio de 2026 a las 00:25
Idioma detectado de SKILL.md
inglés
Estrellas
4
Forks
0

Opciones de instalación

De forma predeterminada está seleccionado el prompt que primero revisa el origen. Puedes cambiar a un comando directo o descargar una copia local.

Revisa los archivos de origen

Lee SKILL.md y los archivos complementarios que muestra SkillsMP antes de decidir si quieres instalarlo.

Mostrando SKILL.md

SKILL.md
Instrucciones de origen · Vista previa de solo lectura
name
design-judge-skills
description
Evidence-driven agent skills for design award research, evaluation, matching, entry preparation, and submission checks across 11+ major design awards
triggers
["help me apply for design awards","evaluate this design for award submission","find similar award-winning designs","which design award should I enter","prepare my design award entry text","check my award submission package","design award pipeline workflow","match my project to design awards"]
# design-judge-skills > Skill by [ara.so](https://ara.so) — Design Skills collection. `design-judge-skills` is a collection of modular agent skills that decompose the design award application process into discrete, verifiable workflows: award-winning case research, design evaluation, award matching, entry writing, and submission readiness checks. The project covers 11 major design awards including iF DESIGN AWARD, Red Dot, IDEA, DIA, K-Design, GOOD DESIGN AWARD Japan, Core77, James Dyson Award, and EPDA. It includes observational data from **22,125 award-winning or finalist works** and enforces evidence-based evaluation with official source validation. ## Installation ### NPX Skills Installation (Recommended) Requires [Node.js 18+](https://nodejs.org/). **List available skills:** ```bash npx skills add SeanJ1ang/design-judge-skills --list ``` **Install all skills globally for Codex:** ```bash npx skills add SeanJ1ang/design-judge-skills --global --agent codex --skill '*' --yes --copy ``` **Install for Claude Code:** ```bash npx skills add SeanJ1ang/design-judge-skills --global --agent claude-code --skill '*' --yes --copy ``` **Install a single skill with dependencies:** ```bash # design-award-search and design-award-match require design-judge-shared npx skills add SeanJ1ang/design-judge-skills --global --agent codex \ --skill design-award-search --skill design-judge-shared --yes --copy ``` **Install to all supported agents:** ```bash npx skills add SeanJ1ang/design-judge-skills --all ``` **Check and update:** ```bash npx skills list --global --agent codex npx skills update --global --yes ``` ### Manual Installation For agents that support `SKILL.md` format: 1. Clone the repository to a stable path 2. Copy complete skill directories to your agent's skill directory 3. Preserve `SKILL.md`, `agents/`, `references/`, `scripts/`, `examples/`, and `tests/` 4. When installing `design-award-search` or `design-award-match`, also install `design-judge-shared` ## Skills Overview The project provides 6 user-facing skills plus 1 shared support package: | Skill | Status | Purpose | |-------|--------|---------| | `design-award-pipeline` | Beta | Orchestrates multi-stage award workflows and maintains handoff records | | `design-award-search` | Stable | Retrieves and verifies similar award-winning cases from official sources | | `design-evaluation` | Beta | Evaluates design quality and presentation with evidence-based scoring | | `design-award-match` | Beta | Matches projects to awards, tracks, and categories with eligibility checks | | `design-information-prep` | Beta | Extracts facts and prepares award entry text from user materials | | `design-submission-check` | Beta | Validates submission packages against current official requirements | | `design-judge-shared` | Support | Shared taxonomy and source registry (dependency only) | ## Workflow Patterns ### Complete Award Application Pipeline ```text Use $design-award-pipeline to plan the complete award route from the provided materials and maintain stage handoff records. ``` The pipeline skill determines the minimal sufficient path based on user intent and current materials. It does NOT force execution of all stages. ### Finding Award-Winning Benchmarks ```text Use $design-award-search to find officially verified award-winning cases similar to this rehabilitation training product. ``` **Key behaviors:** - Searches official award galleries (iF, Red Dot, IDEA, etc.) - Verifies each case by navigating to the official detail page - Reports case metadata: award name, year, category, project title, designer, country - Search summaries and third-party sites are used for discovery only ### Evaluating Design Quality ```text Use $design-evaluation to evaluate the design in the attached files. I confirm the maturity level as "student concept". Output separate scores for design substance, presentation quality, evidence confidence, and critical issues. ``` **Maturity levels** (user must specify): - `student-concept`: Conceptual work without market release - `early-stage-product`: Pre-production or limited release - `market-product`: Publicly available commercial product **Evaluation dimensions:** - Design substance (innovation, user value, feasibility, sustainability) - Presentation quality (visual clarity, narrative logic, material completeness) - Evidence confidence (factual vs. inferred vs. needs-user-confirmation) - Critical issues (structural disqualifiers, misrepresentation risks, IP concerns) **Example output structure:** ```markdown ## Design Substance: 7.8/10 - Innovation: 8/10 [evidence: novel mechanism in attached patent draft] - User Value: 8/10 [evidence: user research summary p.3] - Feasibility: 7/10 [inferred from CAD model; material sourcing not confirmed] - Sustainability: 8/10 [evidence: LCA report attached] ## Presentation Quality: 6.5/10 - Visual Clarity: 7/10 - Narrative Logic: 6/10 [gap: user journey not visualized] - Material Completeness: 6/10 [missing: technical specs diagram] ## Evidence Confidence: MEDIUM - 60% factual (from attached documents) - 25% model inference (from images and context) - 15% needs user confirmation (material sourcing, certifications) ## Critical Issues: 2 items 1. [ELIGIBILITY] Production timeline unclear → may affect student vs. professional track 2. [EVIDENCE] Sustainability claim lacks third-party certification ``` Scores are for decision support only. They do NOT predict award probability. ### Matching Awards and Categories ```text Use $design-award-match to compare award fit for iF Student, Red Dot Design Concept, DIA, Core77, and James Dyson for this project. ``` **Match outputs:** - Structural eligibility (geographic, entity type, IP rights, timeline) - Category recommendations with official taxonomy references - Track selection (when applicable: student vs. professional, concept vs. product) - Award fee, deadline (re-verified from official pages at runtime) - Submission priority ranking with rationale **Example snippet:** ```markdown ## iF DESIGN STUDENT AWARD - Eligibility: ✓ PASS (student status confirmed, no geographic restriction) - Best Category: 08 Health & Care → 08.03 Rehabilitation - Fee: €0 (student track) - Deadline: 2026-12-15 (re-verified from https://ifdesign.com/en/student-award) - Priority: HIGH (strong alignment with evaluation criteria; no concept-stage penalty) ## Red Dot Design Concept - Eligibility: ✓ PASS (concept stage accepted) - Best Category: Living → Wellness & Healthcare - Fee: €299 Early Bird / €399 Regular - Deadline: 2026-10-31 Early / 2026-12-31 Regular - Priority: MEDIUM (good fit but higher cost; consider after iF Student results) ``` ### Preparing Entry Text ```text Use $design-information-prep to prepare IDEA entry text from the attached materials. First list missing facts, then output English drafts with character count validation. ``` **Workflow:** 1. Extracts facts from user-provided documents (briefs, research, specs, images) 2. Reports missing mandatory fields for target award 3. Generates entry text drafts (title, description, innovation statement, etc.) 4. Validates character/word limits against official requirements 5. Tags each sentence with source attribution or `[INFERRED]` / `[USER CONFIRM]` **Example output:** ```markdown ## Missing Information for IDEA Entry - [ ] Project completion date (required) - [ ] Retail price or production cost estimate - [ ] Specific material certifications (referenced in sustainability claim) ## Draft: Project Title (max 100 chars) **VitalGrip Rehabilitation Glove** [78 chars] ✓ ## Draft: Design Innovation (max 500 words) VitalGrip introduces a modular resistance system... [source: design brief p.2] The sensor array provides real-time feedback... [source: technical spec diagram] Preliminary user testing showed 40% improvement... [INFERRED from user research summary; USER CONFIRM exact metric] [Draft continues...] Word count: 487/500 ✓ ``` ### Submission Readiness Check ```text Use $design-submission-check to validate this submission package against current Red Dot Product Design official requirements and provide a go/no-go recommendation. ``` **Check dimensions:** - File format, resolution, size limits (re-verified from official submission guide) - Mandatory vs. optional materials completeness - Consistency across title, description, category, visual materials - IP and rights declarations (model releases, trademark conflicts, authorship) - Payment and entry form status **Output format: go / conditional go / no-go** ```markdown ## Submission Check: Red Dot Product Design 2027 ### File Compliance: ✓ PASS - Main image: 3000×2250px JPG, 4.2MB ✓ - Supporting images (4): all 3000×2250px JPG ✓ - Video: MP4 1920×1080, 45s, 28MB ✓ ### Content Completeness: ⚠ CONDITIONAL - ✓ Project title, description, category - ✓ Designer/company information - ⚠ Innovation statement present but does NOT reference technical validation (recommended for this category) - ✗ Sustainability documentation missing (required for "Sustainable Product" sub-category) ### Consistency Check: ✓ PASS - Title matches across entry form and visual materials - Category "01.03 Medical & Health" aligns with project scope ### Rights & IP: ⚠ CONDITIONAL - ✓ Designer authorship declared - ⚠ Model release for user testing photos not provided (required if faces visible) ## Recommendation: CONDITIONAL GO **Action required before submission:** 1. Upload model release forms for user testing photos 2. Add technical validation reference to innovation statement (recommended) 3. Either remove "Sustainable Product" tag OR provide third-party certification **Estimated fix time:** 2-4 hours ``` ## Configuration & Data Sources ### Official Source Validation Skills re-verify time-sensitive information (deadlines, fees, eligibility, format specs) at runtime by scraping official award pages. The `design-judge-shared/source-registry.md` maintains canonical URLs. **Example source registry entry:** ```markdown ### iF DESIGN AWARD - Main: https://ifdesign.com/en/design-award - Submission Guide: https://ifdesign.com/en/submit - Categories: https://ifdesign.com/en/categories - Winners Gallery: https://ifdesign.com/en/winner-gallery ``` ### Category Taxonomy `design-judge-shared/category-taxonomy.md` maintains normalized category mappings across awards. Example: ```markdown ## Health & Medical Devices - iF: 08 Health & Care - Red Dot: Living → Wellness & Healthcare - IDEA: Medical & Scientific Products - DIA: Healthcare & Wellness - K-Design: Medical & Health ``` ### Observational Benchmark Data Evaluation skills reference 22,125 aggregated observations from past winners (2015-2025) to provide descriptive context. This data: - Does NOT alter core scoring logic - Does NOT predict award probability - Provides pattern recognition for presentation quality and category norms - Is anonymized (no private project details) See [benchmark coverage documentation](docs/benchmark-coverage.md) for privacy and limitation details. ## Environment Variables No API keys or authentication required for basic functionality. Optional: ```bash # For enhanced web scraping (if official sites use anti-bot measures) export BROWSERLESS_API_KEY=your_key_here # For bulk processing (optional concurrency limit) export MAX_CONCURRENT_EVALUATIONS=5 ``` ## Common Patterns ### Pattern 1: Student Concept → Award Route ```python # User provides: concept boards, research deck, CAD renderings # Agent workflow: # Step 1: Evaluate to confirm strengths and gaps "Use $design-evaluation with maturity level 'student-concept'" # Step 2: Match to student-friendly awards "Use $design-award-match to compare iF Student, Red Dot Concept, Core77, James Dyson, and DIA for this student concept" # Step 3: Prepare entry for top match "Use $design-information-prep for iF DESIGN STUDENT AWARD" # Step 4: Pre-submission check "Use $design-submission-check for iF Student entry package" ``` ### Pattern 2: Multi-Award Strategy ```python # For a market product targeting multiple awards: # Step 1: Find positioning benchmarks "Use $design-award-search to find similar award winners in the smart home category from the past 3 years" # Step 2: Evaluate against benchmark patterns "Use $design-evaluation with maturity level 'market-product'" # Step 3: Prioritize awards by fit and cost "Use $design-award-match to compare iF, Red Dot Product, IDEA, DIA, K-Design, and GOOD DESIGN Japan" # Step 4: Batch prepare entries for top 3 "Use $design-information-prep for iF DESIGN AWARD, Red Dot Product Design, and IDEA" ``` ### Pattern 3: Pipeline Orchestration ```python # When user says: "I have a rehabilitation glove concept and want to enter design awards" "Use $design-award-pipeline to determine the optimal workflow and maintain handoff state" # Pipeline decides minimal path, e.g.: # 1. Evaluation (to assess readiness) # 2. Award match (to select targets) # 3. Information prep (for selected awards) # 4. Submission check (before deadline) # Pipeline maintains state file to resume or skip stages ``` ## Troubleshooting ### Issue: Skill not triggering **Solution:** After installation, start a NEW agent session to refresh skill registry. For Codex: ```bash npx skills list --global --agent codex # verify installation # Then restart Codex session ``` ### Issue: "Missing design-judge-shared" error **Solution:** Install the shared dependency: ```bash npx skills add SeanJ1ang/design-judge-skills --global --agent codex \ --skill design-judge-shared --yes --copy ``` ### Issue: Evaluation returns "insufficient evidence" **Cause:** Missing or ambiguous design materials. **Solution:** Provide at minimum: - Visual materials (renderings, photos, or presentation boards) - Project description (brief, design statement, or report) - Maturity level confirmation from user ### Issue: Award match returns "eligibility unclear" **Cause:** Missing structural information (student status, geographic location, IP ownership, production timeline). **Solution:** Explicitly confirm: - Entity type (student, startup, established company) - Designer location (for geographic restrictions) - IP ownership status - Project completion date (for timeline-based eligibility) ### Issue: Official page scraping fails **Cause:** Award website structure changed or anti-bot protection. **Temporary workaround:** Manually verify deadline/fee from official site and provide to agent: ```text I've verified from the official iF page: deadline is 2026-12-15, fee is €0 for students. Use this information for the match analysis. ``` **Long-term fix:** Report the issue at https://github.com/SeanJ1ang/design-judge-skills/issues with the affected award and URL. ### Issue: Character count validation fails **Cause:** Award official requirement changed. **Solution:** Cross-check the current submission guide link in `design-judge-shared/source-registry.md` and report discrepancy as an issue. ## Testing Each skill includes example inputs and expected outputs in `skills/<name>/examples/` and automated tests in `skills/<name>/tests/`. **Run tests for a specific skill:** ```bash cd skills/design-evaluation python tests/test_evaluation.py ``` **Run all tests:** ```bash python run_all_tests.py ``` ## Design Principles 1. **Official sources first:** Award rules and cases reference official pages; search summaries and third-party sites are for discovery only 2. **Separate fact from inference:** User materials, model inferences, and user-confirmation items are explicitly tagged 3. **Transparent scoring:** Fit scores and evaluation ratings support decisions but DO NOT predict award probability 4. **Single responsibility:** Skills do not cross boundaries (search ≠ evaluation ≠ matching ≠ prep ≠ check) 5. **No official impersonation:** Skills align with public criteria but do not simulate undisclosed judge preferences or internal processes ## Contributing See [contribution guidelines](docs/CONTRIBUTING.md). Key points: - Skill directory names match frontmatter `name` (kebab-case only) - Core workflows stay in `SKILL.md`; long rules/specs go in `references/` - Repeatable operations become `scripts/` with corresponding tests - Do NOT commit API keys, cookies, user project materials, or copyrighted full case content - Current year, deadlines, fees, and format specs must be runtime-verified from official sources
Ver en GitHub
Este SKILL.md es muy grande, por eso SkillsMP muestra aqui solo la primera seccion. Ver en GitHub