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Design Submission Check

Community
SeanJ1ang
design-submission-check

Audit a design-award submission package against the current official rules for a specific award cycle. Check required materials and technical constraints, cross-material facts and claims, rights and disclosure risks, and final submission readiness. Use when a user asks for a pre-submission check, compliance review, missing-material audit, consistency check, or final go/no-go decision. Do not use this skill to choose an award, retrieve winners, judge the design itself, rewrite the whole entry, or give a legal clearance opinion.

Overview

PublisherSeanJ1ang
Repositorydesign-judge-skills
Skill namedesign-submission-check
Stars
712
Forks
102
Bundled files
10
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 10 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by SeanJ1ang on GitHub. Read the source before you install it.

Installation

Install the Design Submission Check AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/SeanJ1ang/design-judge-skills/tree/main/skills/design-submission-check
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/SeanJ1ang/design-judge-skills.git /tmp/design-judge-skills
mkdir -p .claude/skills
cp -r /tmp/design-judge-skills/skills/design-submission-check .claude/skills/design-submission-check
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Design Submission Check in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Design Submission Check on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Design Submission Check is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Design Submission Check

Purpose

Determine whether a concrete design-award submission package is complete, internally consistent, and ready to submit under the current official rules for one exact award, track, category, and cycle.

Return one of three decisions:

  • Ready: no Blocker or Important findings remain.
  • Conditionally ready: no Blocker remains, but one or more Important findings require attention.
  • Not ready: at least one Blocker remains.

Scope Boundary

  • Convert current official submission rules into a project-specific checklist.
  • Check required files, fields, declarations, and technical constraints.
  • Compare names, facts, claims, credits, metrics, and versions across materials.
  • Screen rights, permissions, confidentiality, personal-data, and disclosure risks.
  • Perform a final package-level audit and prioritize fixes.
  • Stop after the audit. Do not select the award, score design quality, redesign the project, or perform comprehensive copy-editing.

Use $design-award-match before this skill when the award, track, or category has not been selected. Route design-quality questions to design-evaluation and substantive redesign or rewriting to design-optimization when those skills are available.

Severity Model

Read references/checking-framework.md. Classify every finding:

  • Blocker: likely prevents submission, violates an explicit hard rule, invalidates eligibility, or leaves a mandatory item absent.
  • Important: materially weakens clarity, credibility, consistency, or rights readiness but is not a confirmed hard-rule failure.
  • Optimization: optional improvement that does not affect basic submission readiness.

Never hide an unresolved rule or unreadable file inside an overall percentage. The highest unresolved severity controls the final decision.

User Interaction Contract

Accept:

  • the exact award, track, category, and submission cycle;
  • official rule page, entry guide, or terms when supplied;
  • the submission files or a manifest describing them;
  • applicant, team, project, release, authorship, and rights facts relevant to the entry.

If the award, track/category, or cycle is missing, ask one concise question containing only the missing identifiers. If materials are incomplete, audit what is available and list everything that could not be checked; do not invent a pass.

Offer this template when the user asks how to use the skill:

text
Award / cycle: {exact award and year}
Track / category: {exact official names}
Official rules: {URL or attached guide, optional}
Applicant / team: {names, roles, organization, country or student status}
Submission materials: {attach files or provide paths}
Known third-party content: {images, fonts, music, data, trademarks, AI-generated content}
Requested mode: {full audit / technical check / consistency check / final check}

Audit Workflow

1. Lock the submission target

Record the exact award program, cycle, track, category, applicant type, submission stage, deadline, and official timezone. Do not combine requirements from different cycles, categories, or judging stages.

If the selected target appears inconsistent with the package, report it and refer category selection back to $design-award-match; do not silently change the target.

2. Verify and extract current rules

Read references/rule-evidence-policy.md. At request time, verify current official sources and create a requirement ledger containing:

  • mandatory and optional materials;
  • form fields and declarations;
  • accepted file types, counts, sizes, dimensions, aspect ratios, duration, word or character limits, and languages;
  • filename, anonymity, branding, caption, and credit rules;
  • applicant, authorship, release-window, prototype, and publication restrictions relevant to final submission;
  • rights, consent, AI-use, confidentiality, and disclosure requirements;
  • deadline with an absolute date and official timezone.

Attach an official URL and checked on date to each rule group. Search snippets and third-party summaries are discovery evidence only. When official sources conflict, the most specific current official terms control; report unresolved conflicts as Blockers.

3. Inventory the package

List every supplied file and form field. Assign each item to exactly one requirement ID and record its version, file type, size, technical metadata, language, and readable/openable status.

Use scripts/check_submission_manifest.py for deterministic checks when a local package or structured manifest is available. Prepare inputs using the schemas in examples/rules.example.json and examples/manifest.example.json.

powershell
python scripts/check_submission_manifest.py `
  --rules examples/rules.example.json `
  --manifest examples/manifest.example.json `
  --pretty

The script checks declared metadata and available filesystem facts. It does not replace opening documents, inspecting images, playing videos, or verifying portal behavior.

4. Check completeness and technical compliance

For each requirement, check:

  • presence and required count;
  • readable/openable state;
  • extension and actual format when detectable;
  • file size, dimensions, aspect ratio, resolution, duration, word or character count;
  • naming, language, anonymity, credits, and other explicit restrictions;
  • form fields, checkboxes, declarations, and signatures;
  • deadline and upload-stage compatibility.

Mark an unverified mandatory constraint Not checked, never Pass. Treat a required missing item or confirmed hard-limit failure as a Blocker.

5. Check cross-material consistency and evidence integrity

Read references/consistency-rights-checklist.md. Establish a canonical fact sheet, then compare every material against it:

  • project title, category, applicant, team, roles, organization, dates, and version;
  • problem, target user, primary function, workflow, technology, materials, and sustainability claims;
  • quantities, dimensions, performance, research results, impact metrics, and commercial status;
  • captions, labels, subtitles, voice-over, charts, citations, and credits.

Flag contradictions, unsupported superlatives, missing units, inconsistent denominators, obsolete versions, and claims that exceed the supplied evidence. Do not independently validate scientific or commercial truth unless authoritative evidence is supplied; state the verification limit.

Evaluate narrative only for submission integrity: required content coverage, logical continuity, comprehensibility, and agreement with evidence. Do not perform general stylistic polishing or rewrite the entire entry unless separately requested through the appropriate skill.

6. Screen rights and disclosure risks

Check the provenance and declared permission status of photographs, illustrations, video, music, sound, fonts, icons, maps, datasets, research, code, trademarks, product imagery, personal information, and AI-generated or AI-assisted content.

Use only these statuses:

  • Cleared: the user supplies a credible ownership, license, consent, or permitted-use basis.
  • Pending: permission or required disclosure is being obtained.
  • Unknown: provenance or permission is not established.
  • Restricted: supplied terms appear incompatible with the intended submission use.

This is risk screening, not legal advice or a guarantee of non-infringement. Never mark content legally cleared from appearance alone. Escalate ambiguity in official terms or third-party licenses for qualified review.

7. Run the final gate

Follow references/output-template.md. Before declaring Ready, confirm:

  • all mandatory requirements have been mapped and checked;
  • every Blocker and Important finding has a disposition;
  • final versions are identifiable and no stale duplicate is in the upload set;
  • the portal-entry values match the final files when portal information is available;
  • the deadline and timezone are explicit;
  • a final archive or manifest can reproduce the intended upload set.

If portal behavior, payment, account permissions, or an upload preview cannot be accessed, state that this portion remains a user-executed check.

Decision Rules

  • Current official rules outrank templates, past-cycle guides, organizer emails without context, and third-party summaries.
  • Explicit hard-rule failures are Blockers even when the material is otherwise strong.
  • Missing evidence never becomes a pass by inference.
  • One issue receives one primary severity; cross-reference affected materials instead of duplicating it.
  • Do not use an average score to cancel a Blocker.
  • Rights Pending, Unknown, or Restricted cannot be reported as cleared.
  • A completed offline audit does not prove that the award portal accepted the upload.

Fallback Rules

  • If live official rules cannot be verified, use user-supplied official documents, label rule freshness, and do not return Ready for time-sensitive requirements.
  • If a file cannot be opened, report exactly which checks were impossible and classify mandatory unreadability as a Blocker.
  • If technical metadata cannot be measured, request the metadata or mark the constraint Not checked.
  • If only a partial package is supplied, return a partial audit and a missing-material list, not a final pass.
  • If official rights or AI-disclosure wording is ambiguous, quote minimally, link the rule, and label the issue for qualified review.

Compliance and Safety

  • Inspect only user-authorized files and public official pages.
  • Do not upload materials to an award portal, accept legal declarations, pay fees, or submit on the user's behalf without explicit authorization and an available approved workflow.
  • Do not expose confidential project content in external search queries.
  • Avoid reproducing or redistributing copyrighted submission content beyond what is necessary for the audit.
  • Treat personal data, unpublished designs, credentials, and application identifiers as sensitive.

Example Invocations

  • 使用 $design-submission-check,按照附件中的 iF 当届规则,对这个提交包进行完整终检。
  • 使用 $design-submission-check,只检查所有图片、PDF和视频的数量、格式、大小及命名是否合规。
  • 使用 $design-submission-check,核对表单、展板、说明文档和视频中的项目数据是否一致,并筛查授权风险。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Design Submission Check AI skill do?

Audit a design-award submission package against the current official rules for a specific award cycle. Check required materials and technical constraints, cross-material facts and claims, rights and disclosure risks, and final submission readiness. Use when a user asks for a pre-submission check, compliance review, missing-material audit, consistency check, or final go/no-go decision. Do not use this skill to choose an award, retrieve winners, judge the design itself, rewrite the whole entry, or give a legal clearance opinion.

Why use Design Submission Check on TypingMind?

Because you install it once and use it with any model. Design Submission Check is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Design Submission Check in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/SeanJ1ang/design-judge-skills/tree/main/skills/design-submission-check. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Design Submission Check?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Design Submission Check?

As many as you like. As long as a model supports skills, you can use Design Submission Check with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Design Submission Check AI skill free?

Yes. It is published on GitHub by SeanJ1ang under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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