Contractor‑Ready JSON‑LD Feature Library: Ship 10 Machine‑Readable Feature Cards From One Figma Mockup
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Return to blogCONTRACTOR‑READY JSON‑LD FEATURE LIBRARY: SHIP 10 MACHINE‑READABLE FEATURE CARDS FROM ONE FIGMA MOCKUP
Ship machine-readable product artifacts from design to contract in a day. This guide gives a focused, repeatable workflow for product teams: take one Figma mockup, extract 10 distinct feature cards (JSON‑LD SoftwareApplication entries), generate concise acceptance tests and a contract brief for each card, and produce SEO- and agent-ready structured data that developers and contractors can use immediately.
Section 1
Why machine‑readable feature cards matter (and what to expect)
A small library of JSON‑LD feature cards turns a vague mockup into assets that power multiple downstream uses: SEO-rich search snippets, agent retrieval and reasoning, contract language for contractors, and executable acceptance tests. Using the SoftwareApplication type in schema.org standardizes how features are described so search engines and automated systems can understand and index them. (schema.org)
This guide expects: one finished Figma mockup (screens or a component page), a short feature decomposition session (10 minutes), and a simple toolchain: a Figma-to-JSON export, a small JSON-LD template, and a lightweight test generator. The result is 10 contractor-ready deliverables: feature card (JSON‑LD), 3–6 line acceptance tests, and a one‑page contract brief per feature.
- Primary output: JSON‑LD SoftwareApplication feature cards (10)
- Secondary outputs: acceptance tests and one‑page contract briefs
- Uses: SEO snippets, agentic retrieval, onboarding for contractors, press one-pagers
Section 2
Step 1 — From Figma mockup to structured feature list
Open the mockup and run a 10‑minute micro‑decomposition: identify independent user-visible features (e.g., sign-in, email notifications, CSV export, inline editing). Aim for 10 cards — each card maps to a distinct interaction or product promise. This keeps scope small and makes handover precise.
Use a Figma export plugin (or the Figma Plugin API) to extract frame names, text layers, and component metadata as JSON. Popular community plugins and export tools create a JSON representation of frames and component properties you can parse automatically. If you prefer manual extraction, copy each feature title and 1–2 lines of description into a spreadsheet to prepare JSON-LD fields. (figma2json.com)
- Decompose: find 10 independent feature intents in the mockup.
- Extract: use a Figma-to-JSON plugin or the plugin API to get text and component metadata.
- Prepare: map extracted text to three canonical fields — name, shortDescription, screenshot (image URL or exported PNG).
Sources used in this section
Section 4
Step 3 — Generate short acceptance tests and a one‑page contract brief
Turn each feature card into 3–6 line acceptance tests using the Given‑When‑Then style. Keep tests implementation‑agnostic and testable by a contractor or QA: Given (initial state), When (user action), Then (observable result). Use the description and featureList from the JSON‑LD card to seed these statements. A simple acceptance test doubles as a QA checklist and a minimal contract deliverable.
Create a one‑page contract brief per feature: 1) feature name and card @id, 2) shortDescription (from JSON‑LD), 3) acceptance tests, 4) acceptance criteria (pass/fail rules), 5) deliverables (assets, screenshots, API endpoints), and 6) estimated hours. This brief becomes the agreement artifact you include in scopes of work and contractor tickets. For acceptance criteria templates and examples, product management playbooks and PM templates are useful starting points. (pmread.org)
- Acceptance tests: 3–6 lines using Given‑When‑Then
- Contract brief: one page — includes JSON‑LD @id and acceptance tests
- Use the same JSON‑LD fields to auto-fill the brief and tests to avoid drift
Sources used in this section
Section 5
Step 4 — Automation and delivery: pipelines that scale
Automate export + generation: write a small script (Node/Python) that reads the Figma JSON export, maps frames to the JSON‑LD template, and emits: (a) 10 JSON‑LD files, (b) acceptance tests as markdown, and (c) contract briefs as PDF or markdown. Use the Figma REST or Plugin API if you need repeatability across files; community plugins and exporters often provide ready-made JSON outputs to speed the process. (figma2json.com)
Where to put the generated artifacts: publish JSON‑LD into feature landing pages (script blocks) or host a /.well-known or API endpoint that agents can query. Maintain a small index file linking feature @ids so search crawlers, press kits, and agent systems can discover the library. This single-source approach keeps SEO, press, and developer-facing contracts aligned and prevents duplication. Also consider adding lastModified timestamps so consumers can detect changes.
- Automation: script mapping from exported Figma JSON → JSON‑LD → tests → briefs
- Publishing: embed JSON‑LD into pages or provide a discoverable machine endpoint
- Governance: include lastModified and @id to prevent drift
Sources used in this section
FAQ
Common follow-up questions
Can I use JSON‑LD feature cards for both SEO and contracts?
Yes. A concise JSON‑LD SoftwareApplication card provides a machine‑readable description that search engines and agents can index while the same content (name, description, feature list) can be copy‑pasted into a one‑page contract brief and acceptance tests. Keep the JSON‑LD focused and authoritative; use the same source fields to generate contract text to avoid drift. (schema.org)
What tools do I need to extract data from Figma?
Use a Figma-to-JSON exporter plugin or the Figma Plugin API/export endpoints. Several community plugins export frames, text layers, and component metadata as JSON which you can parse. For repeatable, production workflows, build a small script that calls the Figma REST or Plugin API to retrieve the file and convert it to your JSON‑LD template. (figma2json.com)
How strict must I be with schema.org fields?
Follow the SoftwareApplication examples from schema.org and Google Search Central for compatibility, but prioritize simplicity: include @context, @type, @id, name, description, and image. Optional fields like applicationCategory and softwareRequirements are helpful but not required. More properties can improve agentic retrieval but increase maintenance. (schema.org)
How do I keep JSON‑LD and contract briefs in sync?
Treat the JSON‑LD card as the single source of truth and auto‑generate briefs and acceptance tests from it. Include lastModified dates and a stable @id in each card. Add this generation as part of your release checklist so every design change triggers regeneration and a short review. Automation reduces human error and keeps contractors working from current specs.
Sources
Research used in this article
Each generated article keeps its own linked source list so the underlying reporting is visible and easy to verify.
schema.org
SoftwareApplication - Schema.org Type
https://schema.org/SoftwareApplication
Software App (SoftwareApplication) Schema | Google Search Central
https://developers.google.com/search/docs/appearance/structured-data/software-app
Referenced source
Figma To JSON - Figma2JSON (plugin and exporter)
https://www.figma2json.com/
Referenced source
Figma to JSON - Plugin (figma2json plugin page)
https://www.figma2json.com/plugin
PMRead
Free Acceptance Criteria Template for Product Managers | PMRead
https://pmread.org/templates/acceptance-criteria
Referenced source
Figma Plugin | Layout Docs (export patterns & automation)
https://layout.design/docs/figma-plugin
Referenced source
SoftwareApplication - Schema.org Type
https://schema.org/SoftwareApplication?utm_source=openai
Referenced source
Figma to JSON - File
https://www.figma2json.com/?utm_source=openai
Next step
Turn the idea into a build-ready plan.
AppWispr takes the research and packages it into a product brief, mockups, screenshots, and launch copy you can use right away.