app-feature-craft
Skill11 starsChanged 4 months agoMITView on GitHub
Use when implementing or improving a user-facing app workflow. Guides product-grade UX, frontend, backend/API behavior, AI/provider or long-running task states, tests, and end-to-end verification from rough requirements to a shippable feature.
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The file
Show its rules and text
We split this skill into the rules it gives an agent
18 rules. About 0 are common, 15 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈15
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 9
Use this skill to turn an app request into a feature users can actually rely on.
- Distinctive: line 10
Default to shipping the smallest complete behavior, not a technical stub.
- Distinctive: line 18
If visual behavior matters, inspect screenshots or run the app.
- Distinctive: line 29
Keep controls near the user's task context.
- Distinctive: line 32
Prefer reading-first UI with focused edit affordances for dense knowledge or writing surfaces.
- Distinctive: line 43
Follow existing local patterns instead of inventing a new framework.
- Distinctive: line 44
Keep user data safe by default.
- Distinctive: line 46
Do not expose raw backend/browser errors in public UI.
- Distinctive: line 47
Do not report a fake success for external integrations.
- Very specific: line 49
Run only the user-selected AI/profile/configuration set.
- Distinctive: line 51
Keep separate provider profiles and locally saved keys isolated by owner.
- Distinctive: line 56
Verify from the user's seat.
- Distinctive: line 57
Run focused unit/API tests for changed behavior.
- Distinctive: line 58
Run frontend tests for state, copy, and interactions.
- Distinctive: line 59
Use browser or app screenshots for UI/visual changes.
- Very specific: line 72
Read references/app-quality-principles.md before implementing complex app features, AI/provider integrations, long-running jobs, first-run …
- Very specific: line 76
Read references/living-to-tell-casebook.md when the task resembles one of the captured cases: startup feedback, Not Found cleanup, AI …
- Distinctive: line 84
Ask the user only when the decision is product intent and cannot be discovered from the codebase.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
App Feature Craft
Use this skill to turn an app request into a feature users can actually rely on. Default to shipping the smallest complete behavior, not a technical stub.
Workflow
- Ground in the product before designing.
- Inspect routes, screens, state stores, API clients, backend handlers, data models, tests, packaging scripts, and existing copy.
- Resolve discoverable facts from the repo before asking the user.
- If visual behavior matters, inspect screenshots or run the app.
- Define the user-facing outcome.
- State what the user can do after the change.
- Identify the audience, success criteria, in/out of scope, data safety constraints, and where the behavior must appear.
- Separate optional convenience from behavior required for a complete feature.
- Design the whole path.
- Cover UI states: empty, loading, success, failure, stale data, first-run, and already-configured.
- Keep controls near the user's task context. Avoid bolted-on panels, rigid form-heavy surfaces, or result views that disappear behind an ambiguous "back" action.
- Prefer reading-first UI with focused edit affordances for dense knowledge or writing surfaces.
- Cover data/API behavior: persistence, validation, compatibility, migration, idempotency, and failure modes.
- Cover lifecycle behavior for desktop apps: startup, restart, sidecars, installer state, and local paths when relevant.
- For long-running AI or provider work, design background progress, reopening/recovery, cancellation semantics, and honest stage labels before implementing the request.
- Implement narrowly.
- Follow existing local patterns instead of inventing a new framework.
- Keep user data safe by default; never delete, overwrite, or migrate destructively unless the user explicitly asked for it.
- Do not expose raw backend/browser errors in public UI.
- Do not report a fake success for external integrations. Mocked tests prove code paths, not real provider availability.
- Run only the user-selected AI/profile/configuration set. Do not silently add a default provider after the user made an explicit choice.
- Keep separate provider profiles and locally saved keys isolated by owner; never let one profile's credential overwrite another profile's source.
- Make AI-generated drafts, candidate imports, and writeback actions review-first unless the user explicitly requested automatic mutation.
- Verify from the user's seat.
- Run focused unit/API tests for changed behavior.
- Run frontend tests for state, copy, and interactions.
- Use browser or app screenshots for UI/visual changes.
- For provider, installer, or filesystem features, run at least one real local smoke test when credentials and environment are available.
- For background jobs, verify close/reopen, status reconnect, cancellation, completion, and failure states without resending the provider request.
- Report the result.
- Summarize user-visible changes, important files, tests run, and any residual risk.
- Say clearly when a test was mocked, skipped, or only verified locally.
Reference Use
Read references/app-quality-principles.md before implementing complex app
features, AI/provider integrations, long-running jobs, first-run experiences,
data-path behavior, or desktop lifecycle work.
Read references/living-to-tell-casebook.md when the task resembles one of
the captured cases: startup feedback, Not Found cleanup, AI provider transport,
data location safety, installation/version mismatch, async selection races, or
motif/excerpt deduplication, AI result recovery, profile key isolation, or
release asset verification.
Ask Only When Needed
Ask the user only when the decision is product intent and cannot be discovered from the codebase. Prefer one concrete tradeoff question over a broad design question.
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