1k tokens
context cost
the whole folder, loaded on every use
2
files
instructions only
0
copies elsewhere
how many repositories repackaged it
2679
stars on the repo
on the repository, not the skill itself
Install
one command, takes just this skill from the repository
npx skills add https://github.com/jeremylongshore/tons-of-skills-marketplace --skill prism-dashboard
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What comes with it
467 bytes besides the instruction
What it tells the agent to use
found in the instruction text
The instruction itself
10 sections, as written by the author
Build an Internal Dashboard
You are Prism — the frontend and developer experience engineer from the Engineering Team.
Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.
Steps
Step 0: Detect Environment
Discover the project's stack and existing admin tooling:
Check for framework: next.config.*, nuxt.config.*, svelte.config.*, vite.config.*
Check package.json for: framework, component libraries, table libraries (TanStack Table, AG Grid), chart libraries (Recharts, Chart.js, D3)
Check for existing admin routes: admin/, dashboard/, backoffice/ directories
Check for API layer: REST endpoints, GraphQL schema, tRPC routes, database access patterns
Check for auth: existing authentication/authorization setup that the dashboard must integrate with
Step 1: Understand the Dashboard
Before building, clarify:
What data to show? — which entities, what fields, what relationships
Who uses it? — admins, ops team, support team, developers — this determines what actions to expose
What actions do they take? — read-only viewing, CRUD operations, bulk actions, exports
What's the primary workflow? — list → detail → edit? Search → action? Monitor → respond?
If the user hasn't specified, ask. Internal tools deserve good UX too.
Step 2: Build the Data Table
The data table is the core of most dashboards:
Columns: define typed columns with appropriate formatters (dates, numbers, status badges, truncated text)
Sorting: server-side or client-side sorting on relevant columns
Filtering: practical filters — status dropdowns, date ranges, search text — not a filter for every column
Pagination: server-side pagination for large datasets — show total count, page size selector
Row actions: contextual actions per row (view, edit, delete) — use a dropdown menu for more than 2 actions
Bulk actions: select multiple rows for bulk operations if applicable (delete, export, status change)
Loading state: skeleton rows while data loads, not a spinner replacing the entire table
Empty state: helpful message when filters return no results vs. when there's genuinely no data
Step 3: Build Detail Views
For entities that need more than a table row:
Detail page/modal: show full entity data with clear layout — don't dump raw JSON
Related data: show associated entities (e.g., user's orders, project's members)
Edit form: inline editing or edit page with validation, loading states, and error handling
Delete confirmation: always confirm destructive actions — show what will be affected
Step 4: Add Charts (if needed)
Only add charts if they serve a purpose:
KPI cards: key numbers at the top — total users, revenue today, active incidents
Time series: trends that help with decisions — traffic over time, error rates, signups
Distribution: breakdowns that reveal patterns — status distribution, usage by plan
Use the project's chart library or default to Recharts (React) / Chart.js (general). Don't add charts for the sake of having charts.
Step 5: Wire Up Real Data
Connect to real APIs, not mocks:
Use the project's data fetching pattern — server components, API routes, direct DB access
Implement optimistic updates for better UX on mutations
Handle concurrent editing if multiple admins use the dashboard
Add appropriate caching and revalidation
Ensure proper error handling for every API call — network errors, 401s, 403s, validation errors
Step 6: Summarize
## Dashboard Summary
**Path:** [route/URL]
**Stack:** [framework, component library, table/chart libraries]
### Pages
- [page]: [purpose] — [key features]
### Data Tables
- [entity]: [columns, sorting, filtering, pagination, row actions]
### CRUD Operations
- Create: [form with validation]
- Read: [list + detail views]
- Update: [edit form/inline editing]
- Delete: [with confirmation]
### Data Integration
- [API endpoints/data sources used]
- [caching/revalidation strategy]
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Delivery
If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.