Invocation
Output
The skill writes a self-contained HTML file to/tmp/matrix.html and opens it in the browser. The matrix features:
- Color-coded cells (green / blue / orange / red)
- Sort on every column (click any header)
- Filter by competitor name (case-insensitive)
- Dark background (
#1e1e2e) - A “Last updated: YYYY-MM-DD” line above the table
Rating scale
All ratings use the four-point scale exclusively. No numbers, percentages, stars, or prose in cells:| Symbol | Meaning | Cell color |
|---|---|---|
checkcheck | Excellent | Green (#27ae60) |
check | Good | Blue (#2980b9) |
tilde | Partial / mixed | Orange (#d35400) |
x | Poor / missing | Red (#c0392b) |
Workflow
Identify the space
Confirm the market, product category, or technology being compared. Ask for clarification if the scope is ambiguous.
List the players
Enumerate 5–10 key competitors or options to include. If the user lists more than 10, select the 10 most relevant and note the exclusions — matrices with more than 10 rows become unreadable.
Choose evaluation dimensions
Select 5–8 columns relevant to this specific domain. Avoid generic filler columns. Dimensions should reflect what actually differentiates the players in this space.
Research each player
Run at least one web search per player to verify current status and ratings. Training data goes stale; search results do not. Never assign a rating without a supporting search result from this session.
Assign ratings
Score every cell using the four-point scale with evidence from the research step. Every cell must have a rating — no blanks.
Write the HTML file
Write a complete self-contained file to
/tmp/matrix.html using the template from TEMPLATE.md. The file must include: color-coded cells, sortable columns, a filter input, the dark background, and the “Last updated” date.Open in browser and screenshot
Call
mcp__chrome-devtools__new_page with url: file:///tmp/matrix.html. Wait for the first competitor name to appear (wait_for, timeout 8000ms). Then take a screenshot.Self-review checklist
Before delivering, verify all of the following:- At least one web search run per player — no player rated from training data alone
- Between 5 and 10 players in the matrix
- Between 5 and 8 evaluation dimension columns, plus a Verdict column as the last column
- Every cell has a rating from the four-point scale — no blanks, no numbers
- Every cell is color-coded with the correct color for its rating
- A “Last updated: YYYY-MM-DD” line appears above the table
- Sort works on every column
- Filter input present and filters by competitor name (case-insensitive)
- Dark background (
#1e1e2e) applied - Screenshot taken after
wait_for— not immediately afternew_page
Golden rules
1. Never rate from training data alone
1. Never rate from training data alone
Run at least one web search per player before assigning any rating. Training data goes stale; search results do not.
2. Always use the four-point scale exclusively
2. Always use the four-point scale exclusively
The only valid ratings are
checkcheck, check, tilde, and x. Never use numbers, percentages, stars, or prose in cells.3. Always include a Verdict column
3. Always include a Verdict column
Every row must end with a 5–10 word phrase summarising that player’s position. The Verdict column is the last column.
4. Always color-code every cell
4. Always color-code every cell
A matrix where all cells look the same is broken. Color-coding is what makes the matrix readable at a glance.
5. Never include more than 10 players
5. Never include more than 10 players
Matrices with more than 10 rows become unreadable. If the user lists more, select the 10 most relevant and note the exclusions.
6. Always include a Last updated date
6. Always include a Last updated date
Competitive landscapes change. The date the research was conducted must appear above the table in the rendered output.
Reference files
| File | Contents |
|---|---|
TEMPLATE.md | Complete HTML template with color-coded cell rendering, sort/filter JS, CSS design tokens, and rating scale constants |
RESEARCH.md | How to choose evaluation dimensions, research each player, assign ratings, and handle stale or conflicting data |