Fetches shapely-compute from parcadei/continuous-claude-v3 and configures it for Cursor.
3
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/shapely-compute
Restart Cursor to activate shapely-compute. Access via /shapely-compute in your agent's command palette.
⚠
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
op intersection --g1 "POLYGON(...)" --g2 "POLYGON(...)"
Check contains
pred contains
pred contains --g1 "POLYGON(...)" --g2 "POINT(0.5 0.5)"
Calculate area
measure area
measure area --geom "POLYGON(...)"
Distance
distance
distance --g1 "POINT(0 0)" --g2 "POINT(3 4)"
Transform
transform translate
transform translate --geom "..." --params "1,2"
Validate
validate
validate --geom "POLYGON(...)"
Commands
create
Create geometric objects from coordinates.
# Pointuv run python scripts/shapely_compute.py create point --coords"1,2"# Line (2+ points)uv run python scripts/shapely_compute.py create line --coords"0,0 1,1 2,0"# Polygon (3+ points, auto-closes)uv run python scripts/shapely_compute.py create polygon --coords"0,0 1,0 1,1 0,1"# Polygon with holeuv run python scripts/shapely_compute.py create polygon --coords"0,0 10,0 10,10 0,10"--holes"2,2 8,2 8,8 2,8"# MultiPointuv run python scripts/shapely_compute.py create multipoint --coords"0,0 1,1 2,2"# MultiLineString (pipe-separated lines)uv run python scripts/shapely_compute.py create multilinestring --coords"0,0 1,1|2,2 3,3"# MultiPolygon (pipe-separated polygons)uv run python scripts/shapely_compute.py create multipolygon --coords"0,0 1,0 1,1 0,1|2,2 3,2 3,3 2,3"
op (operations)
Boolean geometry operations.
# Intersection of two polygonsuv run python scripts/shapely_compute.py op intersection \--g1"POLYGON((00,20,22,02,00))"\--g2"POLYGON((11,31,33,13,11))"# Unionuv run python scripts/shapely_compute.py op union --g1"POLYGON(...)"--g2"POLYGON(...)"# Difference (g1 - g2)uv run python scripts/shapely_compute.py op difference --g1"POLYGON(...)"--g2"POLYGON(...)"# Symmetric difference (XOR)uv run python scripts/shapely_compute.py op symmetric_difference --g1"..."--g2"..."# Buffer (expand/erode)uv run python scripts/shapely_compute.py op buffer --g1"POINT(0 0)"--g2"1.5"# Convex hulluv run python scripts/shapely_compute.py op convex_hull --g1"MULTIPOINT((00),(11),(02),(20))"# Envelope (bounding box)uv run python scripts/shapely_compute.py op envelope --g1"POLYGON(...)"# Simplify (reduce points)uv run python scripts/shapely_compute.py op simplify --g1"LINESTRING(...)"--g2"0.5"
pred (predicates)
Spatial relationship tests (returns boolean).
# Does polygon contain point?uv run python scripts/shapely_compute.py pred contains \--g1"POLYGON((00,20,22,02,00))"\--g2"POINT(1 1)"# Do geometries intersect?uv run python scripts/shapely_compute.py pred intersects --g1"..."--g2"..."# Is g1 within g2?uv run python scripts/shapely_compute.py pred within --g1"POINT(1 1)"--g2"POLYGON(...)"# Do geometries touch (share boundary)?uv run python scripts/shapely_compute.py pred touches --g1"..."--g2"..."# Do geometries cross?uv run python scripts/shapely_compute.py pred crosses --g1"LINESTRING(...)"--g2"LINESTRING(...)"# Are geometries disjoint (no intersection)?uv run python scripts/shapely_compute.py pred disjoint --g1"..."--g2"..."# Do geometries overlap?uv run python scripts/shapely_compute.py pred overlaps --g1"..."--g2"..."# Are geometries equal?uv run python scripts/shapely_compute.py pred equals --g1"..."--g2"..."# Does g1 cover g2?uv run python scripts/shapely_compute.py pred covers --g1"..."--g2"..."# Is g1 covered by g2?uv run python scripts/shapely_compute.py pred covered_by --g1"..."--g2"..."
measure
Geometric measurements.
# Area (polygons)uv run python scripts/shapely_compute.py measure area --geom"POLYGON((00,10,11,01,00))"# Length (lines, polygon perimeter)uv run python scripts/shapely_compute.py measure length --geom"LINESTRING(0 0,3 4)"# Centroiduv run python scripts/shapely_compute.py measure centroid --geom"POLYGON((00,20,22,02,00))"# Bounds (minx, miny, maxx, maxy)uv run python scripts/shapely_compute.py measure bounds --geom"POLYGON(...)"# Exterior ring (polygon only)uv run python scripts/shapely_compute.py measure exterior_ring --geom"POLYGON(...)"# All measurements at onceuv run python scripts/shapely_compute.py measure all --geom"POLYGON((00,20,22,02,00))"
›Access to product documentation and roadmap tools (Jira, Notion, etc.)
›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
1Install product management skill
2Start with user story generation for known feature
3Progress to competitive analysis: research 2-3 competitors
4Use for roadmap prioritization: apply RICE/ICE scoring
5Draft stakeholder communications and refine based on feedback
6Build template library for recurring PM tasks
7Share effective prompts with product team
Common Pitfalls
⚠Not validating competitive research—verify facts before sharing
⚠Accepting user stories without involving engineering team
⚠Over-relying on frameworks without qualitative judgment
⚠Not customizing outputs to company culture and communication style
⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
+Validate research and competitive analysis with real data
+Collaborate with engineering when generating technical requirements
+Customize frameworks and templates to your company context
+Use skill for first drafts, refine with stakeholder input
+Document successful prompt patterns for PM tasks
+Combine AI efficiency with human judgment and intuition
✗ Don't
−Don't publish competitive analysis without fact-checking
−Don't finalize user stories without engineering review
−Don't make prioritization decisions solely on AI scoring
−Don't skip customer validation of generated requirements
−Don't ignore company-specific context and culture
💡 Pro Tips
★Provide context: company goals, constraints, customer feedback
★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
1Basic: user stories, feature specs, status updates
