Best use case
limits-colimits is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Problem-solving strategies for limits colimits in category theory
Teams using limits-colimits should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/limits-colimits/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How limits-colimits Compares
| Feature / Agent | limits-colimits | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Problem-solving strategies for limits colimits in category theory
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Limits Colimits
## When to Use
Use this skill when working on limits-colimits problems in category theory.
## Decision Tree
1. **Identify Limit Type**
- Product: limit of discrete diagram
- Equalizer: limit of parallel pair f, g: A -> B
- Pullback: limit of A -> C <- B
- Terminal object: limit of empty diagram
- Lean 4: `CategoryTheory.Limits` namespace
2. **Verify Universal Property**
- Cone from L with projections pi_i: L -> D_i
- For any cone from X, unique morphism u: X -> L
- Triangles commute: pi_i . u = cone_i
- Lean 4: `IsLimit.lift` gives the unique morphism
3. **Colimit (Dual)**
- Coproduct: colimit of discrete diagram
- Coequalizer: colimit of parallel pair
- Pushout: colimit of A <- C -> B
- Initial object: colimit of empty diagram
4. **Compute Limits Concretely**
- In Set: product = Cartesian product
- Equalizer = {x | f(x) = g(x)}
- Pullback = {(a,b) | f(a) = g(b)}
- `sympy_compute.py solve "f(a) == g(b)"`
5. **Preservation**
- Right adjoint preserves limits
- Left adjoint preserves colimits
- Representable functors preserve limits
- Lean 4: `Adjunction.rightAdjointPreservesLimits`
- See: `.claude/skills/lean4-limits/SKILL.md` for exact syntax
## Tool Commands
### Lean4_Limit
```bash
# Lean 4: import CategoryTheory.Limits.Shapes.Products
```
### Lean4_Universal
```bash
# Lean 4: IsLimit.lift cone -- unique morphism from universal property
```
### Sympy_Pullback
```bash
uv run python -m runtime.harness scripts/sympy_compute.py solve "f(a) == g(b)"
```
### Lean4_Build
```bash
lake build # Compiler-in-the-loop verification
```
## Cognitive Tools Reference
See `.claude/skills/math-mode/SKILL.md` for full tool documentation.Related Skills
limits
Problem-solving strategies for limits in real analysis
workflow-router
Goal-based workflow orchestration - routes tasks to specialist agents based on user goals
wiring
Wiring Verification
websocket-patterns
Connection management, room patterns, reconnection strategies, message buffering, and binary protocol design.
visual-verdict
Screenshot comparison QA for frontend development. Takes a screenshot of the current implementation, scores it across multiple visual dimensions, and returns a structured PASS/REVISE/FAIL verdict with concrete fixes. Use when implementing UI from a design reference or verifying visual correctness.
verification-loop
Comprehensive verification system covering build, types, lint, tests, security, and diff review before a PR.
vector-db-patterns
Embedding strategies, ANN algorithms, hybrid search, RAG chunking strategies, and reranking for semantic search and retrieval.
variant-analysis
Find similar vulnerabilities across a codebase after discovering one instance. Uses pattern matching, AST search, Semgrep/CodeQL queries, and manual tracing to propagate findings. Adapted from Trail of Bits. Use after finding a bug to check if the same pattern exists elsewhere.
validate-agent
Validation agent that validates plan tech choices against current best practices
tracing-patterns
OpenTelemetry setup, span context propagation, sampling strategies, Jaeger queries
tour
Friendly onboarding tour of Claude Code capabilities for users asking what it can do.
tldr-stats
Show full session token usage, costs, TLDR savings, and hook activity