Best use case
active-interleave is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Active Interleave Skill
Teams using active-interleave 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/active-interleave/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How active-interleave Compares
| Feature / Agent | active-interleave | 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?
Active Interleave Skill
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
# Active Interleave Skill
Interleaves context from recently active Claude/Amp threads into current activity via random walk.
## bmorphism Contributions
> *"all is bidirectional"*
> — [@bmorphism](https://gist.github.com/bmorphism/ead83aec97dab7f581d49ddcb34a46d4), Play/Coplay gist
**Active Inference Pattern**: The interleave implements [Active Inference in String Diagrams](https://arxiv.org/abs/2308.00861) epistemic foraging — actively sampling from recent contexts to minimize uncertainty about the current task. Each random walk step is an epistemic action that gathers information.
**Play/Coplay Duality**: The interleave embodies bmorphism's bidirectional principle:
- **Play** (action): Query recent threads, walk the awareness graph
- **Coplay** (perception): Integrate fragments, update current context
**GF(3) Balanced Exploration**: The triadic structure (MINUS/ERGODIC/PLUS) ensures balanced exploration — validation filters (MINUS), random walk explores (ERGODIC), and colored emission generates (PLUS). Conservation Σ = 0 maintains coherence.
## Activation
Load when context from recent work would help current task.
## Usage
```bash
# Interleave from last 24 hours
bb ~/.claude/skills/active-interleave/active.bb
# Interleave from last N hours
bb ~/.claude/skills/active-interleave/active.bb --hours 6
# Query-focused interleave
bb ~/.claude/skills/active-interleave/active.bb --query "aptos blockchain"
# JSON output
bb ~/.claude/skills/active-interleave/active.bb --json
```
## Behavior
1. **MINUS (-1)**: Validate recency window, filter to active threads only
2. **ERGODIC (0)**: Random walk through recent sessions following awareness edges
3. **PLUS (+1)**: Emit interleaved fragments with GF(3) coloring
## GF(3) Conservation
Each interleave batch maintains Σ trits ≡ 0 (mod 3).
## Integration
Call from current thread to surface relevant recent context:
```clojure
;; In any bb script
(require '[babashka.process :refer [shell]])
(def context (-> (shell {:out :string} "bb" (str (System/getProperty "user.home")
"/.claude/skills/active-interleave/active.bb") "--json")
:out))
```
## Schema
Reads from `~/worldnet/cognition.duckdb`:
- `messages` - Content with timestamps
- `sessions` - Session metadata
- `awareness_edges` - Play/coplay graph
- `temporal_index` - Time-ordered index
## Scientific Skill Interleaving
This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:
### Graph Theory
- **networkx** [○] via bicomodule
- Universal graph hub
### Bibliography References
- `general`: 734 citations in bib.duckdb
## SDF Interleaving
This skill connects to **Software Design for Flexibility** (Hanson & Sussman, 2021):
### Primary Chapter: 6. Layering
**Concepts**: layered data, metadata, provenance, units
### GF(3) Balanced Triad
```
active-interleave (−) + SDF.Ch6 (+) + [balancer] (○) = 0
```
**Skill Trit**: -1 (MINUS - verification)
### Secondary Chapters
- Ch4: Pattern Matching
- Ch7: Propagators
- Ch10: Adventure Game Example
### Connection Pattern
Layering adds metadata. This skill tracks provenance or annotations.
## Cat# Integration
This skill maps to **Cat# = Comod(P)** as a bicomodule in the equipment structure:
```
Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826
```
### GF(3) Naturality
The skill participates in triads satisfying:
```
(-1) + (0) + (+1) ≡ 0 (mod 3)
```
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