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PathFinding.js — Fleet Demo Template

Pre-configured repo for running skills fleet demos against a real JavaScript codebase.

Slides: https://def1-20-124-190-109.ngrok-free.app/ (temporary ngrok link)

Provenance

  • Upstream: qiao/PathFinding.js — comprehensive pathfinding library for grid-based games
  • Fork point: commit 2904a9a (latest upstream as of 2026-04-15)
  • Patch applied: should.js upgraded from 4.3.x to ^13.2.3 for Node 25 compatibility

The codebase is untouched upstream code — no fleet-generated modifications included.

Prerequisites

1. Node.js (v18+)

node --version
# or install via nvm
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.40.3/install.sh | bash
nvm install 22

2. tmux

Fleets run workers in tmux sessions. Required.

  • Ubuntu/Debian: sudo apt install -y tmux
  • Fedora/RHEL: sudo dnf install -y tmux
  • macOS: brew install tmux

Verify: tmux -V

3. Claude Code

npm install -g @anthropic-ai/claude-code

Verify: claude --version

4. Install fleet skills

From inside this repo:

npx skills add quickcall-dev/skills

When prompted:

  • Skills: select all (or pick specific fleets you want)
  • Agents: select Claude Code
  • Scope: Project
  • Method: Symlink

Verify skills loaded — start a new Claude Code session and check /dag-fleet appears in the skill list.

Setup

git clone <this-repo-url> && cd <repo-name>
npm install

Start dev environment

./dev.sh

Launches a tmux session (pathfinding-dev) with:

  • server window: visual demo on http://localhost:8080
  • tests window: runs the test suite

Keep this running. Fleet workers need the dev server for visual testing.

Verify

Tests window should show all tests passing.

Fleet Definitions

Four ready-to-launch fleets in docs/experiments/002-live-demo/fleets/:

Fleet Type Workers What it does
fleet-01-test-blitz dag 9 Coverage audit → distribute → parallel test writing → validation
fleet-02-scenario-builder iterative 6 Build interactive scenario builder with reviewer loop
fleet-03-algorithm-race dag 3 Benchmark A* vs Dijkstra on identical maps, compile leaderboard
fleet-04-dijkstra-optimize autoresearch 1 Autonomous loop: optimize Dijkstra to close gap with A*

Launch a fleet

Open Claude Code in a separate terminal (not inside the dev tmux):

cd <repo-root>
claude

Then pick a fleet:

# Easiest — 3 workers, fast
/dag-fleet launch docs/experiments/002-live-demo/fleets/fleet-03-algorithm-race

# Medium — 9 workers, DAG dependencies
/dag-fleet launch docs/experiments/002-live-demo/fleets/fleet-01-test-blitz

# Advanced — iterative with reviewer loop
/iterative-fleet launch docs/experiments/002-live-demo/fleets/fleet-02-scenario-builder

# Autonomous — runs until stopped or budget exhausted
/autoresearch-fleet launch docs/experiments/002-live-demo/fleets/fleet-04-dijkstra-optimize

Monitor

/<fleet-type> status    # worker states, durations
/<fleet-type> view      # live tmux pane view
/<fleet-type> report    # summary report

Fleet structure diagrams

graph TD
    subgraph "fleet-01: test-blitz (dag)"
        A1[coverage-auditor] --> O1[orchestrator]
        A2[visual-auditor] --> O1
        O1 --> T1[test-writer-1]
        O1 --> T2[test-writer-2]
        O1 --> T3[test-writer-3]
        O1 --> T4[test-writer-4]
        O1 --> S1[scenario-builder]
        T1 --> V1[validator]
        T2 --> V1
        T3 --> V1
        T4 --> V1
        S1 --> V1
    end
Loading
graph TD
    subgraph "fleet-02: scenario-builder (iterative)"
        C[canvas-worker] --> R[reviewer]
        CT[controls-worker] --> R
        SC[scorer-worker] --> R
        P[persistence-worker] --> R
        I[integration-worker] --> R
        R -->|iterate| C
        R -->|lgtm| DONE[done]
    end
Loading
graph TD
    subgraph "fleet-03: algorithm-race (dag)"
        RA[racer-astar] --> L[leaderboard]
        RD[racer-dijkstra] --> L
    end
Loading
graph TD
    subgraph "fleet-04: dijkstra-optimize (autoresearch)"
        LOOP[edit → eval → keep/discard → repeat]
        LOOP -->|plateau| WEB[web search]
        WEB --> LOOP
    end
Loading

Recommended order for first-time users

  1. fleet-03 (algorithm-race) — simplest, 3 workers, finishes fast
  2. fleet-01 (test-blitz) — shows DAG dependencies in action
  3. fleet-02 (scenario-builder) — shows iterative reviewer loop
  4. fleet-04 (dijkstra-optimize) — autonomous research, runs indefinitely

Documentation skill (/doc)

This repo comes with a pre-initialized docs/ structure managed by the /doc skill. As you run fleets, use /doc to track plans, findings, checkpoints, and learnings — all organized under numbered experiments.

docs/experiments/002-live-demo/
├── .meta.json           # auto-managed metadata
├── fleets/              # fleet definitions (ready to launch)
├── plans/               # numbered plans (01, 02, ...)
├── findings/            # discoveries during work
├── checkpoints/         # progress snapshots
├── research/            # experiment-scoped research
└── review/              # structured reviews

Quick reference

# Inside Claude Code:
/doc plan 2 "test-strategy"
/doc ckpt 2 "tests-passing"
/doc finding 2 "perf-regression"
/doc learn 2 "testing" "mock-pitfalls"
/doc status 2
/doc list
/doc resume 2

Stateless and parallel-safe — multiple fleet workers can write to the same experiment without conflicts.

Repo structure

├── src/                 # pathfinding library source
│   ├── core/            # Grid, Node, Heap, Util
│   └── finders/         # A*, Dijkstra, BFS, JumpPoint, etc.
├── test/                # mocha test suite
├── visual/              # browser demo app
├── dev.sh               # tmux dev environment launcher
└── docs/
    └── experiments/
        └── 002-live-demo/
            └── fleets/
                ├── fleet-01-test-blitz/
                ├── fleet-02-scenario-builder/
                ├── fleet-03-algorithm-race/
                └── fleet-04-dijkstra-optimize/

Dev commands

npm install
npx mocha --require should test/**/*.js    # run tests
npx http-server visual -p 8080 -c-1         # start visual demo

Troubleshooting

Problem Fix
skills not found Restart Claude Code after installing skills
tmux: command not found Install tmux (see prerequisites)
port 8080 in use fuser -k 8080/tcp (Linux) or lsof -ti:8080 | xargs kill (macOS)
Workers stuck on "waiting" Check DAG — upstream workers must complete first
Tests fail on install Make sure you're on Node 18+ (node --version)
npx skills hangs Check internet connection, skills installs from GitHub

Cost estimates

Based on prior runs with Claude models:

Fleet Approximate cost
fleet-01 (test-blitz) ~$6
fleet-02 (scenario-builder) ~$2
fleet-03 (algorithm-race) ~$3
fleet-04 (dijkstra-optimize) ~$5-50 (depends on iterations)

Costs vary by model choice and worker budget caps. See fleet.json for per-worker max_budget_usd settings.

Original library

PathFinding.js provides 10 pathfinding algorithms for 2D grids: A*, Dijkstra, BFS, BestFirst, JumpPoint, IDA*, and their bi-directional variants. See the online demo.

MIT License — Xueqiao Xu

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