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ADHD — a skill for coding agents. Tree-of-thought with pruning, built on the Claude & Codex Agent SDK. Fans out parallel divergent thoughts under different cognitive frames, scores, prunes traps, deepens the survivors. The no-brainer skill for creative and interdisciplinary work.
This repository page has enough original analysis, source evidence, and comparison context to be treated as an indexable Git-Stars review.
100
review score
Problem solved
ADHD solves the problem of premature convergence in linear Chain-of-Thought reasoning, where the model anchors on its first output. Unlike standard Tree-of-Thought, it spawns isolated reasoning processes with zero shared context during divergence, then uses a separate critic pass to score, cluster, prune traps, and deepen survivors, enabling more creative and diverse solutions.
Deployment reality
The available setup signal starts with: npm install adhd-agent. Treat this as a starting point, then ask Codex or Claude to inspect the README, environment variables, runtime version, and deployment target before production use.
Commercial use
The recorded license is MIT. This is a useful commercial-use signal, but teams should still verify license text, dependencies, model/API terms, and trademark constraints.
Capability ceiling
Developers can build agents that generate a wide range of creative and non-obvious solutions for design decisions, fuzzy debugging, naming, API surface design, strategy, and any prompt requiring multiple approaches. Real-world use cases include generating diverse retry/timeout strategies, exploring alternative architectures, and surfacing novel ideas that a single-shot approach would miss. The ceiling is high for interdisciplinary and creative work where breadth and novelty are valued over quick, conventional answers.
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UditAkhourii/adhd is tracked as a TypeScript project in the AI Agent, LLM Tool, Developer Tool, UI Framework area. This evaluation combines public GitHub metadata, category signals, short source summaries, and Git-Stars editorial rules rather than copying project documentation.
Momentum check: the repository has 2.9k total stars, with +0 today, +791 this week, and +0 this month. These growth windows help distinguish durable adoption from short-lived visibility spikes.
Maintenance check: current activity is Moderate; the latest push was 31 days ago, and the open issue queue is 14, about 0.49% of total stars. Treat this as an adoption signal, not a substitute for engineering due diligence.
Adoption check: 219 forks and 2.9k watchers suggest how often the project is reused or followed. License signal: MIT. Always verify license compatibility before commercial or internal use.
Practical fit: this project is most relevant when you need AI prototypes, LLM workflows, and agent-style applications. Be cautious when you need a legal review, security audit, or production SLA.
Source check: Git-Stars currently has 2 explicit source reference(s) for this report and a recent growth signal of 791. Follow the original GitHub repository for final install, security, and release information.
Analysis
ReadyOriginal problem, capability, and verdict guidance are available.
Sources
ReadyRepository metadata and README/source references are attached.
License
ReadyMIT is recorded for review.
Maintenance
ReadyRecent activity is visible in repository metadata.
Alternatives
ReadyEnough nearby projects exist for comparison.
Momentum
2.9k Stars
Reuse
219 Forks
Attention
2.9k Watchers
Maintenance
moderate
License
MIT
Open issues
14
ADHD is an architectural fix for premature convergence in autoregressive reasoning, spawning isolated reasoning processes under deliberately distorted cognitive frames to generate diverse solutions for design decisions, debugging, and strategy tasks.
Key Features
- Spawns N isolated reasoning processes with zero shared context under distorted cognitive frames for divergent ideation - Runs a separate critic pass to score, cluster, prune traps, and deepen survivors - Generates 30+ ideas across clusters like economic-incentive, async-control-surface, and gamification, with non-obvious picks and trap detection
AI Agent
Agent frameworks, autonomous workflows, and tool-use systems
LLM Tool
Libraries and tools for LLM apps, RAG, prompts, and evals
Developer Tool
Tools that improve coding, testing, build, and local workflow
UI Framework
Frontend frameworks, design systems, and interface libraries
npm install adhd-agent63
Health Score
Moderate
Commit Activity
May 25, 2026
Created
Jul 23, 2026
Last push
+141
Today's growth
+307
7-day growth
+307
30-day growth
Forks
Open
Watchers
UditAkhourii
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✓
License
✓
Forked
~ Moderate
Maintained
Problem Solved
ADHD solves the problem of premature convergence in linear Chain-of-Thought reasoning, where the model anchors on its first output. Unlike standard Tree-of-Thought, it spawns isolated reasoning processes with zero shared context during divergence, then uses a separate critic pass to score, cluster, prune traps, and deepen survivors, enabling more creative and diverse solutions.
Capabilities
Developers can build agents that generate a wide range of creative and non-obvious solutions for design decisions, fuzzy debugging, naming, API surface design, strategy, and any prompt requiring multiple approaches. Real-world use cases include generating diverse retry/timeout strategies, exploring alternative architectures, and surfacing novel ideas that a single-shot approach would miss. The ceiling is high for interdisciplinary and creative work where breadth and novelty are valued over quick, conventional answers.
Bottom Line
ADHD is ideal for developers building coding agents that need creative, diverse, and non-obvious solutions, especially for open-ended problems. It should be avoided when speed and simplicity are paramount, as the parallel divergence adds overhead. The key trade-off is between breadth/novelty and efficiency/conventionality.