Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for AI engineers and researchers who want a real vocabulary for agent architecture decisions instead of a flat list of pattern names ('Reflection, ReAct, Multi-Agent, Tree of Thoughts, Reflexive Metacognitive...'). A flat list answers 'what patterns exist' but not 'where my problem sits, and which pattern lives at that coordinate' — and that is the gap the paper and the repo close. The 7×6
Who should use it
Who should skip it
Skip huangjia2019/agent-design-patterns if the source repository or demo is inactive, unmaintained, or no longer matches the description shown here.
About this signal
huangjia2019/agent-design-patterns is tracked by RepoRadar as a 28 agent design patterns (runnab in the AI Apps section. It was first seen on 2026-07-04 and last updated on 2026-07-04. The current verdict is 'worth watch' with a Silver tier and easy setup difficulty. huangjia2019/agent-design-patterns leads on setup ease (8.8) and open-source/build quality (8.4); its lowest signal is maturity (5.4), so factor that in before investing setup time. This page summarizes the evidence RepoRadar has captured from captured source metadata. The score, tier, risk label, and verdict on this page are never influenced by sponsorship, ads, or tips — they reflect only the usefulness, popularity, novelty, momentum, maturity, and evidence signals described in the RepoRadar methodology.
How this item is evaluated
RepoRadar assigned huangjia2019/agent-design-patterns a composite score of 7.4 out of 10, placing it in the Silver tier. This score combines weighted sub-signals: usefulness (35%), novelty (18%), momentum (14%), maturity (10%), open-source/build quality (7%), evidence quality (6%), workflow potential (6%), and setup ease (4%). Popularity is tracked separately at 1.0 and never affects the composite score or tier. The risk label of 'low' reflects inherent user-impacting hazards, not generic novelty. Items with no risk flag may still require normal code review before production use.
Putting this into practice? Read How to vet an AI agent or MCP server before you wire it in for the checklist behind this score.
Risk explanation
Risk label is still being reviewed from the captured evidence. Treat the item as unknown-risk until you review the linked source, permissions, setup path, and data access.