Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for teams benchmarking coding agents against real business-software constraints rather than toy code-gen tasks, especially when they care about auditability and recovery behavior as much as pass rates.
Who should use it
Who should skip it
Skip teaql/teaql-agent-kit if the source link, documentation, or setup requirements do not align with your current workflow or stack.
About this signal
teaql/teaql-agent-kit is tracked by RepoRadar as a coding agent eval in the Evals section. It was first seen on 2026-06-29 and last updated on 2026-06-29. The current verdict is 'worth watch' with a Silver tier and moderate setup difficulty. The standout signals for teaql/teaql-agent-kit are open-source/build quality (8.4) and workflow potential (8.2), while maturity (5.7) trails — that balance shapes where it fits best. 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 teaql/teaql-agent-kit a composite score of 7.8 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 'none' 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
The current tasks are TEAQL business-software-specific, so results should be treated as targeted evidence rather than a universal ranking of coding agents.