Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for AI agent operators, customer-facing automation teams, and developer-tools builders who want a real-time conversational task manager with explicit human-in-the-loop checkpoints for AI agents, so they can route work, gather human approval, and audit agent decisions through a single ACP-compatible surface instead of stitching together queue tools and chat prompts by hand.
Where this stands now
agentrq/agentrq ranks #499 of 3231 tracked Radar items by composite score (8.0 against a section median of 4.9). The section currently carries 2115 Bronze, 645 Gold, 471 Silver. RepoRadar has retained observations for this record since 2026-06-22 (110 days in the current window). Signal extremes versus the section: momentum at the 85th percentile; novelty at the 85th percentile.
Who should use it
Who should skip it
Avoid running agentrq/agentrq in production until you have reviewed its permissions, data-access scope, and failure modes in a sandbox.
About this signal
agentrq/agentrq is tracked by RepoRadar as a hosted app or demo in the Radar section. First seen 2026-06-22; the source record was last checked on 2026-06-22. The current verdict is 'try now' with a Gold tier and moderate setup difficulty. The standout signals for agentrq/agentrq are workflow potential (9.5) and open-source/build quality (8.4), while setup ease (6.4) trails — that balance shapes where it fits best. This page summarizes the public evidence on the linked source page and states where additional review is still needed.
How this item is evaluated
The agentrq/agentrq record combines a 8.0/10 composite score with separate popularity (8.2), risk (medium), and setup (moderate) signals. See the scoring methodology for the current weights and evidence definitions.
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
It is a conversational task manager with explicit human-in-the-loop checkpoints for AI agents, so review what payloads, prompts, and operator decisions are persisted in the audit log, scope who can approve or redirect agent decisions, and confirm retention matches your compliance requirements before connecting customer-facing agents.