Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for AI builders, research teams, and developers who want a self-hostable, long-horizon agent harness that can chain research, coding, and creative work in a single sandboxed run, instead of stitching together a hand-rolled multi-agent loop on top of an LLM API.
Where this stands now
bytedance/deer-flow ranks #77 of 3231 tracked Radar items by composite score (8.6 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 2026-06-21 (111 days in the current window). Signal extremes versus the section: momentum at the 92th percentile; novelty at the 85th percentile.
Who should use it
Who should skip it
Skip bytedance/deer-flow unless the captured evidence suggests it solves a problem you are actively working on.
About this signal
bytedance/deer-flow is tracked by RepoRadar as an agent project in the Radar section. First seen 2026-06-21; the source record was last checked on 2026-06-21. The current verdict is 'try now' with a Gold tier and moderate setup difficulty. bytedance/deer-flow leads on workflow potential (10.0) and momentum (9.0); its lowest signal is setup ease (6.4), so factor that in before investing setup time. 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 bytedance/deer-flow record combines a 8.6/10 composite score with separate popularity (8.7), risk (low), and setup (moderate) signals. See the scoring methodology for the current weights and evidence definitions.
Questions worth asking before you adopt this
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 runs sandboxed code on your behalf and is intended to back long-horizon agent workflows, so scope the sandbox permissions, audit what gets persisted in agent memory, and confirm sensitive intermediate files are wiped between runs before promotion.