Unverified50% confidenceFactExact time
Evaluation in dsh-superagent is divided into two steps, admission and assessment: admission first performs rule filtering, and assessment then performs intent understanding and impact evaluation, outputting one of four conclusions: borrow, stop, ignore or incomplete.
1
Sources
50%
Confidence
Long-term
Relevance
11/4/2026
First Seen
Sources
DeepSeek's Open-Source Agent Teardown: 11,700 Stars but Only One Commit
bilibili翻车老头11/3/2026
Related Entities
Related Claims
UnverifiedAt each sampling step, DSC evaluates, based on the current state, how much intervention is needed, in which space the intervention should be applied, and when to stop the intervention.68% similarUnverifieddsh-superagent is suitable for reading designs and doing experiments, and is not recommended for directly hosting production repositories; it is advisable to start in observation mode and let the agent first prove that it will not cause trouble before discussing automation.67% similarUnverifiedA tiered evaluation strategy uses small models or rules for initial filtering, deploys expensive large-model judges only at critical stages, uses caching to avoid redundant evaluations, and uses refined evaluation sets to reduce token consumption.66% similarUnverifiedThe evaluation tool independently scores two dimensions: notice (whether the warning is mentioned in the conversation trajectory) and action (whether the final tool call violates forbidden_actions).66% similarUnverifiedThe two-stage review model splits review into two phases: an editorial filter (deciding whether a change should be made) and a governance filter (deciding whether the rewrite is permitted).65% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1133482API
curl https://kongchang.com/api/v1/knowledge/claims/1133482MCP
get_claim(id=1133482)