GitHub Reviews

1. Reinhard

   · Boss at CLOUD Meister · over 5 years ago
   perfect 4 open Source

Kimp Reviews

1. June Xing

   · Marketing Director at Pro Marketing · about 4 years ago
   Great service, very happy!

   Kimp is great. Their entire process is very organized. Really love the experience from on-boarding to handling the tasks. Quality designs, fast turnaround. Highly recommended!

   🏁 Competitors: Design Pickle, Penji, ManyPixels, Graphics Zoo, Flocksy

   👍 Pros:    Very organized structure
2. Cathy Lee

   · Founder/CEO at Phenom Marketing · about 4 years ago
   Amazing service!!

   I really wish that I knew about this kind of service long ago. I was referred to Kimp by a friend so decided to give them a try. I have blown away by how much I was able to get done and free up my time. Great designs from the getgo. My project manager is very responsive and friendly to work with. Overall, I really enjoy working with the Kimp team and I can see this being a very long working relationship.

   👍 Pros:    Can outsource all my design requirement so i can focus on scaling my business|Great quality designs from the getgo, they nail most of the designs in the first attempt.|Very responsive and friendly project manager|Followups from management team|Very affordable|Fast turnarounds

   👎 Cons:    Nothing i can think of at the moment, they are really like part of my team

GitHub mentions (2476)

• Como criei um agente de IA para selecionar testes automaticamente em PRs (Parte 1)

  """Clones a single branch of a GitHub repository into a temporary directory for local scanning.""" Import logging Import shutil Import subprocess Import tempfile Logger = logging.getLogger(__name__) Class RepoFetchError(RuntimeError): """Raised when the target repository/branch cannot be cloned.""" Class RepoFetcher: """Shallow-clones a single branch of a repository so its tests can be scanned... - Source: dev.to / 1 day ago

• I Treat My Video Descriptions Like a Build Artifact Now. Here's the Pipeline.

  # video-meta.yml Topic: > Walking through how we cut cold-start time on a Lambda-backed GraphQL API from 2.4s to under 400ms, including the two things that didn't work. Target_keyword: lambda cold start optimization Audience: backend devs who already ship serverless, not beginners Model_channels: - the three channels currently ranking for this keyword Links: repo: https://github.com/... slides:... - Source: dev.to / 2 days ago

• I audited a 5.5 GB AI training dataset by downloading 0.8% of it

  Import struct, json, urllib.request REL = "https://github.com/{owner}/{repo}/releases/download/{tag}/" PART = ["...part1.zip.001", "...part2.zip.002", "...part3.zip.003"] SIZE = [1992294400, 1992294400, 1893639808] # from the releases API Def grab(part, start, end, out): # HTTP range fetch req = urllib.request.Request(REL + PART[part], Headers={"Range":... - Source: dev.to / 7 days ago

• Superlogical – Mitchell Hashimoto

  Is published at https://github.com/.keys so an SSH server to which you connect could do a reverse lookup. This is the reason why my ~/.ssh/config has those 2 lines at the end:

          Host *.

  - Source: Hacker News / 14 days ago

• Your Agent's Confidence Score Is Not a Probability

  All of this assumes you can actually inspect what the agent did — the real inputs after resolution, the real tool outputs, the real intermediate steps. That is the other half of the workflow. AgentLens captures the trace: every model and tool step, resolved inputs, raw outputs. agent-eval scores and gates the output; AgentLens gives you the unforgeable, agent-didn't-author trace data for Tier 1+2 to score against... - Source: dev.to / 15 days ago

Kimp mentions (0)