Research pipelines as semantic execution units: each skill declares inputs/outputs, acceptance criteria, and guardrai...
Copy the install, test the workflow, then decide if it earns a permanent slot.
Still active enough to matter. Good candidate for a fast stack test instead of a long evaluation loop.
Copy the install, test the workflow, then decide if it earns a permanent slot.
Not hard to test, not trivial to unwind. Worth trying if it closes a sharp gap.
GitHub health 28/100. no security policy. 0 open issues make this testable, but not something to trust blind.
AI Agent
Multiple
Model
Claude
Fastest way to find out if research-units-pipeline-skills belongs in your setup.
Copy the install command, run a real test, and back it out cleanly if it slows you down.
# Visit: https://github.com/WILLOSCAR/research-units-pipeline-skillsRun this first. You will know quickly if the workflow earns a permanent slot.
# No automated removal — visit https://github.com/WILLOSCAR/research-units-pipeline-skillsNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
~/ └─ .claude/ ├─ commands/ ├─ agents/ │ └─ research-units-pipeline-skills/ ← installs here └─ settings.json
Research pipelines as semantic execution units: each skill declares inputs/outputs, acceptance criteria, and guardrails. Evidence-first methodology prevents hollow writing through structured intermediate artifacts.
Source: GitHub repository
Source check: July 18, 2026
Upstream commit: July 17, 2026
Repository state: Not marked archived
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