fastworkflow-research-methodology

fastworkflow-research-methodology is an Engineering planning & specs skill for AI agents, published by radiantlogicinc in the fastworkflow repository on GitHub. Skillspace rates fastworkflow-research-methodology C (74/100) and it passed the safety scan; the rating is based on static analysis only.

Load when you are about to propose, run, review, accept, or retire a research idea or experiment in this repo — trigger phrases include "I have a hypothesis", "let's try adding X and see if the score improves", "the numbers went up so it works", "should we pin the simulator temperature", "write up this experiment", "is this result real", "kill this idea", or any request to design an E-card / pre-registration / adversarial review. Do NOT load for executing the tau2 campaign step-by-step (use tau2-reliability-campaign), for statistics recipes and pass^k math (use fastworkflow-proof-and-analysis-toolkit), for picking WHICH open problem to work on (use fastworkflow-research-frontier), or for ordinary bug fixing (use fastworkflow-debugging-playbook).

Grade

C

Quality

74 / 100

Safety

Passed

GitHub stars

49

Unproven: rated by static analysis only, not yet compared head-to-head.

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