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SKILL: The Scientist Agent (Universal Literate Note)

Overview

The Scientist Agent provides a formal, hypothesis-driven approach to debugging. Instead of "trial and error," it formulates symbolic theories about why a failure occurred, designs experiments (test cases), and updates the system's Institutional Memory upon discovery.

Phase A: Demand (PRD)

1. Purpose

Eliminate speculative debugging through rigorous scientific methodology.

2. User Needs

  • Hypothesis Formulation: Neural generation of potential failure causes.
  • Experimental Design: Autonomous creation of minimal failing test cases.
  • Theory Verification: Execution of tests via the TDD Runner.
  • Knowledge Update: Permanent update to `RCA.org` to prevent regression.

Phase D: Build (Implementation)

Scientific Loop

(defun scientist-formulate-hypothesis (failure-log)
  "Analyzes an error and proposes a 'Theory of Failure'."
  (org-agent:ask-neuro 
   (format nil "Explain why this failure occurred and propose a specific experiment to prove it: ~a" failure-log)
   :system-prompt "You are a PSF Senior Debugging Scientist. Use formal logic and the scientific method."))

(defun scientist-run-experiment (hypothesis)
  "Designs a minimal test case based on a hypothesis."
  ;; Delegates to TDD Runner to create and run the experiment.
  (org-agent:spawn-task (format nil "Create a minimal failing test for: ~a" hypothesis)))

Registration

(defskill :skill-scientist
  :priority 90
  :trigger (lambda (context) (search "ERROR" (getf (getf context :payload) :text)))
  :neuro #'scientist-formulate-hypothesis
  :symbolic (lambda (action context) action))