falsifiability-audit

Research

Tactic: hypothesis quality assurance — check falsifiability, repair failing hypotheses, complete operationalization and boundary-condition specification

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Falsifiability Audit

Hypothesis quality assurance — check each hypothesis in the set for falsifiability, repair failing hypotheses, complete operational definitions, and specify boundary conditions, ensuring every hypothesis can be tested by experiment or observation.

Orchestration Intent

The final gate of hypothesis formation. No matter how good the theoretical foundation, if the resulting hypotheses cannot be falsified, they are not scientific hypotheses. This tactic's job is "quality control," not "generation": the input is a set of existing hypothesis candidates, and the output is the proof document that each hypothesis has passed QC.

The three SOPs form a pipeline: falsifiability-check identifies problems → operationalization converts variables into measurable form → boundary-condition-specification delimits the range within which the hypothesis holds. No step skipping is allowed, and advancing directly when falsifiability-check fails is not allowed.

Available SOPs

SOP	Responsibility	When to call
falsifiability-check	Run a falsifiability check on each hypothesis, identify unfalsifiable hypotheses, and propose fixes	Required in all modes, executed first; if any hypothesis fails, iterate the fix and re-check
operationalization	Provide operational definitions for each hypothesis's variables — how to measure, with what instrument, under what conditions	Required in all modes, executed after falsifiability-check passes
boundary-condition-specification	Specify the preconditions, scope of applicability, and known limitations under which the hypothesis holds	Required in all modes, executed last

Orchestration Pattern

Simplified (S tier, ≤3 hypotheses)

Sequential execution: falsifiability-check → operationalization → boundary-condition-specification
If any hypothesis fails falsifiability-check, CC immediately repairs and re-checks it (at most 2 iterations)
Suited to: few hypotheses, expected to be of higher quality

Standard (M tier, 4-6 hypotheses)

falsifiability-check runs in batch over all hypotheses, compiling a failure list; CC repairs in batch; re-check the repaired hypotheses
operationalization and boundary-condition-specification run in series
Suited to: medium-sized hypothesis sets needing systematic QC

Deep (L tier, ≥7 hypotheses)

All 3 SOPs run; falsifiability-check additionally outputs the "strongest counterexample scenario" for each hypothesis; operationalization additionally requires ≥2 measurement methods per variable (primary + alternative); boundary-condition-specification additionally requires listing known exceptions
Suited to: large hypothesis sets needing production-grade quality assurance

Minimum Yield

Every input hypothesis has passed falsifiability-check (or has been repaired until it passes)
Every variable of every hypothesis has an operational definition (including measurement instrument/method)
Every hypothesis has explicit boundary conditions (the preconditions under which it holds + the situations where it does not apply)
A complete QC record: which hypotheses passed on the first try, which passed after repair, and what the repairs were

Yield Report

After execution, report to the calling strategy:

Number of input hypotheses / first-pass count / post-repair pass count / final fail count
The most common type of falsifiability problem (to help the upstream strategy improve hypothesis generation)
Operationalization difficulty: which variables are hard to measure (requiring special instruments or datasets)
Boundary-condition coverage: which hypotheses have a narrow scope of applicability (high risk, easily overturned by counterexamples)

Available SOPs

Optional, no fixed order; the final leaf is always a sop.

SOP	When to use
boundary-condition-specification	SOP: Specify the boundary conditions under which a hypothesis holds
falsifiability-check	SOP: check whether a hypothesis meets the falsifiability criterion
operationalization	SOP: operationalize abstract concepts into measurable indicators and methods