---
name: yogsoth-ai-hypothesis-formulation
description: "Campaign: transform insights and gaps into structured testable hypotheses"
license: "Apache-2.0"
metadata:
  decimalai-skill-id: "4fd58732-7b91-42c8-817e-c820ad370d58"
  decimalai-version-id: "cb63688e-c940-4e95-b585-9568f3677473"
  decimalai-version: "1"
  decimalai-body-sha256: "05e23b2b0604a26742c255328c2a8c1e1a4dec8d7a2c42fe17a9bca91c5cc5a4"
  decimalai-name: "yogsoth-ai/hypothesis-formulation"
  decimalai-format: "1"
  decimalai-invocation: "model"
  decimalai-category: "research"
  decimalai-source: "https://app.decimal.ai/s/yogsoth-ai-hypothesis-formulation@1/SKILL.md"
---
# Hypothesis Formulation

Transform insights and gaps into structured testable hypotheses — answering "how do we turn an insight into a testable hypothesis?"

## HARD-GATE

<HARD-GATE>
Preconditions (all must hold before starting):
1. At least 1 clear research gap or insight has been identified
2. The gap/insight has sufficient context (domain, existing theory, observed phenomenon)
3. The research intent is clear (knowing what is to be explained or predicted)

Not met → stop, recommend completing gap-prioritization or upstream work first.
</HARD-GATE>

## Campaign Goal

Transform a vague "there's a gap here" or "this phenomenon is interesting" into a precise, falsifiable hypothesis with boundary conditions. The output is not a "solution" but a "testable proposition."

## Strategy Selection

| Strategy | When to Use | Reasoning direction |
|----------|---------|---------|
| deductive-hypothesis-generation | The domain has mature theory, and the gap is a deviation between theoretical prediction and reality | Theory → prediction |
| inductive-hypothesis-generation | The domain lacks theory but has abundant empirical observations or data patterns | Data → regularity |
| abductive-hypothesis-generation | An anomalous phenomenon that existing theory cannot explain has been observed | Anomaly → best explanation |
| competing-hypothesis-construction | Need to maintain openness and avoid confirmation bias | Multiple explanations in parallel |
| hypothesis-operationalization | A directional hypothesis exists and needs to be formalized into a testable form | Vague → precise |

CC selects autonomously based on input characteristics (whether there is theoretical support, whether there is anomalous data, hypothesis maturity). Can be combined serially.

## Budget Gate

| Tier | Hypothesis yield | Theory/mechanism | Falsifiability | Competing hypotheses |
|------|---------|----------|---------|---------|
| S | ≥2 structured hypotheses | ≥2 relevant theories | 1 falsification scenario per hypothesis | Optional |
| M | ≥3 structured hypotheses | ≥3 theories + ≥5 mechanisms | ≥1 scenario + boundary conditions per hypothesis | ≥2 competing hypotheses |
| L | ≥5 structured hypotheses | ≥5 theories + ≥8 mechanisms | Complete falsifiability audit | ≥3 competing hypotheses + discriminating predictions |

## Hypothesis Structure (standard output format)

Each hypothesis must contain:
- **Statement**: If X then Y (condition-result form)
- **Variables**: independent, dependent, control, and moderator variables
- **Mechanism**: why X causes Y (causal chain)
- **Boundary conditions**: the preconditions under which the hypothesis holds
- **Falsification**: what observation would refute this hypothesis
- **Measurability**: how to measure it (operational definitions)

## Context Management

- Invoke context-init at campaign start
- Invoke context-checkpoint after each strategy completes (hard constraint)
- All outputs accumulate in a single campaign-scoped context file

## Minimum Yield

Each campaign run must produce:
1. ≥2 complete structured hypotheses (including all 6 components)
2. A falsifiability argument for each hypothesis
3. Relationship notes between hypotheses (complementary/competing/independent)
4. A recommended next direction (which hypothesis is most worth further developing into a research question)

<!-- BEGIN available-tables (generated) -->

## Available Strategies

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

| Strategy | When to use |
| --- | --- |
| abductive-hypothesis-generation | Strategy: Inference to the best explanation in the face of anomalies |
| competing-hypothesis-construction | Strategy: Construct multiple competing hypotheses for the same phenomenon |
| deductive-hypothesis-generation | Strategy: deduce hypotheses from existing theory |
| hypothesis-operationalization | Strategy: refine a working hypothesis into a precise, testable form |
| inductive-hypothesis-generation | Strategy: induce and distill hypotheses from data/observations |

## Available SOPs

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

| SOP | When to use |
| --- | --- |
| context-checkpoint | Append research process and results to the current Phase's context file. Covers both process and results with genuine substance. Use this skill at plan-designated checkpoint points — typically after each strategy completes or at key decision nodes within a research Phase. |
| context-init | Create a new context file for a research Phase. Called once at Phase start to initialize the file that subsequent context-checkpoint calls will append to. Use this skill whenever a new research Phase begins and a fresh context file is needed. |
| hypothesis-formation-quality-gate-check | Shared SOP: General quality-gate check (format completeness, logical consistency) |
| hypothesis-formation-saturation-detection | Shared SOP: judge whether the current activity has reached information saturation |
| hypothesis-synthesis | SOP: synthesize all intermediate products into a final structured hypothesis set |

## Available Campaigns

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

| Campaign | When to use |
| --- | --- |
| research-question | Campaign: Refine hypotheses into precise, framed research questions |

<!-- END available-tables (generated) -->
