Apply Bhaskar's critical realism to analyze phenomena through three ontological domains (real, actual, empirical), identify generative causal mechanisms via retroduction, and examine structure-agency interplay. Use this skill when the user needs to go beyond surface correlations to underlying causes, design research that distinguishes mechanisms from events from experiences, or when they ask 'what causes this beyond the observed pattern', 'what structures enable or constrain this behavior', or 'how do I move from correlation to causal explanation'.
npx skills add https://github.com/asgard-ai-platform/skills --skill grad-critical-realism
Critical realism posits a stratified ontology: the real (structures and mechanisms that exist whether or not they are activated), the actual (events that occur when mechanisms are activated), and the empirical (events that are observed or experienced). Research must move beyond empirical regularities to identify the generative mechanisms that produce observed phenomena.
IRON LAW: Observable events (empirical) are a SUBSET of what happens
(actual), which is a SUBSET of what exists (real) — research must go
beyond correlations to identify underlying generative mechanisms.
Key assumptions:
Document observable patterns, regularities, and experiences — what do we see happening?
Map the events that occurred whether or not they were observed, including contextual conditions, co-occurring events, and counterfactual absences.
Use retroductive reasoning: "What must be true for this phenomenon to be possible?" Propose candidate generative mechanisms — structures, powers, and tendencies that could produce the observed events.
Analyze how context enables or constrains mechanism activation. Explain why the same mechanism produces different outcomes in different settings (context + mechanism = outcome).
## Critical Realist Analysis: [Context]
### Empirical Domain (Experienced)
- Observed patterns: [what we see in the data]
- Measurement instruments: [how we accessed these observations]
- Known limitations: [what we cannot observe directly]
### Actual Domain (Events)
- Events occurred: [including unobserved events inferred from evidence]
- Contextual conditions: [enabling/constraining factors]
- Counterfactuals: [what did NOT happen and why it matters]
### Real Domain (Mechanisms)
| Mechanism | Structure/Power | Tendency | Evidence |
|-----------|----------------|----------|----------|
| [name] | [underlying structure] | [what it tends to produce] | [how we infer it] |
### Context-Mechanism-Outcome Configuration
- Context: [specific conditions]
- Mechanism activated: [which mechanism and why]
- Outcome: [what was produced]
### Implications
1. [What this tells us about underlying reality]
2. [Practical interventions targeting mechanisms, not symptoms]
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Take asgard-ai-platform/grad-critical-realism from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.