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/causal-modeling

Campaign for building causal models — identify variables, map mechanisms,

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de-anthropocentric-research-engine
393200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill causal-modeling --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/causal-modeling

Context preview

The summary Claude sees to decide when to auto-load this skill.

Campaign for building causal models — identify variables, map mechanisms,

SKILL.md

causal-modeling.SKILL.md
name: causal-modeling
description: Campaign for building causal models — identify variables, map mechanisms,
  collect evidence, analyze interventions, validate models. Produces causal graphs
  in the wiki vault.
execution: campaign
dependencies:
  strategies:
  - evidence-collection
  - intervention-analysis
  - knowledge-structuring-variable-identification
  - mechanism-mapping
  - model-validation
  tactics:
  - counterfactual-reasoning
  - evidence-weighing
  - feedback-loop-detection
  - knowledge-compilation
  sops:
  - context-checkpoint
  - context-init

Causal Modeling

Build causal models for research domains. Identifies variables, maps causal mechanisms, collects supporting evidence, analyzes potential interventions, and validates the resulting causal graph.

Manifest

| Level | Count | Skills | |-------|-------|--------| | Strategy | 5 | variable-identification, mechanism-mapping, evidence-collection, intervention-analysis, model-validation | | Tactic | 3 | counterfactual-reasoning, evidence-weighing, feedback-loop-detection | | SOP | 10 | variable-page-creation, mechanism-edge-creation, evidence-linking, contradiction-flagging, confidence-scoring, intervention-page-creation, loop-documentation, model-gap-detection, causal-chain-query, validation-report |

Budget Table

| Metric | Small | Medium | Large | |--------|-------|--------|-------| | Variables identified | 8 | 20 | 40 | | Causal edges created | 15 | 40 | 80 | | Evidence pages linked | 10 | 30 | 60 | | Interventions analyzed | 2 | 5 | 10 | | Feedback loops documented | 1 | 3 | 6 |

Strategy Sequence (Reference, Not Prescription)

1. **variable-identification** — identify key variables in the causal system 2. **mechanism-mapping** — map causal mechanisms between variables 3. **evidence-collection** — gather evidence supporting/refuting causal claims 4. **intervention-analysis** — analyze what happens when variables are manipulated 5. **model-validation** — validate the causal model for consistency and completeness

MCP Tools Used

  • `vault_search` — find existing variables and mechanisms
  • `vault_add_edge` — create causal edges (derived_from, supported_by, contradicts)
  • `vault_query_graph` — trace causal chains
  • `vault_graph_stats` — assess model coverage
  • `vault_lint` — validate structural integrity

Context-Management

<HARD-GATE>

  • Call `context-init` at campaign start
  • Call `context-checkpoint` after each strategy completes
  • Call `knowledge-compilation` after each strategy

</HARD-GATE>

Guiding Principles

  • **Correlation is not causation.** Every causal edge must have mechanistic justification, not just statistical association.
  • **Confounders are everywhere.** Actively search for confounding variables that could explain observed relationships.
  • **Interventions reveal truth.** The strongest evidence for causation comes from intervention studies.
  • **Feedback loops are the norm.** Most real systems have circular causation. Document loops explicitly.
  • **Confidence is calibrated.** Strong mechanism + strong evidence = high confidence. Weak either = low confidence.

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

Available Strategies

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

| Strategy | When to use | | --- | --- | | evidence-collection | Gather evidence for causal claims | | intervention-analysis | Analyze interventions and manipulations on the causal system | | knowledge-structuring-variable-identification | Identify key variables in the causal system | | mechanism-mapping | Map causal mechanisms between variables | | model-validation | Validate causal model consistency |

Available Tactics

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

| Tactic | When to use | | --- | --- | | counterfactual-reasoning | Tactic for reasoning about what would happen if variables were different — supports causal identification and intervention analysis. | | evidence-weighing | Tactic for assessing the strength and relevance of evidence for causal claims — distinguishes correlation from causation. | | feedback-loop-detection | Tactic for identifying circular causation — detect feedback loops, classify as reinforcing or balancing, document loop structure. | | knowledge-compilation | Tactic for compiling research findings into vault pages — orchestrates page creation, updates, edge linking, and index maintenance. Minimum yield ≥3 page operations per invocation. |

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. |

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

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The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.

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