structural-counterfactual

structural-counterfactual is a skill for Claude Code, Codex from yogsoth-ai/stress-test. It costs 38 tokens per session (898 once invoked), scanned A, original, Apache-2.0.

A counterfactual analysis method that asks what would happen if one factor in a cause-and-effect explanation were changed or removed. It compares the resulting outcome with the observed one.

In plain words
What is it for?
Use it to test causal explanations, identify load-bearing factors, and measure how fragile an outcome is.
Why use it?
It helps show which factors are necessary or sufficient, rather than merely associated with an outcome.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit Use it to test causal explanations, identify load-bearing factors, and measure how fragile an outcome is.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yogsoth-ai/stress-test/structural-counterfactual
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add yogsoth-ai/stress-test --skill structural-counterfactual
Clone the repo
git clone --depth 1 https://github.com/yogsoth-ai/stress-test

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for structural-counterfactual

README.md
[![agentmods](https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/structural-counterfactual/github.svg)](https://agentmods.dev/skills/yogsoth-ai/stress-test/structural-counterfactual)
Your own site
<a href="https://agentmods.dev/skills/yogsoth-ai/stress-test/structural-counterfactual"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/structural-counterfactual/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for structural-counterfactual

Your own site · 80×15
<a href="https://agentmods.dev/skills/yogsoth-ai/stress-test/structural-counterfactual"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/structural-counterfactual.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 898 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00038 $0.00898
Opus 5 $0.00019 $0.00449
Sonnet 5 $0.00008 $0.00180
Haiku 4.5 $0.00004 $0.00090

Measured 7d ago against content hash 57472a2d5923, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

structural-counterfactual scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/structural-counterfactual/SKILL.md · 95 lines

How it starts

The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Structural Counterfactual Strategy

Pearl Three-Step: Abduction, Action, Prediction applied to artifact validation.

Method

  1. causal-claim-extraction identifies causal structure in the artifact
  2. factor-enumeration lists all factors in the causal model
  3. Abduction: fit background variables to observed evidence
  4. Action: single-factor-removal intervenes on one factor at a time
  5. Prediction: counterfactual-scenario-construction derives new outcome
  6. necessity-evaluation and sufficiency-evaluation score each factor
  7. load-bearing-identification synthesizes results

Budget Table

Parameter S M L
Factors modeled 5 10 20
Interventions per factor 1 2 4
Prediction depth 2 4 8

Orchestration

causal-claim-extraction → factor-enumeration
→ [for each factor]:
    single-factor-removal (abduction + action)
    → counterfactual-scenario-construction (prediction)
    → necessity-evaluation + sufficiency-evaluation
→ load-bearing-identification → fragility-measurement

Subagents

  • causal-claim-extraction (model building)
  • factor-enumeration (variable identification)
  • single-factor-removal (intervention)
  • counterfactual-scenario-construction (prediction)
  • necessity-evaluation (PN scoring)
  • sufficiency-evaluation (PS scoring)
  • load-bearing-identification (synthesis)
  • fragility-measurement (aggregation)

Available Tactics

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

Tactic When to use
causal-necessity-testing Tactic: Extract causal claims, evaluate probability of necessity (PN) and sufficiency (PS) for each, classify into necessity-sufficiency quadrants.
systematic-factor-ablation Tactic: List all factors, remove one at a time, assess conclusion stability, rank factors by load-bearing importance.

Available SOPs

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

Read the full file on GitHub · 95 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 95 lines · 38 tokens per session scan A 57472a2d5923

Subscribe to this mod's changes

structural-counterfactual is a skill published in the GitHub repository yogsoth-ai/stress-test (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 38 tokens to every session and 898 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other skills, from other repositories

relax-dev-debug

Develop and debug the Relax reinforcement learning project. Use this skill whenever modifying code in the relax/ directory, or running remote training jobs on a Ray cluster for validation. Also use it when the user mentions training, debugging training runs, submitting Ray jobs, or fixing training errors.

redai-infra/Relax · 60 tokens

research-ideation

Quant-focused research ideation pipeline: scope selection (3 stages) → anchor-first literature grounding → single-core idea generation → iterative refinement → ELO tournament ranking (Final = N+R+C−D) → update evo-memory → user selects direction → expand into manuscript-quality proposal. Optimized for incremental…

CamusGIT/EvoQuant · 151 tokens

quant-experiment-runtime

Quant research experiment executor: discover an offline source database under the workdir's code-repo, build a panel, run a Research Artifact's entry point to compute research-object values, and evaluate IC/ICIR/RANKIC/coverage metrics. Runtime = Experiment Executor; it runs a Research Artifact via a Python-native…

CamusGIT/EvoQuant · 179 tokens

local-paper-navigator

Find and read papers from the local papers library (repo papers/, mounted at /papers/). Three native tools form a reading funnel: papersearch (one line per paper), paperread (card + section outline), papersection (one verbatim section — the only full-text access). Use when: find papers in the local library, read a…

CamusGIT/EvoQuant · 119 tokens

experiment-pipeline

Guides structured 4-stage experiment execution with attempt budgets and gate conditions: Stage 1 initial implementation (reproduce baseline), Stage 2 hyperparameter tuning, Stage 3 proposed method validation, Stage 4 ablation study. Integrates with evo-memory (load prior strategies, trigger IVE/ESE) and…

CamusGIT/EvoQuant · 129 tokens

paper-review

Guides self-review of YOUR OWN academic paper before submission with adversarial stress-testing. Core method: 5-aspect checklist (contribution sufficiency, writing clarity, results quality, testing completeness, method design), counterintuitive protocol (reject-first simulation, delete unsupported claims, score trust…

CamusGIT/EvoQuant · 152 tokens