causal-tree-building

causal-tree-building is a skill for Claude Code, Codex from yogsoth-ai/de-anthropocentric-research-engine. It costs 50 tokens per session (527 once invoked), scanned A, original, Apache-2.0.

A root-cause analysis method that builds logical trees from visible problems back to their underlying causes, then checks whether each link makes sense.

In plain words
What is it for?
Use it to break down research problems, connect multiple contributing factors, validate causal links, and identify root causes.
Why use it?
It helps separate symptoms from causes and exposes weak or unsupported explanations.

Skill for Claude CodeCodex

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

Good fit Use it to break down research problems, connect multiple contributing factors, validate causal links, and identify root causes.

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Install with agentmods
npx agentmods add skills/yogsoth-ai/de-anthropocentric-research-engine/causal-tree-building
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/de-anthropocentric-research-engine --skill causal-tree-building
Clone the repo
git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine

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 causal-tree-building

README.md
[![agentmods](https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/causal-tree-building/github.svg)](https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/causal-tree-building)
Your own site
<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/causal-tree-building"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/causal-tree-building/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 causal-tree-building

Your own site · 80×15
<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/causal-tree-building"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/causal-tree-building.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 527 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00050 $0.00527
Opus 5 $0.00025 $0.00264
Sonnet 5 $0.00010 $0.00105
Haiku 4.5 $0.00005 $0.00053

Measured 8d ago against content hash ad46edf1f854, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

causal-tree-building 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 8d 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/causal-tree-building/SKILL.md · 61 lines

What it actually says

Causal Tree Building

Build formal causal trees from symptoms to root causes.

Operations

  • ishikawa-decomposition — multi-factor decomposition (6M categories)
  • current-reality-tree — sufficient-cause logic tree
  • clr-validation — validate every causal link

Available SOPs

Subagent: five-whys-drilling, ishikawa-decomposition, current-reality-tree, clr-validation Import: paper-search

Execution Guidance

Decompose via Ishikawa (6M categories adapted for research: Methodology, Data, Theory, Measurement, Researchers, Environment). Build formal CRT with sufficient-cause logic. Validate every causal link with CLR 8-check.

Minimum Yield

<HARD-GATE>
- ishikawa diagrams: >= 1
- CRT constructed: >= 1
- CLR validations: >= 3 links validated
- root causes identified: >= 1
</HARD-GATE>

Available SOPs

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

SOP When to use
clr-validation Apply Goldratt's 8 Categories of Legitimate Reservation to validate causal claims. Tests clarity, existence, sufficiency, and logical integrity.
current-reality-tree Build TOC Current Reality Trees — connect Undesirable Effects via sufficient-cause logic to identify 1-3 root causes.
deep-insight-paper-search AI-powered paper summary and search. Import of literature-engine/literature-search skill. AI summary level — cite as "AI-extracted" not "paper states".
five-whys-drilling Iterative "Why?" questioning (5+ levels) to drill from surface phenomenon to actionable root cause. Each level verified against evidence.
ishikawa-decomposition Decompose problems into 6M categories (Methodology, Data, Theory, Measurement, Researchers, Environment) via fishbone diagram analysis.
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. 8d ago First seen · 61 lines · 50 tokens per session scan A ad46edf1f854

Subscribe to this mod's changes

causal-tree-building is a skill published in the GitHub repository yogsoth-ai/de-anthropocentric-research-engine (462 stars, last pushed 2d ago), licensed Apache-2.0. It adds 50 tokens to every session and 527 once invoked, about $0.0003 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.

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