failure-chain-construction

failure-chain-construction is a skill for Claude Code, Codex from yogsoth-ai/stress-test. It costs 23 tokens per session (292 once invoked), scanned A, original, Apache-2.0.

A method for tracing each failure from its root cause through the failure event to its resulting effects. The chain shows how one problem can lead to another.

In plain words
What is it for?
Use it to build cause-to-effect chains, find shared root causes, and identify failures that can trigger further failures.
Why use it?
It makes systemic and cascading risks easier to understand than a simple list of failure descriptions.

Skill for Claude CodeCodex

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

Good fit Use it to build cause-to-effect chains, find shared root causes, and identify failures that can trigger further failures.

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Install with agentmods
npx agentmods add skills/yogsoth-ai/stress-test/failure-chain-construction
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 failure-chain-construction
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 failure-chain-construction

README.md
[![agentmods](https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/failure-chain-construction/github.svg)](https://agentmods.dev/skills/yogsoth-ai/stress-test/failure-chain-construction)
Your own site
<a href="https://agentmods.dev/skills/yogsoth-ai/stress-test/failure-chain-construction"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/failure-chain-construction/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 failure-chain-construction

Your own site · 80×15
<a href="https://agentmods.dev/skills/yogsoth-ai/stress-test/failure-chain-construction"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/failure-chain-construction.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 23 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 292 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 $0.00023 $0.00292
Opus 5 $0.00012 $0.00146
Sonnet 5 $0.00005 $0.00058
Haiku 4.5 $0.00002 $0.00029

Measured 9d ago against content hash 5d408ac7040f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

failure-chain-construction 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 9d 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/failure-chain-construction/SKILL.md · 48 lines

What it actually says

Failure Chain Construction

Builds multi-level cause → mode → effect chains for systemic failure understanding.

Execution

Subagent — spawned via subagent-spawning/spawn-agent.

Why Subagent

Chain construction requires disciplined causal reasoning without skipping levels. Isolated context prevents shortcutting.

Input

  • failure_modes: Structured failure mode catalog
  • function_tree: Function decomposition for context
  • depth: Max chain depth (2/4/6 per budget)

Output

  • chains: List of cause-mode-effect chains with level annotations
  • shared_causes: Root causes appearing in multiple chains
  • cascade_risks: Modes that trigger other modes

Available SOPs

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

SOP When to use
spawn-agent Spawn a customized CC subagent with full MCP tool access. Used by SOPs that declare execution: subagent.
Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 9d ago First seen · 48 lines · 23 tokens per session scan A 5d408ac7040f

Subscribe to this mod's changes

failure-chain-construction is a skill published in the GitHub repository yogsoth-ai/stress-test (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 23 tokens to every session and 292 once invoked, about $0.0001 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 2026-08-31.

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