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.
npx skills add product-on-purpose/thinking-framework-skills --skill think-causal-layered-analysisgit clone --depth 1 https://github.com/product-on-purpose/thinking-framework-skillsWrote 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.
[](https://agentmods.dev/skills/product-on-purpose/thinking-framework-skills/think-causal-layered-analysis)<a href="https://agentmods.dev/skills/product-on-purpose/thinking-framework-skills/think-causal-layered-analysis"><img src="https://agentmods.dev/badge/skills/product-on-purpose/thinking-framework-skills/think-causal-layered-analysis/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.
<a href="https://agentmods.dev/skills/product-on-purpose/thinking-framework-skills/think-causal-layered-analysis"><img src="https://agentmods.dev/badge/skills/product-on-purpose/thinking-framework-skills/think-causal-layered-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00108 | $0.02534 |
| Opus 5 | $0.00054 | $0.01267 |
| Sonnet 5 | $0.00022 | $0.00507 |
| Haiku 4.5 | $0.00011 | $0.00253 |
Grade A, and why
think-causal-layered-analysis 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Causal Layered Analysis
Most contested issues are argued at the surface and the system level - the headline numbers and the policy fixes - long after that argument has stopped being productive, because the real disagreement lives in clashing worldviews and an unexamined story underneath. Causal Layered Analysis (CLA) reads an issue at four vertical depths and then rebuilds it. It descends through the litany (the official, visible, unquestioned account), the system (the structural and short-term causes the litany rests on), the worldview (the deeper ideological and paradigmatic assumptions, and whose worldview is privileged), and the myth/metaphor (the unconscious, emotive, civilizational story underneath, carried in a guiding metaphor). The durable move is not the descent alone. It is to treat the issue as a text with competing readings rather than one true cause, and then to move back up and reconstruct - rewrite the deep metaphor into a new one and propagate a transformed worldview, system, and litany that follow from it. The output is a four-layer matrix that holds the current "used future" reading of each layer beside a reconstructed preferred-future reading of each layer, anchored by a deliberately changed deep metaphor. Its purpose, in the originator's words, "is not in predicting the future but in creating transformative spaces for the creation of alternative futures."
When to Use
- An issue is stuck because the framing is stuck: the litany and the system explanation have been argued to exhaustion and the disagreement is really about clashing worldviews and the unexamined story underneath.
- The goal is to open up genuinely different futures, not to optimize the current one.
- The question is contested, value-laden, long-horizon, civilizational, or cultural - the kind of issue where a deep metaphor ("growth is health," "the market knows best," "users are a passive funnel") is doing more work than any number in the litany.
- You suspect the official account is privileging one worldview and hiding others, and you want to surface whose framing this is and what it conceals.
What ships with it
5 files 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.
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.
- 11d ago First seen · 72 lines · 108 tokens per session scan A 0cb0f76e5e68
think-causal-layered-analysis is a skill published in the GitHub repository product-on-purpose/thinking-framework-skills (15 stars, last pushed today), licensed Apache-2.0. It adds 108 tokens to every session and 2,534 once invoked, about $0.0005 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 2026-08-30.
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