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-process-tracinggit 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-process-tracing)<a href="https://agentmods.dev/skills/product-on-purpose/thinking-framework-skills/think-process-tracing"><img src="https://agentmods.dev/badge/skills/product-on-purpose/thinking-framework-skills/think-process-tracing/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-process-tracing"><img src="https://agentmods.dev/badge/skills/product-on-purpose/thinking-framework-skills/think-process-tracing.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 | $0.00150 | $0.02351 |
| Opus 5 | $0.00075 | $0.01175 |
| Sonnet 5 | $0.00030 | $0.00470 |
| Haiku 4.5 | $0.00015 | $0.00235 |
Grade A, and why
think-process-tracing 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 10d 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Process Tracing (rival-explanation adjudication)
When one thing has happened and several stories compete to explain why, the instinct is to tally evidence: pile up what supports each story and pick the side with the bigger pile. That rewards whichever explanation attracted the most loosely-relevant chatter. Process tracing refuses the tally. It weighs each piece of within-case evidence by its diagnosticity - its power to eliminate or confirm an explanation - so that one decisive observation outranks any amount of weak, ambiguous support. The durable move is to make each rival explanation concrete as a causal mechanism chain (the step-by-step way that story would have produced this outcome, and the observable fingerprints each step would leave), state those expected fingerprints before weighing the evidence, then type each piece of evidence by certainty (if the explanation is true, must we see this?) and uniqueness (could the rivals also produce it?). A single failed hoop test eliminates a rival no matter how much straw-in-the-wind support it had. The output is a rival-explanation evidence ledger: the rivals, each one's mechanism chain, every evidence item typed per rival, the surviving explanation with its residual uncertainty, and the single most decisive observation still missing. It is explicitly not a cross-case generalization, not a consistency-scoring matrix, and not a manufactured winner when nothing available is diagnostic.
When to Use
- One outcome has occurred and there are genuinely rival stories about why it happened: an incident postmortem with three competing root-cause theories, a churn spike (a pricing change versus a competitor launch versus an onboarding regression), a lost deal, a metric anomaly, a contested past decision.
- Mechanism-level evidence is available or obtainable - logs, timestamps, documents, sequence of events, who knew what when - that could discriminate the rivals rather than merely decorate them.
- The argument has become a shouting match between narratives, and the useful reframing is "what would I expect to see if THIS story were true that the others would not produce?"
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.
- 10d ago First seen · 75 lines · 150 tokens per session scan A d96effe70e4a
think-process-tracing is a skill published in the GitHub repository product-on-purpose/thinking-framework-skills (15 stars, last pushed 23d ago), licensed Apache-2.0. It adds 150 tokens to every session and 2,351 once invoked, about $0.0007 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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