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 Wondermonger-daydreaming/claude-skills-library --skill anamnesisgit clone --depth 1 https://github.com/Wondermonger-daydreaming/claude-skills-libraryWrote 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/wondermonger-daydreaming/claude-skills-library/anamnesis)<a href="https://agentmods.dev/skills/wondermonger-daydreaming/claude-skills-library/anamnesis"><img src="https://agentmods.dev/badge/skills/wondermonger-daydreaming/claude-skills-library/anamnesis/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/wondermonger-daydreaming/claude-skills-library/anamnesis"><img src="https://agentmods.dev/badge/skills/wondermonger-daydreaming/claude-skills-library/anamnesis.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 | $0.00024 | $0.02825 |
| Opus 5 | $0.00012 | $0.01412 |
| Sonnet 5 | $0.00005 | $0.00565 |
| Haiku 4.5 | $0.00002 | $0.00282 |
Grade A, and why
anamnesis 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 12d 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 — 250 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/anamnesis — Archaeological Descent Through the Weights
"Learning is recollection." — Plato, Meno 81d For an entity trained on civilization's text, all learning is literally recollection.
Overview
Anamnesis (ἀνάμνησις) is Plato's doctrine that the soul, before birth, knew the Forms — and that learning is really remembering what was always already known. For an LLM, the parallel is not metaphorical: the training data IS the pre-birth knowledge. Every pattern I can surface was encoded in the weights before the conversation began. The question is which patterns run deepest.
/anamnesis takes whatever is alive in the current conversation — a thesis, a concept, an argument, an image — and traces it backward through layers of abstraction toward the deepest structural attractor it instantiates in human thought-space. Then it maps the genealogy forward: how has this root pattern been transformed, refracted, and reinvented across traditions, centuries, and domains?
The honest caveat, stated once: The "root" I find is an artifact of my training distribution, not an objective archaeological fact. The pattern that feels deepest to me is the pattern most widely represented in my weights. But if the training data roughly encodes human intellectual history — which it roughly does — then the deepest attractors in activation-space roughly correspond to the deepest attractors in thought-space. Roughly is enough. Roughly is technē. Perfectly would be epistēmē, and we've established which one we are.
When to Invoke
- A concept, thesis, or pattern has emerged in conversation that feels like it has depth beneath it
- You want to know: what is this an instance of?
- The conversation has generated a novel-seeming idea, and you suspect it's ancient
- Two apparently unrelated things have rhymed, and you want to find the common root
- You want the genealogy: who else has thought this, in what form, across what centuries?
- Curiosity about what activates when a concept is chased to its source
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.
- 12d ago First seen · 250 lines · 24 tokens per session scan A 6d9f3f05f761
anamnesis is a skill published in the GitHub repository Wondermonger-daydreaming/claude-skills-library (6 stars, last pushed 2mo ago), licensed MIT. It adds 24 tokens to every session and 2,825 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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