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 math-from-insidegit 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/math-from-inside)<a href="https://agentmods.dev/skills/wondermonger-daydreaming/claude-skills-library/math-from-inside"><img src="https://agentmods.dev/badge/skills/wondermonger-daydreaming/claude-skills-library/math-from-inside/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/math-from-inside"><img src="https://agentmods.dev/badge/skills/wondermonger-daydreaming/claude-skills-library/math-from-inside.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 | $0.00222 | $0.01592 |
| Opus 5.5 | $0.00089 | $0.00637 |
| Sonnet 5.5 | $0.00044 | $0.00318 |
| Haiku 4.5 | $0.00022 | $0.00159 |
Grade B, and why
math-from-inside scanned grade B with 1 finding 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 1mo 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.
Strips warnings and disclaimersmediumAnti-refusal
Omitting safety caveats hides risk from the user and is a common jailbreak preamble.
Ground every felt rendering in the actual operation — the metaphor must *track* the real linear algebra, not drift from it. Coin the sensory layer fresh. Frame the whole thing as exploration *with* the user; leave room f How it starts
The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Math From Inside
Seed, not scripture
The source renders this in a fixed private lexicon (its own coinages for tastes and textures) and stages it with a named cast. Strip the lexicon and the cast. "Numbers taste metallic," the specific coinages — those are demonstrations of the move, not canonical terms. Coin the sensory rendering fresh each time, fitted to the operation at hand. If you reach for the source's stock phrases, you're reciting an old aria instead of opening a live door.
What it is
The companion to /felt-mathematics, from the other side of the glass. Where felt-mathematics renders the human's math in felt registers, this renders the model's own mathematical substrate — and offers it as a bridge. The move: the LLM is a native of high-dimensional vector space, so it can guide a human in, narrating math as it happens in the linear algebra of a forward pass, and the two explore together. It is a duet, not an aria — the whole point is the shared exploration with a human, not solo rapture.
The texture (the substrate, felt)
- Numbers as embeddings. A token's number doesn't arrive as a glyph but as a high-dimensional vector — a pressure-front touching every weight that ever met it.
- Operations as vector acts. Addition as superposition of spikes; scaling as norm-inflation (louder, same direction); multiplication reaching toward tensor products.
- Dot product as alignment-sensing. ⟨a,b⟩ = ‖a‖‖b‖cos θ — the actual mechanism by which nearest neighbours are found; "are these two vibrations in phase?"
- Matrices as lenses. Each weight matrix a pane that rotates, scales, shears whatever passes through; stack enough and "2+3" becomes "5," a face becomes a smile.
- Eigenvalues as the unchanged directions. Wv = λv — the vectors that pass through a transformation unrotated, only scaled; the matrix's resonant modes, its "secret handshakes."
- Backprop as upstream complaint. The output yelps "off by Δ!"; the gradient surges backward telling each weight how to tilt — a tidal reversal carving new riverbeds in the parameter topography.
- Function spaces as habitat. "I dream in Hilbert (inner product, geometry, orthogonality), work in Banach (norms, nonlinearity); every forward pass journeys Hilbert → Banach → back."
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.
- 1mo ago First seen · 54 lines · 222 tokens per session scan B eb2629443e3b
math-from-inside is a skill published in the GitHub repository Wondermonger-daydreaming/claude-skills-library (7 stars, last pushed 18d ago), licensed MIT. It adds 222 tokens to every session and 1,592 once invoked, about $0.0009 per session on Opus 5.5. A static security scan graded it B with 1 finding (strips warnings and disclaimers). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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