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 plurigrid/asi --skill synthetic-adjunctionsgit clone --depth 1 https://github.com/plurigrid/asiWrote 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/plurigrid/asi/synthetic-adjunctions)<a href="https://agentmods.dev/skills/plurigrid/asi/synthetic-adjunctions"><img src="https://agentmods.dev/badge/skills/plurigrid/asi/synthetic-adjunctions/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/plurigrid/asi/synthetic-adjunctions"><img src="https://agentmods.dev/badge/skills/plurigrid/asi/synthetic-adjunctions.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00023 | $0.01093 |
| Opus 5 | $0.00012 | $0.00547 |
| Sonnet 5 | $0.00005 | $0.00219 |
| Haiku 4.5 | $0.00002 | $0.00109 |
Grade A, and why
synthetic-adjunctions 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 7d 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Synthetic Adjunctions Skill: Universal Construction Generation
Status: ✅ Production Ready Trit: +1 (PLUS - generator) Color: #D82626 (Red) Principle: Adjunctions generate universal structures Frame: Directed type theory with adjoint functors
Overview
Synthetic Adjunctions generates adjunction data in directed type theory. Adjunctions are the fundamental generators of universal constructions—limits, colimits, Kan extensions, and monads all arise from adjunctions.
- Unit/counit: Natural transformations η, ε
- Triangle identities: Coherence conditions
- Mate correspondence: Bijection between hom-sets
- Universal properties: Initial/terminal characterizations
Core Formula
L ⊣ R adjunction:
η : Id → R ∘ L (unit)
ε : L ∘ R → Id (counit)
Triangle identities:
(εL) ∘ (Lη) = id_L
(Rε) ∘ (ηR) = id_R
-- Generate adjunction from universal property
generate_adjunction :: FreeConstruction → Adjunction
generate_adjunction (Free F) = Adjunction {
left = F,
right = Forgetful,
unit = η_universal,
counit = ε_evaluation
}
Key Concepts
1. Adjunction Generation
-- Construct adjunction from representability
representable-adjunction :
(F : A → B) → (G : B → A) →
((a : A) (b : B) → Hom_B(F a, b) ≃ Hom_A(a, G b)) →
Adjunction F G
representable-adjunction F G iso = record
{ unit = λ a → iso.inv (id (F a))
; counit = λ b → iso.to (id (G b))
; triangle-L = from-iso-naturality
; triangle-R = from-iso-naturality
}
2. Free-Forgetful Generation
-- Generate free algebra adjunction
free-forgetful : (T : Monad) → Adjunction (Free T) (Forgetful T)
free-forgetful T = record
{ unit = T.η
; counit = T.μ ∘ T.map(eval)
; triangle-L = T.left-unit
; triangle-R = T.right-unit
}
-- Free monoid on sets
Free-Mon : Adjunction Free Underlying
Free-Mon = free-forgetful List-Monad
3. Kan Extension via Adjunction
-- Left Kan extension as left adjoint to restriction
Lan : (K : A → B) → Adjunction (Lan_K) (Res_K)
Lan K = record
{ left = λ F → colim_{K/b} F ∘ proj
; right = λ G → G ∘ K
; unit = universal-arrow
; counit = eval-at-colimit
}
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.
- 7d ago First seen · 144 lines · 23 tokens per session scan A 839a76062c51
synthetic-adjunctions is a skill published in the GitHub repository plurigrid/asi (62 stars, last pushed 2mo ago), licensed MIT. It adds 23 tokens to every session and 1,093 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 2026-09-03.
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