synthetic-adjunctions

synthetic-adjunctions is a skill for Claude Code, Codex from plurigrid/asi. It costs 23 tokens per session (1,093 once invoked), scanned A, original, MIT.

A formal method for generating adjunctions, which are paired mathematical mappings that describe relationships between constructions, in directed type theory.

In plain words
What is it for?
It is for constructing limits, colimits, Kan extensions, monads, and other structures derived from adjunctions.
Why use it?
It turns universal properties into explicit data such as units, counits, and the rules that ensure the pair behaves correctly.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It is for constructing limits, colimits, Kan extensions, monads, and other structures derived from adjunctions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/plurigrid/asi/synthetic-adjunctions
Install

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.

Any agent
npx skills add plurigrid/asi --skill synthetic-adjunctions
Clone the repo
git clone --depth 1 https://github.com/plurigrid/asi

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for synthetic-adjunctions

README.md
[![agentmods](https://agentmods.dev/badge/skills/plurigrid/asi/synthetic-adjunctions/github.svg)](https://agentmods.dev/skills/plurigrid/asi/synthetic-adjunctions)
Your own site
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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.

agentmods 80×15 button for synthetic-adjunctions

Your own site · 80×15
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Per session 23 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,093 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
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 content
    Fix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 7d ago against content hash 839a76062c51, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

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.

ies/music-topos/.ruler/skills/synthetic-adjunctions/SKILL.md · 144 lines

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.

  1. Unit/counit: Natural transformations η, ε
  2. Triangle identities: Coherence conditions
  3. Mate correspondence: Bijection between hom-sets
  4. 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
  }

Read the full file on GitHub · 144 lines

Changes

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.

  1. 7d ago First seen · 144 lines · 23 tokens per session scan A 839a76062c51

Subscribe to this mod's changes

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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