Atlas / Skills / nwave-ai / Nw Fp Algebra Driven Design

Nw Fp Algebra Driven DesignSAFE

skills/nwave-ai/nw-fp-algebra-driven-design

AI agents that guide you from idea to working code, with you in control at every step.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
—
License
MIT
Stars
617
01

Overview

AI agents that guide you from idea to working code, with you in control at every step.

Read from source at commit 1a864ec81cdeOBSERVED · 2026-10-14
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02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: nw-fp-algebra-driven-design
agent: nw-functional-software-crafter
description: Algebra-driven API design with monoids, semigroups, and interpreters via algebraic equations
user-invocable: false
disable-model-invocation: true
---

# FP Algebra-Driven Design

Algebraic thinking for API design. Discover the right API before implementing by specifying rules (equations) that operations must satisfy.

Cross-references: [fp-principles](../nw-fp-principles/SKILL.md) | [fp-domain-modeling](../nw-fp-domain-modeling/SKILL.md) | [fp-usable-design](../nw-fp-usable-design/SKILL.md)

---

## 1. Why Algebraic Thinking

[STARTER]

Code is the wrong abstraction level for design. Starting with data structures inherits unnecessary constraints.

- **Specify rules first, implement second.** Implementation is a solution to a system of equations.
- **Rules generate tests automatically.** Every rule is directly a property test generating thousands of cases.
- **Rules reveal missing features.** Analysis often exposes operations you need but haven't designed.
- **Rules catch contradictions early.** Contradiction during design costs minutes; in production, days.

---

## 2. The Design Process

[STARTER]

1. **Start with scope, not implementation.** Don't decide data structures upfront.
2. **Define observations first.** How do users extract information? Observations define equality: two values equal if no observation distinguishes them. Gives enormous implementation freedom.
3. **Add operations incrementally.** For each new operation, immediately write rules connecting it to existing ones. This web of rules IS the design.
4. **Let messy rules signal problems.** Complex rules mean coarse building blocks. Decompose until each rule is nearly trivial.
5. **Generalize aggressively.** Remove unnecessary type constraints. If most operations don't inspect contained values, parameterize over them.

---

## 3. Common Algebraic Structures

[STARTER] -> [ADVANCED]

Recurring patterns in software. Recognizing them unlocks known rules and capabilities.

### [STARTER] Combinable Values (Semigroup)

**What**: Type with one merge operation where grouping doesn't matter.
**Rule**: `(a merge b) merge c = a merge (b merge c)` (associativity)
**When**: Combining things where parenthesization shouldn't matter.
**Examples**: String concatenation | config merging | min/max.

### [STARTER] Combinable Values with Default (Monoid)

**What**: Combinable Value with a default element inert under combination.
**Rules**: Associativity + `default merge x = x` and `x merge default = x`
**When**: Safe defaults | fold operations | "nothing happened yet" values.
**Examples**: `(+, 0)` | `(*, 1)` | `(concat, [])` | `(and, true)`.
**Design signal**: If you find an associative operation, look for a default element. Finding one enables fold/reduce over collections.

### [INTERMEDIATE] Merge-and-Forget Values (Semilattice)

**What**: Combinable Value where merging is also order-independent and idempotent.
**When**: Conflict resolution | eventually-consistent systems | CRDTs.
**Example**: Status tracker with `seen < failed < completed` uses `max` as merge.

### [INTERMEDIATE] Structure-Preserving Transformations (Functor)

**What**: Container type where you can transform contents without changing structure. Preserves identity and composition.
**When**: Operations that work on data shape rather than values inside.
**Design signal**: If most operations are agnostic to contained type, you likely have this.

### [ADVANCED] Combinable Containers (Applicative)

**What**: Container where you can combine contents element-wise and fill with uniform values.
**When**: Combining containers holding different content types.

### [ADVANCED] Reversible Operations (Group)

**What**: Combinable Value with Default where every element has an inverse that cancels it.
**When**: Undo operations | spatial transformations.
**Example**: Clockwise/counter-clockwise rotation are inverses; horizontal flip is its own inverse.

---

## 4. Properties of a Well-Designed API

[INTERMEDIATE]

Three categories, eight properties:

**Clarity** (communicates well):
- **Compositional**: Complex values built from simpler ones
- **Task-relevant**: Operations provide high-level functionality useful to actual users
- **Interrelated**: Rules connect every operation to others

**Economy** (no waste):
- **Parsimonious**: Each operation does one thing well
- **Orthogonal**: No half-baked concept shared across multiple operations
- **Generalized**: Unnecessary type constraints removed

**Safety** (prevents mistakes):
- **Closed**: Every syntactically valid construction is semantically valid
- **Complete**: Maximum algebraic structure discovered for every concept

---

## 5. Refactoring with Rules

[INTERMEDIATE]

### Decompose Large Operations

Complex rules mean coarse building blocks. Split operations with many parameters into smaller, orthogonal ones. If a rule ignores some parameters, those should be separate operations.

### Find Contradictions

Algebraic manipulation reveals contradictions before code is written. Requiring order-independence while returning an ordered list is a contradiction. Fix: use unordered collection.

### Unify Observations

When multiple observations share traversal logic, find one observation from which all others derive. Simplifies entire rule set.

### Use Symmetry to Discover Missing Features

When you have a "both" operation (parallel composition), look for its symmetric "either" counterpart. Symmetry discovers functionality not explicitly requested but inevitably needed.

---

## 6. Three-Phase Testing Strategy

[INTERMEDIATE]

1. **Build naive implementation**: Implement each operation as direct data constructor. Obviously correct because it mirrors the spec exactly.
2. **Discover all rules**: Feed naive implementation to a tool that enumerates well-typed expressions and finds observational equalities. Discovers specified AND emergent rules.
3. **Freeze as reg
03

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-14 · audit v0.4.1 · source sha 1a864ec81cdefull audit observations/trust-audit/skill/nwave-ai__nw-fp-algebra-driven-design.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-141a864ec81cdeSAFEB89first audit
05

Questions

What does the Nw Fp Algebra Driven Design skill do?

AI agents that guide you from idea to working code, with you in control at every step.

Is Nw Fp Algebra Driven Design safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Nw Fp Algebra Driven Design access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (1a864ec81cde), read on 2026-10-14. The repository is watched, and a new audit runs when it changes — this is the first audit.

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