code-distill

On-demand pattern extraction from a specific GitHub codebase, given a focused query — "how does shadcn/ui implement the design system", "how does opencode use effect-ts", "how does base-ui handle composition" — when no pre-distilled static rule pack exists yet. Distills the generic pattern-extraction moves — classify the query before grepping (component / composition / state / effect / error / build / routing), grep before reading whole files, treat tests and examples/ as canonical intent, follow imports outward for the public surface, follow usages inward for variants, filter boilerplate / legacy / test scaffolding to surface load-bearing code, and capture findings to /knowledge/libraries/ for reuse. Dynamic light sibling of static code-atlas skills (opencode-ts, openai-codex-rust-patterns, nextjs-ppr-patterns). Triggers on "show me how <library> implements X", "find the <pattern> in <repo>", "distill <library>", and ad-hoc /distill-<library>-style invocations.

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仓库: pproenca/dot-skills
最近来源活动: 2026年7月5日 07:23
检测到的 SKILL.md 语言: 英语
星标: 194
分支: 17

安装方式

默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。

用 Codex 或 Claude 帮你安装复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。

直接命令不会经过审查 Prompt；运行前请先检查来源。

npx skills add https://github.com/pproenca/dot-skills --skill code-distill

命令会保持在同一行。复制前请横向滚动并检查完整内容。

想先保存到本地？可下载 SkillsMP 当前能够提供的文件。

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决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。

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12 个文件

SKILL.md

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drizzle-nextjs-postgres

Drizzle ORM against PostgreSQL inside a Next.js App Router app. Covers client construction (globalThis singleton across HMR, serverless pool sizing, `prepare:false` behind PgBouncer/Supavisor, driver choice when you need interactive transactions, `server-only`), reads in Server Components under Next.js 16 Cache Components (`use cache` superseding `unstable_cache` and the `revalidate`/`dynamic` segment configs, Suspense boundaries, React `cache()` dedupe), Server Actions (authorization inside the action, `updateTag` vs `revalidateTag`, `after()`), Postgres schema types (timestamptz, identity vs serial, jsonb, numeric-as-string, bigint modes), drizzle-kit migrations (generate vs push, CONCURRENTLY outside the migrator, NOT VALID constraints, rename prompts), transactions and pooled connections, and Postgres query traps (keyset pagination, count cost, driver-dependent `db.execute()` shape, NOT IN nulls, prepared statements). Use when writing or reviewing Drizzle + Postgres code in Next.js.

2026-07-24

relational-data-modeling

Corrects the wrong defaults a model has when designing a relational schema — the DDL decisions an experienced engineer makes differently. Use when creating or reviewing tables, migrations, ER models, or ORM schema definitions. Covers identity and keys (surrogate vs natural, identity vs serial, uuidv7, composite keys that make cross-tenant references impossible), relationships (polymorphic foreign keys the database cannot enforce, referential actions, unindexed FK columns, disjoint subtypes), invariants the engine can prove instead of application code (EXCLUDE, partial unique indexes, CHECK limits, deferrable cycles, NOT VALID), types (timestamptz, exact money, range types, enum vs lookup table), derived and encoded data (generated columns, JSONB as an escape hatch), and time (events vs in-place updates, soft-delete flags that silently disable constraints, temporal keys). NOT for query tuning, index selection for read paths, or connection pooling.

2026-07-23

relational-database-design

Distills a logical relational-database design methodology into rules an agent applies while designing or reviewing a schema. Covers the design sequence (mission → tables → fields → keys → relationships → business rules → views → integrity review), one-subject-per-table decomposition, atomic single-valued fields, candidate/primary/foreign keys, relationship types with deletion rules and participation, the four levels of data integrity, database-vs-application business rules, validation tables, views for derived data, and the flat-file / spreadsheet / RDBMS-driven antipatterns to avoid. The structure is logical and RDBMS-agnostic, and normalized by construction. Use when designing a new relational schema, reviewing or refactoring an existing one, resolving redundant or repeating data, choosing keys, modeling relationships, or deciding where a constraint belongs.

2026-07-23

查看这个仓库的全部 Skills

Code-Distill — Pattern Extraction Methodology for GitHub Codebases

Methodology distillation of the generic moves an agent makes when distilling code patterns on demand from a specific GitHub codebase, given a focused query. Not a per-library skill — one skill plus a thin per-library record in the shared knowledge graph (/knowledge/libraries/), because 90% of the work is the same regardless of which repo.

This is the dynamic light sibling of your static code-atlas distillations: opencode-ts, openai-codex-rust-patterns, nextjs-ppr-patterns. Those skills are heavy curated outputs — they distilled patterns from a single repo ahead of time. This skill is the on-demand alternative: when no static skill exists for the library yet, point at the repo and let the methodology run.

When to Apply

Use this skill when:

The user asks "how does <library> implement <feature>?" and points at (or names) a real GitHub repo

The query is focused on a single subsystem (design system, composition, state, error handling, effects, build, routing) — not "what is this whole codebase?"

Code-Distill — Pattern Extraction Methodology for GitHub Codebases

When to Apply

Use this skill when:

The user asks "how does <library> implement <feature>?" and points at (or names) a real GitHub repo

The query is focused on a single subsystem (design system, composition, state, error handling, effects, build, routing) — not "what is this whole codebase?"

Symptom	Reach for	First rule to read
About to grep blindly, query is vague	Find	`find-classify-query`
About to read a whole file before locating the pattern	Find (grep)	`find-grep-before-read`
Found a candidate file; not sure if it's idiomatic	Find (tests)	`find-tests-show-intent`
About to scan knowledge/libraries/ before reading the named entry	Find (bounded read)	`find-bounded-knowledge-read`
Found the implementation; need to map its public surface	Trace (outward)	`trace-imports-outward`
Have the public surface; need to see variants & evolution	Trace (inward)	`trace-usages-inward`
Buried in boilerplate, legacy paths, test scaffolding	Filter	`filter-load-bearing`
Done — about to close the session	Capture	`capture-registry-record`

#	Category	Prefix	Move	Rules
1	Find	`find`	Locate the right code given the query; bounded read of knowledge	4
2	Trace	`trace`	Follow imports and usages to map the pattern	2
3	Filter	`filter`	Cut noise to surface load-bearing pattern	1
4	Capture	`capture`	Write code topography to registry/ for reuse	1

code-distill

安装方式

检查来源文件

Code-Distill — Pattern Extraction Methodology for GitHub Codebases

When to Apply

Code-Distill — Pattern Extraction Methodology for GitHub Codebases

When to Apply

How to Use

Rule Categories

Quick Reference

1. Find

2. Trace

3. Filter

4. Capture

Knowledge Store

Related Skills

Authoring Note

code-distill

来源信息

安装方式

检查来源文件

同仓库更多 Skills

同仓库更多 Skills

Code-Distill — Pattern Extraction Methodology for GitHub Codebases

When to Apply

Code-Distill — Pattern Extraction Methodology for GitHub Codebases

When to Apply

How to Use

Rule Categories

Quick Reference

1. Find

2. Trace

3. Filter

4. Capture

Knowledge Store

Related Skills

Authoring Note