codex-goals

Patterns and anti-patterns for using OpenAI Codex Goals — the persistent objectives feature introduced in Codex 0.128.0. Use this skill whenever writing, reviewing, or debugging a `/goal` invocation, deciding whether a task should be a Goal at all, drafting a research Goal that needs an evidence ledger, or diagnosing a Goal that completed against the wrong surface. Triggers on `/goal`, "Codex Goal", "Codex goals", "persistent objective", "evidence-based completion", "iteration policy", "blocked stop condition", or any user message describing a multi-turn Codex task with a defined finish line. Trigger even if the user doesn't explicitly mention Goals — if they're typing "/goal" or asking Codex to "keep going until X", this skill applies.

跳到安装

仓库: pproenca/dot-skills
最近来源活动: 2026年5月27日 09:50
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 codex-goals

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。

检查来源文件

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。

文件资源管理器

37 个文件

SKILL.md

来源说明 · 只读预览

返回搜索返回安装

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

OpenAI Codex Goals Best Practices

Reference for writing and managing Codex Goals — the persistent objective feature introduced in Codex 0.128.0. "Best practices" here means the patterns and anti-patterns that determine whether a Goal completes against the right evidence vs. silently against the wrong surface. Contains 31 rules across 8 categories, ordered by how much they affect whether a Goal completes correctly. Derived from the official OpenAI cookbook article "Using Goals in Codex".

When to Apply

Reference these guidelines when:

Deciding whether a task warrants a /goal or a normal prompt

Drafting or strengthening a /goal invocation

Reviewing a Goal someone else wrote before activating it

Debugging a Goal that completed against the wrong verification surface

Setting up a research Goal where exact proof may not be available

Managing Goal lifecycle (pause, resume, clear) across thread sessions

Writing the iteration policy or blocked stop condition for a long-running Goal

Diagnosing a Goal that hit its budget without completing

Rule Categories by Priority

name

codex-goals

description

OpenAI Codex Goals Best Practices

When to Apply

Reference these guidelines when:

Deciding whether a task warrants a /goal or a normal prompt
Drafting or strengthening a /goal invocation
Reviewing a Goal someone else wrote before activating it
Debugging a Goal that completed against the wrong verification surface
Setting up a research Goal where exact proof may not be available
Managing Goal lifecycle (pause, resume, clear) across thread sessions
Writing the iteration policy or blocked stop condition for a long-running Goal
Diagnosing a Goal that hit its budget without completing

Priority	Category	Impact (worst rule)	Prefix
1	Goal Fit Decisions	CRITICAL	`fit-`
2	Outcome Definition	CRITICAL / HIGH	`outcome-`
3	Verification Surface	CRITICAL / HIGH	`verify-`
4	Boundaries & Iteration	HIGH	`bound-`
5	Lifecycle Commands	HIGH	`life-`
6	Evidence-Based Completion	HIGH	`evidence-`
7	Crafting Strong Goals	MEDIUM	`craft-`
8	Research Goals & Anti-Patterns	MEDIUM	`research-`

File	Description
AGENTS.md	Compiled TOC built by `build-agents-md.js`
references/_sections.md	Category definitions and impact ordering
assets/templates/_template.md	Template for new rules
metadata.json	Version and reference information
gotchas.md	Failure points discovered through use

codex-goals

安装方式

检查来源文件

OpenAI Codex Goals Best Practices

When to Apply

Rule Categories by Priority

OpenAI Codex Goals Best Practices

When to Apply

Rule Categories by Priority

Quick Reference

1. Goal Fit Decisions (CRITICAL)

2. Outcome Definition (CRITICAL)

3. Verification Surface (CRITICAL)

4. Boundaries & Iteration (HIGH)

5. Lifecycle Commands (HIGH)

6. Evidence-Based Completion (HIGH)

7. Crafting Strong Goals (MEDIUM)

8. Research Goals & Anti-Patterns (MEDIUM)

How to Use

Reference Files

codex-goals

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

OpenAI Codex Goals Best Practices

When to Apply

Rule Categories by Priority

OpenAI Codex Goals Best Practices

When to Apply

Rule Categories by Priority

Quick Reference

1. Goal Fit Decisions (CRITICAL)

2. Outcome Definition (CRITICAL)

3. Verification Surface (CRITICAL)

4. Boundaries & Iteration (HIGH)

5. Lifecycle Commands (HIGH)

6. Evidence-Based Completion (HIGH)

7. Crafting Strong Goals (MEDIUM)

8. Research Goals & Anti-Patterns (MEDIUM)

How to Use

Reference Files