读模型优化

读模型优化 is a skill for Claude Code, Codex from microwind/ai-skills. It costs 28 tokens per session (753 once invoked), scanned A, original, no licence file.

A database read model shaped for specific queries, often using duplicated data or precomputed views to make reading faster.

In plain words
What is it for?
It helps design query-focused models, denormalized tables, and materialized views for read-heavy applications.
Why use it?
It reduces the work a database must do for frequent or complex queries. The trade-off is that duplicated data may need updating when the source changes.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit It helps design query-focused models, denormalized tables, and materialized views for read-heavy applications.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/microwind/ai-skills/read-model-optimization
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 microwind/ai-skills --skill read-model-optimization
Clone the repo
git clone --depth 1 https://github.com/microwind/ai-skills

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 读模型优化

README.md
[![agentmods](https://agentmods.dev/badge/skills/microwind/ai-skills/read-model-optimization/github.svg)](https://agentmods.dev/skills/microwind/ai-skills/read-model-optimization)
Your own site
<a href="https://agentmods.dev/skills/microwind/ai-skills/read-model-optimization"><img src="https://agentmods.dev/badge/skills/microwind/ai-skills/read-model-optimization/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.

agentmods 80×15 button for 读模型优化

Your own site · 80×15
<a href="https://agentmods.dev/skills/microwind/ai-skills/read-model-optimization"><img src="https://agentmods.dev/badge/skills/microwind/ai-skills/read-model-optimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 753 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.
Origin unknown 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 $0.00028 $0.00753
Opus 5 $0.00014 $0.00377
Sonnet 5 $0.00006 $0.00151
Haiku 4.5 $0.00003 $0.00075

Measured 8d ago against content hash 8c2cd5e45086, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

读模型优化 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 8d 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.

domain-driven-design/read-model-optimization/SKILL.md · 102 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. 8d ago First seen · 102 lines · 28 tokens per session scan A 8c2cd5e45086

Subscribe to this mod's changes

读模型优化 is a skill published in the GitHub repository microwind/ai-skills (80 stars, last pushed 3mo ago), with no licence file. It adds 28 tokens to every session and 753 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.

Related

Other skills, from other repositories

embeddings

Vector embeddings with HNSW indexing, sql.js persistence, and hyperbolic support. 75x faster with agentic-flow integration. Use when: semantic search, pattern matching, similarity queries, knowledge retrieval. Skip when: exact text matching, simple lookups, no semantic understanding needed.

ruvnet/ruflo · 62 tokens

moai-domain-database

Database specialist covering PostgreSQL, MongoDB, Redis, Oracle, and cloud database platforms (Neon, Supabase, Firestore). Use for schema design, query optimization, indexing strategies, data modeling, or cloud database selection. Cloud vendor guide absorbed from moai-platform-database-cloud.

modu-ai/moai-adk · 64 tokens

moai-platform-database-cloud

Cloud database platform specialist covering Neon (serverless PostgreSQL), Supabase (PostgreSQL 16 with real-time), and Firebase Firestore (NoSQL with offline sync). Use when choosing or setting up cloud databases.

modu-ai/moai-adk · 51 tokens

chroma-integration

Chroma local vector database setup and operations for development and production.

a5c-ai/babysitter · 17 tokens

milvus-integration

Milvus distributed vector database configuration for large-scale RAG applications.

a5c-ai/babysitter · 17 tokens

AgentDB Performance Optimization

Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.

ruvnet/ruflo · 53 tokens