query-derivation

query-derivation is a skill for Claude Code from voro6yov/spec-driven-development. It costs 51 tokens per session (2,001 once invoked), scanned A, original, Apache-2.0.

A rulebook for deriving the query part of a Mermaid domain diagram from its command part. It defines how repositories, information views, nested views, filters, brief views, and list results are projected.

In plain words
What is it for?
Use it as the reference when deriving or checking query classes from aggregate roots, repositories, fields, and lookup methods.
Why use it?
It gives the tools one fixed method for producing the read-side model, so the same command diagram leads to the same query design.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter.

Part of the model-diagrams plugin — 4 skills, 4 agents shipped together

Good fit Use it as the reference when deriving or checking query classes from aggregate roots, repositories, fields, and lookup methods.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/voro6yov/spec-driven-development/query-derivation
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 voro6yov/spec-driven-development --skill query-derivation
Clone the repo
git clone --depth 1 https://github.com/voro6yov/spec-driven-development

Made for: Claude Code.

Or install model-diagrams, the plugin that ships this one along with the rest of its 4 skills, 4 agents.

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 query-derivation

README.md
[![agentmods](https://agentmods.dev/badge/skills/voro6yov/spec-driven-development/query-derivation/github.svg)](https://agentmods.dev/skills/voro6yov/spec-driven-development/query-derivation)
Your own site
<a href="https://agentmods.dev/skills/voro6yov/spec-driven-development/query-derivation"><img src="https://agentmods.dev/badge/skills/voro6yov/spec-driven-development/query-derivation/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 query-derivation

Your own site · 80×15
<a href="https://agentmods.dev/skills/voro6yov/spec-driven-development/query-derivation"><img src="https://agentmods.dev/badge/skills/voro6yov/spec-driven-development/query-derivation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,001 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 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 $0.00051 $0.02001
Opus 5.5 $0.00020 $0.00800
Sonnet 5.5 $0.00010 $0.00400
Haiku 4.5 $0.00005 $0.00200

Measured 12d ago against content hash ce1ebe31245b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

query-derivation 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 12d 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.

plugins/model-diagrams/skills/query-derivation/SKILL.md · 172 lines

How it starts

The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Query Part Derivation

Purpose

A domain diagram in this project has a command part (the aggregate root, its Command<X>Repository, child entities / value objects, domain events, and <<TypedDict>> data structures) and a query part (the read-side classes). The query part is almost entirely a mechanical projection of the command part.

This skill is the single source of truth for that projection. It is consulted by:

  • model-diagrams:derive-query-part — the orchestrator skill that interviews the user and delegates the write.
  • model-diagrams:query-part-deriver — the agent that parses the command part and writes the query classes in place.

Both must derive identical output from identical input; divergence between them is a bug in whichever one drifted from this skill.

Command-part inputs

From the classDiagram block, identify:

  • <X> — the single <<Aggregate Root>> class. Its private fields (-name) and its computed properties (+status) are the source of the read model.
  • Command<X>Repository — the <<Repository>> whose name starts with Command. Its lookup methods seed the query repository.
  • Child classes — every <<Entity>> / <<Value Object>> reachable from <X> through composition (*--) or aggregation (o--).
  • Command-side <<TypedDict>> — *Data types and shared types (e.g. Globals, ParsingError). These are reuse candidates (see Type reuse rule).

Domain events, domain services, and Command<X>Repository itself are not projected — the query part ignores them.

<x> below is the aggregate name in snake_case; <X> is the class name.

Query-part outputs

Emit these six class kinds, in this order, at the tail of the classDiagram block — after the last command class, before the closing ```.

1. Query<X>Repository <<Repository>>

  • find_<x>(<x>_id: str) <X>Info | None — always emitted; the projection of Command<X>Repository.<x>_of_id.
  • For each alternate lookup on the command repository — any method returning the aggregate <X> that is not <x>_of_id (e.g. template_of_source_id, project_with_details) — a find_<x>_by_<thing>(<same params>) <X>Info | None. <thing> is the distinguishing noun (template_of_source_id → find_template_by_source; project_with_details → find_project_by_details). Whether each alternate lookup is projected is a feedback point (see below).
  • find_<x>s(filtering: <X>Filtering | None, pagination: Pagination | None) <X>ListResult — always emitted.
  • has_* methods, save, and delete are never projected.

Read the full file on GitHub · 172 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. 12d ago First seen · 172 lines · 51 tokens per session scan A ce1ebe31245b

Subscribe to this mod's changes

query-derivation is a skill published in the GitHub repository voro6yov/spec-driven-development (5 stars, last pushed 13d ago), licensed Apache-2.0. It adds 51 tokens to every session and 2,001 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-04.

Related

Other skills, from other repositories

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens