Check if a RIG preview deployment is actually running and healthy. Verifies CI triggered, images exist, pods started, and services respond. Use when a PR deployment seems broken or after pushing code.
日本語の概要は準備中です。原文の説明を表示しています。
Builds and audits a concept-ontology for a regelrecht corpus to decide and verify reference types — cross-law source-binding vs intra-law source-binding vs open-norm leaf vs external-fact leaf — and to catch concept conflation across laws. Core principle: a value's reference type is fixed by WHO derives it, and a binding is sound only when producer and consumer denote the SAME concept; the lexical surface (the word in the text) is not the concept. Detects false friends (one term, different concepts — e.g. a register-based vs a factual "naar de omstandigheden"-based residence/ingezetene concept), orphan plain-params (a value a regulation actually derives, modeled as a brute input), negation/complement re-entry (¬X modeled as an independent leaf next to X), and duplication (one concept re-entered as several independent leafs, losing the single-source-of-truth invariant). Produces a law-level glossary and a stelsel-level concept map with sound same-concept binding edges and flagged lexical-match-but-concept-mismatch edges. Use when deciding whether a value should be cross-law/intra-law/leaf, when the same term means different things across laws, or when a binding might silently conflate concepts.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Two recurring questions in a cross-law model: (1) what reference type should a value be — a cross-law source-binding, an intra-law source-binding, an open-norm leaf, or an external-fact leaf — and (2) is a given binding sound, given that the same term can denote a different concept in a different law. This skill answers both by building a concept-ontology and auditing references against it.
The reference type of a modeled value is fixed by who derives it. A source-binding is sound only when the producer and the consumer denote the same concept. The lexical surface — the word in the
text:— is not the concept: two laws can use one word for different concepts (false friends), or different words for one concept (synonyms). The engine runs a conflated binding without complaint; only concept analysis catches it.
For each modeled value, ask in order:
Anti-patterns to flag:
The discriminator is the determination-mode, not the lexeme. For each term the corpus reckons with, tag its mode:
Then cluster surface forms into canonical concepts by mode + legal referent, not by spelling:
For each existing source-binding P (law A) ← E (law B):
Across the corpus:
| Bucket | Meaning | Action |
|---|---|---|
| structural-fix | the reference type or binding is mechanically wrong vs the derivation/concept facts | rebind / derive from one source / decompose |
| concept-question (jurist) | whether two concepts are legally equivalent is a normative call (e.g. "do we accept a register as proxy for a factual open norm?") | jurist decides; document the proxy-with-rationale or reject |
| accept-with-rationale | a deliberate proxy (e.g. a register as best machine-readable indicator of a factual norm) | keep — but model the register as an indicator that feeds the open-norm weging, never as its silent replacement; annotate |
Cardinal rule: a register may inform a factual open-norm determination but must not silently replace it — that substitution is the canonical conflation (mirrors the standard "naar de omstandigheden te beoordelen" + "een enkele inschrijving is niet voldoende"-doctrine). Keep the model symmetric: if one side of a stelsel models a concept factually, the mirror side must too, unless a documented decision says otherwise.
term → canonical concept → determination-mode → reference-type → endpoint/leaf id.Confirm a "derived" claim by locating the producing endpoint; confirm a conflation by showing the determination-modes differ, not by the wording. After a rebind/derive/decompose: schema-validation and cross-law-integriteit stay green, and end-to-end outcomes are unchanged where the concept was already equivalent (anti-masking: flip a source fact, see the outcome move). A rebinding that changes outcomes means the concepts were genuinely different — that is a finding, not a regression.
law-letter-fidelity-audit — is the model faithful to the letter (vs toelichting / desired
outcome)? Orthogonal to this skill, which asks whether the references are the right type and
whether bindings respect concept identity. Run fidelity first (terms letter-true), then this
(terms wired and clustered right).law-generate — the placement/binding mechanics (source under input:, not parameters:). This
skill decides which binding type and whether a binding is conceptually sound.regelrecht-stelselanalyse — cross-law-integriteit (dangling / plain-param) is the mechanical
layer; this skill adds the conceptual layer on top (same-concept binding, false-friend
detection).まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Check if a RIG preview deployment is actually running and healthy. Verifies CI triggered, images exist, pods started, and services respond. Use when a PR deployment seems broken or after pushing code.
日本語の概要は準備中です。原文の説明を表示しています。
Performs critical code reviews using REVIEW.md guidelines. Evaluates code quality, architecture, testing, and domain-specific concerns (legal faithfulness, cross-law references, engine safety). Use after completing significant code changes or before merging.
日本語の概要は準備中です。原文の説明を表示しています。
Processes all open Dependabot PRs sequentially — rebases if needed, analyzes for breaking changes and security issues, then merges or requests changes. Use when you want to handle pending Dependabot dependency updates.
日本語の概要は準備中です。原文の説明を表示しています。
Writing rules for the regelrecht docs site (docs/). Use when writing or editing prose under docs/ — RFCs, guides, component docs, concept pages, and the NL/EN landing copy. Keeps docs prose free of AI-generated tells and consistent with the site's government-technical register. Not for code, commit messages, or PR descriptions.
日本語の概要は準備中です。原文の説明を表示しています。
Provides context about the regelrecht Figma design system and helps with Figma-related tasks like component lookups and design comparisons. Use this skill proactively when: implementing UI components, looking up Figma node IDs, comparing code with Figma designs, downloading Figma assets, or working with design tokens. Activate automatically when user mentions Figma, design system, component styling, or asks about RR-Components.
日本語の概要は準備中です。原文の説明を表示しています。
Downloads Dutch official legal publications including national laws, local regulations, and implementation policies from government sources (wetten.overheid.nl, lokaleregelgeving.overheid.nl). Use this skill proactively when: user mentions downloading, fetching, or importing a Dutch law by name or BWB/CVDR identifier, when a source.regulation reference points to a law not in the corpus, or when user provides a wetten.overheid.nl URL. Activate automatically when user mentions a specific Dutch law name, BWB identifier (BWBR...), or CVDR identifier.
日本語の概要は準備中です。原文の説明を表示しています。