model skill
Produces domain-reference kits including glossaries and divergence pages to map bounded contexts and surface decidable questions for stakeholders.
- GitHub stars
- 155
- Files
- 46
- Last commit
- Nov 10, 2026
- License
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What does the model skill do?
model produces domain-reference kits including glossaries and divergence pages to map bounded contexts and surface decidable questions for stakeholders.
Summary generated from the skill's SKILL.md.
About the model skill
Mapping bounded contexts and generating decision queues for stakeholders is what this skill accomplishes. It serves architects and developers during the initial information architecture phase, acting as the first producer in an architecture flow that runs upstream of feature design. By loading specific instruction files and shared producer guards, the agent produces a domain-reference kit consisting of a glossary and a divergences or traps page.
Users trigger the process by requesting a domain model, a glossary, or a bounded context analysis. The tool relies on a strict seven-phase workflow that includes requirements harvesting, code archaeology, and verification passes. It is designed to surface precise, role-tagged questions that humans must resolve, rather than simply producing documentation. It operates in both greenfield modes for new contexts and brownfield modes for updating existing kits, ensuring that any contradicted facts are propagated throughout the session. This skill is not intended for writing feature design documents or performing behavioral code reviews.
What an agent can do with it
- 1Establish a new domain glossaryAn architect can use this to create the first set of documentation for a greenfield bounded context.
- 2Identify critical stakeholder questionsDevelopers can generate a list of precise, decidable questions that require human intervention to move design forward.
- 3Update existing domain documentationWhen working in an established codebase, the agent can perform delta updates to existing reference kits.
- 4Map domain concepts to codeThe tool helps bridge the gap between high-level domain terminology and the actual implementation found in the source code.
Written from the skill's SKILL.md. Every use case is checked against a quote from it.
How to install the model skill
Each command copies the skill folder into the client's skills directory. Restart the client or start a new session to load it.Install the model skill in Plugin
/plugin marketplace add serpro69/claude-toolbox /plugin install kk@claude-toolbox
Install the model skill in Claude Code
~/.claude/skills/model/SKILL.md
$ npx degit serpro69/claude-toolbox/klaude-plugin/skills/model ~/.claude/skills/modelInstall the model skill in Claude Code (project)
.claude/skills/model/SKILL.md
$ npx degit serpro69/claude-toolbox/klaude-plugin/skills/model .claude/skills/modelInstall the model skill in Codex
~/.agents/skills/model/SKILL.md
$ npx degit serpro69/claude-toolbox/klaude-plugin/skills/model ~/.agents/skills/modelInstall the model skill in Gemini CLI
~/.gemini/skills/model/SKILL.md
$ npx degit serpro69/claude-toolbox/klaude-plugin/skills/model ~/.gemini/skills/modelInstall the model skill in Claude.ai
npx degit serpro69/claude-toolbox/klaude-plugin/skills/model model && zip -r model.zip model # claude.ai → Customize → Skills → + → Create skill → Upload a skill → model.zip
Automated checks
Ran Nov 14, 2026Full report →Not verified yet. A skill needs a score of 80, no serious finding, and enough data for us to check. How checks work · What to fix for more points
- Source repository linked and reachableserpro69/claude-toolbox/klaude-plugin/skills/model is public and reachablegithub.com/serpro69/claude-toolbox/tree/HEAD/klaude-plugin/s ↗Pass
- Open source license (OSI)No licenseFinding
- Commit or release in the last yearLast commit 2026-11-10github.com/serpro69/claude-toolbox/commits ↗Pass
- No download-and-run or credential theft in scriptsNo scripts in the skill folderPass
- No hidden instructions in SKILL.mdNo override phrases, safeguard switches, credential requests or hidden charactersgithub.com/serpro69/claude-toolbox/blob/HEAD/klaude-plugin/s ↗Pass
- Pre-approved tools are scopedNo pre-approved tools; the agent asks before using onegithub.com/serpro69/claude-toolbox/blob/HEAD/klaude-plugin/s ↗Pass
- SKILL.md follows the Agent Skills formatValid name and description; says when to use it; 43 linesgithub.com/serpro69/claude-toolbox/blob/HEAD/klaude-plugin/s ↗Pass
SKILL.md
View on GitHubDomain Modelling — the steady-state kit
Goal: produce a provenance-clean domain-reference kit and, above all, a decision queue of precise, role-tagged questions a human can close. The queue is the primary output — artifact count and model sophistication are explicitly not the metric.
/kk:model is the first producer of the architecture flow: it runs at information-architecture altitude (what the domain's concepts are, where they bind to code, and which questions about them only a human can close), upstream of feature /kk:design and never called by it. It writes files and interacts with you mid-flow — it is a main-session skill, not a read-only reviewer.
Conventions
- Capy knowledge base — read shared-capy-knowledge-protocol.md; searched at intake (
kk:arch-decisions,kk:project-conventions), indexed at close. - Shared producer guards — four workflow guards, each citing the field failure it prevents. Load all four before acting:
- shared-requirements-harvesting.md — quote the real asks before modelling (F1).
- shared-open-question-pass.md — verification asks new questions, not just re-confirms (F4).
- shared-fact-flip-propagation.md — a contradicted fact is fixed everywhere in-session (F2).
- shared-contact-ratio-guard.md — at N:0 artifacts-to-contacts, the next step is a conversation (F5).
- Profiles are not consulted —
/kk:modelis language-agnostic in M2; archaeology reads code directly. Profile enrichment is deferred (design §8).
Workflow
Mandatory order — instructions before subject matter. The flow is strictly sequential. Do not read code to model it, draft any kit page, or engage the domain beyond a mode-detecting directory/keyword scan until every instruction file is loaded: this SKILL.md, the process file model-process.md, the reading method archaeology.md, the output contract kit-contract.md, all four shared guards above, and the shared capy protocol. This ordering is load-bearing: with domain code in context before the contracts load, the model emits plausible terms and skips the methodology that makes them trustworthy.
- Load instructions. Read model-process.md (the detailed seven-phase workflow), archaeology.md, kit-contract.md, all four shared guards — shared-requirements-harvesting.md, shared-open-question-pass.md, shared-fact-flip-propagation.md, shared-contact-ratio-guard.md — and shared-capy-knowledge-protocol.md. Minimal early scope — a directory listing or a keyword scan of the request — is permitted only to drive mode detection.
- Execute the seven phases per model-process.md:
- Scope intake — establish the bounded context, the forcing question (the feature/ticket that bounds what is worth modelling), and the mode (greenfield: no kit exists → produce the two pages; brownfield: an existing kit is read in full first and all changes are deltas, status markers never flipped unilaterally). Run the capy knowledge search.
- Requirements-harvesting gate (guard, F1) — read every linked ticket + one hop; quote the actual asks into working notes before any modelling.
- Archaeology — read code state → time → invariants per archaeology.md; two-clock discipline (code-clock facts verifiable, intent stays
proposed). - Draft the kit per kit-contract.md — glossary page + divergences/traps page (+ conventions index if the home has none).
- Verify — at least one confirm-pass plus at least one open-question pass (guard, F4).
- Self-check — conventions-bind-author lint: the produced pages obey the kit's own declared conventions.
- Surface & close — present the decision queue (each RQ precise, decidable, role-tagged); apply the contact-ratio guard (F5); in brownfield, fact-flip propagation (F2) on any contradicted recorded fact; index non-obvious rationale to
kk:arch-decisions.
Required Outputs
- The two durable kit pages (glossary + traps) for the context, provenance-clean, per kit-contract.md (+ conventions index if the home lacked one).
- The decision queue — precise, decidable, role-tagged questions — presented inline and appended to the active feature's
docs/feat/wip/<feature>/design.mdunder an Open Questions heading when that directory exists. - Contact-ratio guard applied; brownfield fact-flips propagated across the workspace.
- Non-obvious modelling rationale indexed to
kk:arch-decisions.
Files in this skill
46model skill questions
How do I install the model skill in Claude Code?
Run npx degit serpro69/claude-toolbox/klaude-plugin/skills/model ~/.claude/skills/model. Claude Code loads skills from ~/.claude/skills (all projects) or .claude/skills (one project) and uses a skill when its description matches the task.
Which clients can use the model skill?
Any client that reads the Agent Skills format: Claude Code, Codex, Gemini CLI and claude.ai (upload as a ZIP). Scripts in the skill run only where the client allows code execution.
What is the primary output of the model skill?
The primary output is a decision queue consisting of precise, role-tagged questions for humans to close, rather than just artifact count.
When should I use the model skill?
Use it for domain modelling, information architecture, building glossaries, or mapping domain concepts to code bindings.
Is this skill used for reviewing code behavior?
No, it is specifically not intended for behavioral code review or writing feature design documents.