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.
npx skills add DDS-Solutions/AI-TadPole-OS --skill domain-modelinggit clone --depth 1 https://github.com/DDS-Solutions/AI-TadPole-OSWrote 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.
[](https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/domain-modeling)<a href="https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/domain-modeling"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/domain-modeling/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.
<a href="https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/domain-modeling"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/domain-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00038 | $0.01230 |
| Opus 5.5 | $0.00015 | $0.00492 |
| Sonnet 5.5 | $0.00008 | $0.00246 |
| Haiku 4.5 | $0.00004 | $0.00123 |
Grade A, and why
domain-modeling 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.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
[!IMPORTANT] AI Context & Knowledge Heritage
- Subsystem: Agent Skills Registry / domain-modeling
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Ubiquitous language drift, semantic naming mismatches across stack boundaries, unrecorded domain entity mutations.
- Observability: Traceability via
execution/parity_guard.py([SKILL])
Domain Modeling & Ubiquitous Language Protocol
Purpose: Maintain absolute conceptual fidelity and ubiquitous nomenclature across all repository tiers—from low-level Rust kernel structs and SQLite migrations to OpenAPI contracts and frontend React stores.
📚 Progressive Disclosure & L3 Reference Index
Read REQUIRED core modeling principles below; consult deep L3 Reference Guides on demand:
| L3 Resource | Scope & Purpose | Trigger / When to Load |
|---|---|---|
domain_modeling_guide.md |
Bounded contexts taxonomy, entity vs value object classification, glossary upkeep SOP | Designing new entities or mapping cross-tier contracts |
domain_glossary_validator.py |
Deterministic ubiquitous language & prohibited alias audit tool | Pre-commit validation of terminology parity |
docs/GLOSSARY.md |
Authoritative Tadpole OS Technical Specifications & Glossary | Canonical definition of hubs, structs, and constants |
documentation-templates |
Architecture Decision Record (ADR) blueprints | Formalizing structural decisions under docs/adr/ |
🏛️ 1. Core Principles of Ubiquitous Language
- One Name, One Meaning: If an autonomous objective is designated as a
Mission, it must be namedMissionacross all layers:- Rust Struct:
pub struct Mission(server-rs/src/agent/types/mission.rs) - OpenAPI Contract:
components.schemas.Mission(docs/openapi.yaml) - TypeScript Type:
export interface Mission(src/types/mission.ts) - SQLite Table:
CREATE TABLE missions(server-rs/migrations/)
- Rust Struct:
- Explicit Bounded Contexts: Never leak internal execution abstractions into unrelated domains (e.g. keep UI visual pulse physics decoupled from cryptographic vault state).
- Immutability of Value Objects: Value objects (e.g.
MicroQuota,Ed25519Signature) must be immutable and replaceable, with zero independent lifecycles.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago Changed · +39 lines · +6 tokens per session c58c6d94ae77
- 2mo ago First seen · 42 lines · 32 tokens per session scan A 876152f9f6db
domain-modeling is a skill published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed today), licensed MIT. It adds 38 tokens to every session and 1,230 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 2026-08-31.
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