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 agentmods add skills/danielvm-git/bigpowers/model-domainnpx skills add danielvm-git/bigpowers --skill model-domaingit clone --depth 1 https://github.com/danielvm-git/bigpowersWhat 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 | $0.00060 | $0.02403 |
| Opus 5 | $0.00030 | $0.01202 |
| Sonnet 5 | $0.00012 | $0.00481 |
| Haiku 4.5 | $0.00006 | $0.00240 |
Grade A, and why
model-domain 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 2d 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 — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Model Domain
Distinct from define-language and deepen-architecture: Use this skill to stress-test a plan through a grilling interview that resolves domain model decisions and captures invariants. Use define-language to produce a canonical glossary of terms. Use deepen-architecture to find module-level refactoring opportunities in code.
Interview me relentlessly about every aspect of this plan until we reach a shared understanding. Walk down each branch of the design tree, resolving dependencies between decisions one-by-one. For each question, provide your recommended answer.
HARD GATE — Capture invariants (what MUST always be true) and state machines (what transitions are legal) for core entities. If these are fuzzy, design will fail.
Ask the questions one at a time, waiting for feedback on each question before continuing.
If a question can be answered by exploring the codebase, explore the codebase instead.
Domain awareness
During codebase exploration, also look for existing documentation:
File structure
Most repos have a single context:
/
├── specs/
│ ├── CONTEXT.md
│ └── adr/
│ ├── 0001-event-sourced-orders.md
│ └── 0002-postgres-for-write-model.md
└── src/
If a specs/tech-architecture/tech-stack.md exists, the repo has multiple contexts. The map points to where each one lives:
/
├── specs/
│ ├── CONTEXT-MAP.md
│ └── adr/ ← system-wide decisions
└── src/
├── ordering/
│ └── specs/
│ ├── CONTEXT.md
│ └── adr/ ← context-specific decisions
└── billing/
└── specs/
├── CONTEXT.md
└── adr/
Create files lazily — only when you have something to write. If no specs/tech-architecture/tech-stack.md exists, create it when the first term is resolved. If no specs/adr/ exists, create it when the first ADR is needed.
During the session
Challenge against the glossary
When the user uses a term that conflicts with the existing language in specs/tech-architecture/tech-stack.md, call it out immediately. "Your glossary defines 'cancellation' as X, but you seem to mean Y — which is it?"
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.
- 2d ago First seen · 233 lines · 60 tokens per session scan A 2eaa53b63fd2
model-domain is a skill published in the GitHub repository danielvm-git/bigpowers (156 stars, last pushed 25d ago), licensed MIT. It adds 60 tokens to every session and 2,403 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
shared/tech-stack-detection
检测项目技术栈的通用方法,通过分析配置文件识别语言、框架、工具链.
devops/changelog-generation
自动生成 CHANGELOG,基于 git 提交历史和 pipeline 产物信息,遵循 Conventional Commits 和 Keep a Changelog 规范.
boss
可审计的 agent 团队:BMAD 全自动研发流水线编排器。编排 9 个专业 Agent(PM、架构师、UI Designer、Tech Lead、Scrum Master、Frontend、Backend、QA、DevOps)从需求到部署,每一步都有事件溯源 + 不可绕过门禁 + 确定性 eval——可验证测试真跑、门禁真过。支持单环节切片命令(/boss:plan /review /qa /ship)与无 CLI 纯 Markdown 降级。 Triggers: 'boss mode', '/boss', '全自动开发', '从需求到部署', '帮我做一个', 'build this', 'ship it', '全流程'…
debloat
Compress an artifact that has accreted into bloat — padding, over-qualification, fused sentences, walls of enumeration, adjacent restatement — down to its load-bearing density, meaning preserved. Use when prose is correct and current but has grown verbose or patched-over and you want it tight without a full rewrite.
bmad-dev-story
Execute story implementation following a context filled story spec file. Use when the user says "dev this story [story file]" or "implement the next story in the sprint plan".
bmad-validate-prd
Validate a PRD against standards. Use when the user says "validate this PRD" or "run PRD validation".