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 dikamilo/dx-workflow --skill dx-domaingit clone --depth 1 https://github.com/dikamilo/dx-workflowWrote 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/dikamilo/dx-workflow/dx-domain)<a href="https://agentmods.dev/skills/dikamilo/dx-workflow/dx-domain"><img src="https://agentmods.dev/badge/skills/dikamilo/dx-workflow/dx-domain/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/dikamilo/dx-workflow/dx-domain"><img src="https://agentmods.dev/badge/skills/dikamilo/dx-workflow/dx-domain.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 | $0.00074 | $0.00674 |
| Opus 5.5 | $0.00030 | $0.00270 |
| Sonnet 5.5 | $0.00015 | $0.00135 |
| Haiku 4.5 | $0.00007 | $0.00067 |
Grade A, and why
dx-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 2mo 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 — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dx-domain
The active glossary discipline: challenge a term, sharpen it, and write it to foundation/glossary.md the moment it resolves. Merely reading the glossary for naming is a one-line habit any skill does — this skill is for changing the model, not consuming it. It fires on three triggers during any work:
- Clash — a term contradicts an existing glossary definition. Call it out at once: "The glossary defines 'cancellation' as X, but you seem to mean Y — which is it?"
- Fuzzy — a vague or overloaded term is in play. Propose one precise canonical term: "You said 'account' — is that the Customer or the User? Those are different things."
- Resolved — a term gets nailed down during framing/design/implementation. Capture it immediately, before the moment passes.
Guard. Write only foundation/glossary.md. If context/foundation/ doesn't exist, the project isn't scaffolded — say so and suggest /dx-init. Create glossary.md lazily on the first resolved term.
Sharpen before you write (invoke dx-references with knowledge-layer)
Load knowledge-layer for the glossary entry shape and the standards/lessons/glossary distinctions. Then force precision:
- Invent a concrete edge-case scenario that probes the boundary between two concepts and makes the user commit. Vague terms survive in the abstract and break on specifics.
- Cross-check the code. If what the user says contradicts what the code does, surface it: "Your code cancels whole Orders, but you just said partial cancellation exists — which is right?"
- Be opinionated. When several words mean one thing, pick the best and list the rest under
_Avoid_.
Write inline, glossary-only
The moment a term resolves, add or edit its entry in foundation/glossary.md using the knowledge-layer entry shape — definitional, domain-only, one or two sentences (what it IS, not what it does). Don't batch. Skip general programming concepts (timeouts, retries, error types) — only terms unique to this project's domain belong.
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.
- 2mo ago First seen · 38 lines · 74 tokens per session scan A f12419df5828
dx-domain is a skill published in the GitHub repository dikamilo/dx-workflow (8 stars, last pushed 23d ago), licensed MIT. It adds 74 tokens to every session and 674 once invoked, about $0.0003 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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relevance-coarse-filter
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recall-memory
Recall relevant long-term memories on demand. Given a topic or question, judges relevance from pre-loaded metadata, loads only relevant files, and returns a concise summary to the main agent.
catchup
Rebuild the human's lost context on a project from live state, in plain language: what needs them, what changed, what new words mean. Use when the human returns after a gap, says they can't follow the project anymore, asks what happened or what a term means, or before deciding what to do next when their mental model…