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 Eilodon/DPS-Superskills-MCP --skill domain-alignmentgit clone --depth 1 https://github.com/Eilodon/DPS-Superskills-MCPWrote 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/eilodon/dps-superskills-mcp/domain-alignment)<a href="https://agentmods.dev/skills/eilodon/dps-superskills-mcp/domain-alignment"><img src="https://agentmods.dev/badge/skills/eilodon/dps-superskills-mcp/domain-alignment/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/eilodon/dps-superskills-mcp/domain-alignment"><img src="https://agentmods.dev/badge/skills/eilodon/dps-superskills-mcp/domain-alignment.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 | $0.00063 | $0.00695 |
| Opus 5 | $0.00032 | $0.00347 |
| Sonnet 5 | $0.00013 | $0.00139 |
| Haiku 4.5 | $0.00006 | $0.00069 |
Grade A, and why
domain-alignment 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 9d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Domain-Alignment — Build the Project Context Layer
Register: TECHNIQUE Goal: Establish shared domain language and non-negotiable context before design begins. Constraints: Label every unsourced assumption as T4/ASSUMED. Do not let inferred vocabulary become verified truth without evidence.
Announce: "Using domain-alignment to establish CONTEXT.md before brainstorming."
Process
- Read
docs/superskills/CONTEXT.mdif it exists. If missing, create it frombootstrap-templates/CONTEXT.seed.mdor the scaffold below. - Capture or update:
- ubiquitous language and domain-specific meanings;
- actors, customers, operators, and external systems;
- business invariants and anti-requirements;
- sensitive data, PII, secrets, payment/compliance concerns;
- external dependencies and operational assumptions;
- forbidden assumptions the agent must not make;
- success/failure semantics;
- synonyms / alias map for
kb-query.
- For each entry, record a source when possible: user confirmation, code, ADR, spec, audit, production incident.
- Mark unsourced items as
T4/ASSUMEDwith a validation target. - Output a Context Alignment Summary before invoking
brainstorming.
CONTEXT.md Sections
# CONTEXT.md — Domain Knowledge
## Ubiquitous Language
- **term**: definition. Source: <user/code/ADR/spec/audit> Evidence: T1|T2|T3|T4
## Actors and Systems
- <actor/system>: role, boundary, data touched, operational responsibility.
## Business Invariants
- <invariant>: what must always remain true. Enforced by: <component/process>. Evidence: <tier/source>
## Sensitive Data and Trust Boundaries
- <data/boundary>: classification, allowed handling, forbidden handling.
## External Dependencies
- <dependency>: owner, failure modes, timeout/fallback expectations, volatility.
## Forbidden Assumptions
- <assumption agent must not make> — why.
## Success / Failure Semantics
- Success means: ...
- Failure means: ...
- Partial success means: ...
## Synonyms / Alias Map
- auth: authentication, token, session, credential, permission
- worker: async job, queue, background task, temporal
- release: deploy, rollout, enable traffic, cutover
- migration: schema change, backfill, data move
## Domain Gotchas
- Use `shared/gotcha-schema.md` for new entries.
What ships with it
1 file 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.
- 9d ago First seen · 90 lines · 63 tokens per session scan A 4b0c1dfb8bba
domain-alignment is a skill published in the GitHub repository Eilodon/DPS-Superskills-MCP (0 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 63 tokens to every session and 695 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…