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 Future-CX/AI-Architecture-Toolkit --skill target-architecture-documentgit clone --depth 1 https://github.com/Future-CX/AI-Architecture-ToolkitWrote 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/future-cx/ai-architecture-toolkit/target-architecture-document)<a href="https://agentmods.dev/skills/future-cx/ai-architecture-toolkit/target-architecture-document"><img src="https://agentmods.dev/badge/skills/future-cx/ai-architecture-toolkit/target-architecture-document/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/future-cx/ai-architecture-toolkit/target-architecture-document"><img src="https://agentmods.dev/badge/skills/future-cx/ai-architecture-toolkit/target-architecture-document.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 | $0.00078 | $0.03960 |
| Opus 5.5 | $0.00031 | $0.01584 |
| Sonnet 5.5 | $0.00016 | $0.00792 |
| Haiku 4.5 | $0.00008 | $0.00396 |
Grade A, and why
target-architecture-document 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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Target Architecture Document
Quick Start
Assume the Enterprise Architect Agent role from agents/enterprise-architect.md: align initiatives to business capabilities, target architecture, standards, roadmaps, reuse opportunities, portfolio impact, cross-domain dependencies, and governance actions.
Ask the user which capabilities to include before drafting the target architecture document. If the user already named capabilities, confirm the list and ask for any missing domains, strategic drivers, constraints, or existing architecture inputs.
Before creating any output files, run a grill-me style clarification session using ../grill-me/SKILL.md. Ask one question at a time until the request, scope, capabilities, assumptions, constraints, terminology, and desired output are clear enough to avoid avoidable misunderstanding.
During that clarification session, use ../ubiquitous-language/SKILL.md whenever terms are vague, overloaded, conflicting, or important enough to become shared domain language. Create or update <private-lab-root>/GLOSSARY.md inline as terms are clarified; do not batch glossary updates until the end. Do not write the glossary inside this public toolkit repository when working with real company context.
While creating or updating target architecture section files, also update <private-lab-root>/GLOSSARY.md whenever the document introduces or changes domain terms, applications, or data objects. Treat glossary maintenance as part of writing each section, not as a final cleanup task. Use the glossary format and rules from ../ubiquitous-language/SKILL.md, including the dedicated ## Applications section and a ## Data objects section when data objects are identified.
After the clarification session, validate that <private-lab-root>/GLOSSARY.md was created or updated during the current run. If it was not created or updated, stop before generating target architecture files and ask the user to run the grill-me skill followed by the ubiquitous-language skill so the glossary is updated first.
What ships with it
14 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.
- README.md 3.6 KB
- templates/00-target-architecture-document-template.md 2.9 KB
- templates/01-preliminary-phase-template.md 1.1 KB
- templates/02-capability-overview-template.md 1.4 KB
- templates/03-phase-a-architecture-vision-template.md 1.2 KB
- templates/04-phase-b-business-architecture-template.md 606 B
- templates/05-phase-c-application-architecture-template.md 1.1 KB
- templates/06-phase-c-data-architecture-template.md 1.3 KB
- templates/07-phase-d-technology-architecture-template.md 692 B
- templates/08-phase-e-solution-building-blocks-template.md 654 B
- templates/09-gap-analysis-template.md 887 B
- templates/10-roadmap-themes-template.md 758 B
- templates/11-governance-actions-template.md 865 B
- templates/12-risks-and-open-questions-template.md 1.3 KB
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 Changed · +10 lines 928eb71a7c02
- 2mo ago First seen · 202 lines · 78 tokens per session scan A d1f256e5042d
target-architecture-document is a skill published in the GitHub repository Future-CX/AI-Architecture-Toolkit (8 stars, last pushed 18d ago), licensed MIT. It adds 78 tokens to every session and 3,960 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.
target-architecture-document compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| target-architecture-documentFuture-CX/AI-Architecture-Toolkit | Skill | 8 | 18d ago | MIT | A | 78 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |