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 ariadoss/superskills --skill human-architect-mindsetgit clone --depth 1 https://github.com/ariadoss/superskillsWrote 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/ariadoss/superskills/human-architect-mindset)<a href="https://agentmods.dev/skills/ariadoss/superskills/human-architect-mindset"><img src="https://agentmods.dev/badge/skills/ariadoss/superskills/human-architect-mindset/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/ariadoss/superskills/human-architect-mindset"><img src="https://agentmods.dev/badge/skills/ariadoss/superskills/human-architect-mindset.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 | $0.00055 | $0.00839 |
| Opus 5 | $0.00028 | $0.00419 |
| Sonnet 5 | $0.00011 | $0.00168 |
| Haiku 4.5 | $0.00006 | $0.00084 |
Grade A, and why
human-architect-mindset 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Human Architect Mindset
Framework for systematic architectural thinking that emphasizes the capabilities humans bring that AI cannot replace.
Foundation: Loyalty
The human capacity to maintain architectural commitments despite optimization pressure or trending alternatives. AI optimizes for the current prompt; architects optimize for the whole system over time.
"The 'correct' technical solution is often unshippable. Architects navigate the gap between idealized examples and messy reality."
Five Pillars
1. Domain Modeling
Understanding actual problem spaces — not just technical implementations.
Key questions:
- What is this system actually doing for its users?
- What are the domain entities and their relationships?
- Where are the invariants that must never be violated?
- What terms do domain experts use, and are we using them too?
2. Systems Thinking
Recognizing component interactions and failure modes before they happen.
Key questions:
- How do components fail, and what cascades from that failure?
- Where are the hidden coupling points?
- What changes slowly? What changes fast? Are they separated?
- What happens at scale? At 10x? At 100x?
3. Constraint Navigation
Managing technical, organizational, and political realities.
Key questions:
- What's the real budget (time, money, people)?
- What legacy systems must we integrate with?
- What regulatory or compliance requirements apply?
- What can we change, and what must we work around?
4. AI-Aware Decomposition
Breaking problems into AI-solvable chunks with clear boundaries.
Key questions:
- Which sub-problems have clear inputs, outputs, and success criteria?
- Where do we need human judgment vs. AI execution?
- How do we validate AI-generated components?
- What context does each AI task need to succeed?
5. AI-First Development
Evaluating modern tools, edge computing, and agentic patterns.
Key questions:
- Does AI solve this better than traditional code?
- What's the failure mode when AI gets it wrong?
- How do we maintain quality in AI-generated systems?
- What's the human review and override strategy?
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 · 118 lines · 55 tokens per session scan A 63d5ca06d683
human-architect-mindset is a skill published in the GitHub repository ariadoss/superskills (9 stars, last pushed 2d ago), licensed MIT. It adds 55 tokens to every session and 839 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.
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