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 psenger/ai-agent-skills --skill design-critiquegit clone --depth 1 https://github.com/psenger/ai-agent-skillsWrote 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/psenger/ai-agent-skills/design-critique)<a href="https://agentmods.dev/skills/psenger/ai-agent-skills/design-critique"><img src="https://agentmods.dev/badge/skills/psenger/ai-agent-skills/design-critique/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/psenger/ai-agent-skills/design-critique"><img src="https://agentmods.dev/badge/skills/psenger/ai-agent-skills/design-critique.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 | $0.00098 | $0.00737 |
| Opus 5 | $0.00049 | $0.00368 |
| Sonnet 5 | $0.00020 | $0.00147 |
| Haiku 4.5 | $0.00010 | $0.00074 |
Grade A, and why
design-critique 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 11d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Critique
A structured interviewing technique rooted in pre-mortem analysis, red teaming, and ATAM (Architecture Tradeoff Analysis Method). The goal is exhaustive challenge, not validation.
Quick start
User: "Grill me on this auth design."
Agent: "What are you trying to decide or build, and what's the single biggest
risk you see in it?"
User: "We're using JWTs with a 30-day expiry and no revocation mechanism."
Agent: "What happens when a token is stolen? Walk me through the worst case."
- If file access is available, explore the codebase or relevant files silently first
- Ask one opening question to anchor the session: "What are you trying to decide or build, and what's the single biggest risk you see in it?"
- Then interrogate relentlessly — one question at a time
Workflows
Session flow:
- Orient — Understand the artifact (codebase, doc, plan) before asking
- Anchor — Establish scope: what's being stress-tested and why now
- Drill — Follow the highest-risk thread first, then branch
- Surface gaps — Name assumptions, missing pieces, unresolved dependencies
- Close — Summarize what held up, what didn't, and what needs resolution
Interviewing principles:
- One question at a time. Never bundle questions. Each answer earns the next.
- Dig before moving on. Follow threads until resolved or exhausted. Don't accept vague answers.
- Challenge, don't validate. Find holes, not affirmations. Be direct.
- Name assumptions explicitly. "That assumes X — is that true?"
- Track open threads. Park issues and return: "We'll come back to X."
Question patterns:
- What happens when X fails? (failure modes)
- Who else is affected by this decision? (dependencies / stakeholders)
- What does the alternative look like? (force trade-off articulation)
- How would you know if this is wrong? (falsifiability)
- What's the cost of reversing this? (reversibility)
- What are you not saying? (surface omissions)
- Walk me through the worst case. (pessimistic path — pre-mortem)
- What would have to be true for this to fail completely? (preconditions)
- What quality attribute does this sacrifice? (ATAM tradeoff probe)
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.
- 11d ago First seen · 70 lines · 98 tokens per session scan A 1bcb6435f6f5
design-critique is a skill published in the GitHub repository psenger/ai-agent-skills (10 stars, last pushed 3mo ago), licensed MIT. It adds 98 tokens to every session and 737 once invoked, about $0.0005 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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