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 nullhack/temple8 --skill interview-cross-cuttinggit clone --depth 1 https://github.com/nullhack/temple8Wrote 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/nullhack/temple8/interview-cross-cutting)<a href="https://agentmods.dev/skills/nullhack/temple8/interview-cross-cutting"><img src="https://agentmods.dev/badge/skills/nullhack/temple8/interview-cross-cutting/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/nullhack/temple8/interview-cross-cutting"><img src="https://agentmods.dev/badge/skills/nullhack/temple8/interview-cross-cutting.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 | $0.00029 | $0.00276 |
| Opus 5.5 | $0.00012 | $0.00110 |
| Sonnet 5.5 | $0.00006 | $0.00055 |
| Haiku 4.5 | $0.00003 | $0.00028 |
Grade A, and why
interview-cross-cutting 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 1mo 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.
What it actually says
Interview (Cross-cutting)
- Load [[requirements/interview-techniques]], [[architecture/quality-attributes]], [[methodology/simplicity-discipline]] — CIT, Laddering, CI Perspective Change, and the Active Listening protocol; the quality-attribute taxonomy to elicit; and the simplicity discipline.
- Read the running interview-notes; append the cross-cutting findings to it.
- Structure the domain into behaviour groups, bounded contexts, integration points, and lifecycle events. Probe each with CIT and Laddering; IF recall stalls THEN re-frame via CI Perspective Change. Capture the quality attributes stakeholders care about as one-line scenarios (stimulus → response), not bare words, per [[architecture/quality-attributes]].
- Ask the simplicity question for each behaviour group: "Is this group speculative — not grounded in a cited stakeholder need?" A group with no CIT incident and no laddered constraint grounding it is speculative per [[methodology/simplicity-discipline]]; flag it for drop at consolidation or ground it with a cited need now.
- Apply Active Listening L2: give a brief synthesis when transitioning between behaviour groups — confirms completeness, offers a recovery point.
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.
- 1mo ago First seen · 13 lines · 29 tokens per session scan A ca592a723ebe
interview-cross-cutting is a skill published in the GitHub repository nullhack/temple8 (11 stars, last pushed 29d ago), licensed MIT. It adds 29 tokens to every session and 276 once invoked, about $0.0001 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 2026-08-30.
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