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 agentmods add skills/borhen68/skillengine/interview-menpx skills add borhen68/SkillEngine --skill interview-megit clone --depth 1 https://github.com/borhen68/SkillEngineWhat 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 | $0.00108 | $0.03382 |
| Opus 5 | $0.00054 | $0.01691 |
| Sonnet 5 | $0.00022 | $0.00676 |
| Haiku 4.5 | $0.00011 | $0.00338 |
Grade A, and why
interview-me 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 2d 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.
This is a copy
88% identical to interview-me — 60 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interview Me
Overview
The most expensive bug in software isn't a null pointer or a race condition — it's building the wrong thing. Users ask for "a dashboard" not because they need a dashboard, but because they need to know something, and a dashboard is the first solution that comes to mind. They say "make it faster" without a number because they haven't defined what "fast enough" means.
The interview contract: Before any plan, spec, or code, ask one question at a time until you can predict the user's answer. Surface assumptions explicitly. Don't silently fill gaps with your own defaults — the gaps are where the real requirements live.
Real-world impact: Research shows that 50% of software features are never used or rarely used. The root cause isn't bad implementation — it's misunderstood requirements. A 10-minute structured interview prevents weeks of building something nobody wanted.
When to Use
Apply this skill when:
- The ask is missing at least one of: who the user is, why they want it, what success looks like, what the binding constraint is
- The request is conventional rather than specific ("build me X", "make it faster") and you can't unpack the convention without guessing
- You're tempted to start with assumptions you haven't surfaced
- The user hasn't said which value they're optimizing for when two reasonable ones are in tension (simplicity vs. flexibility, cost vs. speed)
- The user explicitly invokes: "interview me", "grill me", "before we start, are we sure?", "stress-test my thinking"
When NOT to use:
- The ask is unambiguous and self-contained ("rename this variable", "fix this typo")
- The user has explicitly asked for speed over verification
- Pure information requests ("how does X work?", "what does this code do?")
- Mechanical operations (renames, formats, file moves)
- You already have ≥95% confidence; re-read the stop condition below before assuming you don't
Loading Constraints
This skill needs a live, responsive user. Do not invoke in non-interactive contexts like CI pipelines, scheduled runs, /loop, or autonomous-loop. If you're in one of those and the ask is
underspecified, flag that as a blocker for the user instead of guessing.
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.
- 2d ago First seen · 254 lines · 108 tokens per session scan A 2fe02a815f26
interview-me is a skill published in the GitHub repository borhen68/SkillEngine (17 stars, last pushed 2mo ago), licensed MIT. It adds 108 tokens to every session and 3,382 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to interview-me, differing in 60 lines, and is treated as a copy.
Other skills, from other repositories
code-review-and-quality
执行多维度代码审查。用于合并任何变更之前；用于审查自己、其他 agent 或人类编写的代码；用于在代码进入主分支前从多个维度评估代码质量。.
doubt-driven-development
在每个非平凡决策成立前，用全新上下文进行对抗式审查。当正确性比速度更重要、处理不熟悉代码、风险较高（生产、安全敏感逻辑、不可逆操作），或任何自信输出现在验证比之后调试更便宜时使用。.
test-driven-development
用测试驱动开发。用于实现任何逻辑、修复任何 bug，或改变任何行为。用于需要证明代码能工作、收到 bug 报告，或即将修改现有功能时。.
ci-cd-and-automation
自动化 CI/CD pipeline 设置。用于设置或修改构建和部署 pipeline 时；用于需要自动化质量门禁、在 CI 中配置 test runners，或建立部署策略时。.
code-simplification
为清晰度简化代码。用于在不改变行为的前提下重构代码以提升清晰度；用于代码能运行但比应有状态更难阅读、维护或扩展时；用于审查已累积不必要复杂度的代码时。.
context-engineering
优化 agent 上下文设置。当开始新会话、agent 输出质量下降、在任务之间切换，或需要为项目配置规则文件和上下文时使用。.