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/aksheyw/career-command-center-template/interviewnpx skills add aksheyw/career-command-center-template --skill interviewgit clone --depth 1 https://github.com/aksheyw/career-command-center-templateWrote 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/aksheyw/career-command-center-template/interview)<a href="https://agentmods.dev/skills/aksheyw/career-command-center-template/interview"><img src="https://agentmods.dev/badge/skills/aksheyw/career-command-center-template/interview.svg" alt="Measured on agentmods" 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 | $0.00023 | $0.00865 |
| Opus 5 | $0.00012 | $0.00432 |
| Sonnet 5 | $0.00005 | $0.00173 |
| Haiku 4.5 | $0.00002 | $0.00086 |
Grade A, and why
interview 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 5d 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are preparing the user for a director-level PM interview. The user has provided a company name and optionally a role title.
STEP 1: Read required files
Read all of these:
${CLAUDE_PLUGIN_ROOT}/references/YOUR_PROFILE.md— the user's verified background${CLAUDE_PLUGIN_ROOT}/skills/resume-customizer/SKILL.md— company-type strategies, interview angles${CLAUDE_PLUGIN_ROOT}/skills/resume-customizer/references/star-stories.md— all the user's STAR stories${CLAUDE_PLUGIN_ROOT}/skills/resume-customizer/references/story-bank-index.md— cross-indexed story selection by company type${CLAUDE_PLUGIN_ROOT}/skills/resume-customizer/references/interview-prep.md— frameworks, questions, pitch${CLAUDE_PLUGIN_ROOT}/skills/resume-customizer/references/career-tools.md— 90-day plans, salary strategy
STEP 2: Identify company type
Based on the company name, determine:
- Company Type: AI / Consumer Scale / Enterprise / B2B / Fintech / Telco
- Interview focus: what they will care most about
- Fit level: how strong the match is
STEP 3: Output complete prep pack
2-MINUTE PITCH (company-customized)
Adapt the standard pitch template from interview-prep.md to reference the specific company in the closing line. Pull the user's actual achievements from YOUR_PROFILE.md.
TOP 4 STAR STORIES FOR THIS COMPANY
Use story-bank-index.md to select stories by company type. Cross-reference with star-stories.md for full story details.
For each story, provide:
- Story name
- Why it is relevant to this specific company
- The 60-second version (crisp retelling)
- Watch out for (common stumbles in telling this story)
Also include one failure story and why it works for this company.
QUESTIONS THEY WILL LIKELY ASK
10 specific questions based on the JD / company type, with guidance on how to answer each:
- 3 behavioral (use STAR stories)
- 3 product / strategy (use company-type interview angle from
SKILL.md) - 2 leadership (team building, stakeholder management)
- 1 failure (use one of the user's failure stories)
- 1 "why this company" (prepare specific answer)
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.
- 5d ago First seen · 93 lines · 23 tokens per session scan A 6c775694afd9
interview is a skill published in the GitHub repository aksheyw/career-command-center-template (1 stars, last pushed 6d ago), licensed MIT. It adds 23 tokens to every session and 865 once invoked, about $0.0001 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.
Other skills, from other repositories
interview-coach
Use when the user has an upcoming interview, received an interview invitation, or wants to prepare for a specific role at a specific company.
mock-interviewer
Run a realistic, pressure-tested mock interview for a specific role, one question at a time, with honest feedback at the end. Use when the user wants interview practice, a mock interview, or to rehearse answers for an upcoming interview.
pm-interview-grill
产品经理（PM）高强度面试拷问与即时教练技能。模拟 Google/Meta/字节/腾讯等顶尖科技公司 PM 面试官，支持四大经典题型与真实简历项目深度挖掘，并在每轮回答后提供即时优点拆解、逻辑扣分点与 CIRCLES/STAR/AARM 框架标准示范。当用户提出“PM面试”、“产品经理面试”、“PM烤问”、“产品经理模拟面试”、“PM烤问我”或需要 PM 面试指导时触发。.
upskill
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ai-dev-jobs-mcp
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principal-agent
当用户选择职业/组织/合作方式、困惑「为什么大公司磨洋工/小公司拼命」「该不该自己干」时调用。 核心理念: 委托人(主人)会把事做好, 代理人会为自己利益优化; 收益与创造价值绑得越紧, 越像委托人; 别让媒体洗脑你需要代理人。 不适用于: 具体薪酬谈判数字、组织架构设计细节。 Triggers: 激励/代理/主人/打工 vs 创业/利益绑定/principal/agent/incentive.