PM Skills is a collection of plain-Markdown instructions that teach AI assistants structured methods for handling professional, personal, and life-admin tasks. People use it with Claude, ChatGPT, Gemini, Cursor, Codex, and other supported agents for work such as writing product requirements, reviewing documents, or planning difficult situations.
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.
git clone --depth 1 https://github.com/mohitagw15856/pm-claude-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/rules/mohitagw15856/pm-claude-skills/informational-interview-prep)<a href="https://agentmods.dev/rules/mohitagw15856/pm-claude-skills/informational-interview-prep"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/informational-interview-prep/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/rules/mohitagw15856/pm-claude-skills/informational-interview-prep"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/informational-interview-prep.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 | $0.00122 | $0.01076 |
| Opus 5 | $0.00061 | $0.00538 |
| Sonnet 5 | $0.00024 | $0.00215 |
| Haiku 4.5 | $0.00012 | $0.00108 |
Grade A, and why
informational-interview-prep 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 6d 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Informational-Interview Prep
An informational interview is one of the best career tools — a short, low-pressure conversation to learn about a field, role, or company from someone doing it. But done wrong (vague questions, or angling for a job) it wastes their time and yours. This preps the whole thing: the ask, the right questions for your goal, how to run it, and a follow-up that turns a chat into a relationship.
What This Skill Produces
- The outreach ask — a short, specific, low-friction request for a brief chat (not a job)
- A focused question set — tuned to your goal (exploring a field, breaking in, learning about a company/role), from their path to practical advice
- Conversation flow — how to open, keep it their-story-centered, and use the time well
- What not to do — the mistakes (asking for a job, dominating, being unprepared) that sour these
- A follow-up — a thank-you and a way to keep the connection warm, including any offered next step
- Prep notes — what to research about them beforehand
Required Inputs
Ask for these if not provided:
- Your goal — exploring a field, trying to break in, targeting a company/role, or broad learning
- The person — who they are, their role, and your connection (if any)
- Your background — enough to tailor relevant questions
- The format — call, coffee, video, and how long
- Where you are — early exploration vs. active job search (changes tone)
Framework: Learn, Don't Pitch
- Ask small and specific. Request a brief (15–20 min) chat to learn, name why them, and make it easy to grant — never open with a job ask.
- Prepare targeted questions. Match questions to your goal: their path and day-to-day, how they got in, what they wish they'd known, and specific advice for your situation — not things you could Google.
- Center their story. Let them talk, listen actively, and go deeper on what's useful; you're there to learn, not to perform.
- Don't ask for a job. The fastest way to sour an informational is to turn it into a pitch — build the relationship; opportunities follow later.
- Follow up well. Thank them specifically, act on any advice/intro they offered, and keep the door open for a light future touch.
- Do your homework. Research them enough to ask informed questions and not waste the time.
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.
- 6d ago First seen · 72 lines · 122 tokens per session scan A a0b8a8d11109
informational-interview-prep is a cursor rule published in the GitHub repository mohitagw15856/pm-claude-skills (1,352 stars, last pushed 2d ago), licensed MIT. It adds 122 tokens to every session and 1,076 once invoked, about $0.0006 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 2026-09-03.
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