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/one-on-one-prep)<a href="https://agentmods.dev/rules/mohitagw15856/pm-claude-skills/one-on-one-prep"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/one-on-one-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/one-on-one-prep"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/one-on-one-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 | $0.00106 | $0.00854 |
| Opus 5 | $0.00053 | $0.00427 |
| Sonnet 5 | $0.00021 | $0.00171 |
| Haiku 4.5 | $0.00011 | $0.00085 |
Grade A, and why
one-on-one-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 7d 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
One-on-One Prep Skill
The 1:1 is the highest-leverage meeting you have — and it's wasted when it defaults to status (which belongs in writing). This skill preps an agenda built around the outcomes you want: the decisions to unblock, the asks to make, the feedback to exchange, and the career threads to keep warm — so 30 minutes moves things instead of just reporting them.
Required Inputs
Ask for these only if they aren't already provided:
- Direction — prepping for a 1:1 with your manager (managing up) or with your report (managing down)? The agenda differs.
- What's on your mind — blockers, decisions, tensions, wins, career topics (rough notes are fine).
- Anything time-sensitive or any hard thing you've been avoiding raising.
- Last 1:1's follow-ups, if any.
Output Format
1:1 Prep — with [name], [date]
1. Top topics (most important first) — for each: the topic, the outcome you want, and the framing. Lead with what needs a decision or unblock, not updates.
| Topic | Outcome I want | How I'll frame it |
|---|
2. Asks — explicit requests (a decision, air cover, a connection, time). Naming the ask is the point of the meeting.
3. Status — kept brief — 2–3 bullets of what they genuinely need to know; link the rest. Don't let this eat the meeting.
4. Feedback (both ways) — feedback to give (specific, kind, actionable) and a prompt to ask for feedback on yourself.
5. Growth / career — the longer-game thread to keep warm (a stretch goal, a development area, a promotion track).
6. Follow-ups — from last time, and what you'll commit to from this one.
Direction note: managing up → lead with decisions you need and asks; surface risks early; make it easy to help you. Managing down → lead with their agenda and growth, listen more than you talk, end with clear next steps.
Quality Checks
- Topics lead with a desired outcome, not a status recap
- At least one explicit ask is named
- Status is condensed to a few bullets (the rest written/linked)
- Feedback flows both ways, and is specific and actionable
- A growth/career thread is kept on the agenda, not just the urgent stuff
- The agenda is tuned to direction (managing up vs. down)
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.
- 7d ago First seen · 64 lines · 106 tokens per session scan A 94daff2e9c88
one-on-one-prep is a cursor rule published in the GitHub repository mohitagw15856/pm-claude-skills (1,352 stars, last pushed 3d ago), licensed MIT. It adds 106 tokens to every session and 854 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 2026-09-03.
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