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/career-ladder-map)<a href="https://agentmods.dev/rules/mohitagw15856/pm-claude-skills/career-ladder-map"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/career-ladder-map/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/career-ladder-map"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/career-ladder-map.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 | $0.00092 | $0.00815 |
| Opus 5 | $0.00046 | $0.00407 |
| Sonnet 5 | $0.00018 | $0.00163 |
| Haiku 4.5 | $0.00009 | $0.00081 |
Grade A, and why
career-ladder-map 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.
Career Ladder Map Skill
"How do I get to the next level?" usually gets a vague answer. This skill makes it concrete: lay your
current demonstrated competencies next to the target level's, find the real gaps, and turn each into
a specific project that will generate the evidence a promotion-packet
needs. A plan, not a pep talk.
Required Inputs
Ask for these only if they aren't already provided:
- Current level → target level, and the ladder/rubric for both (the competencies each expects).
- Your current evidence — what you've demonstrated and where (a
brag-dochelps). - Constraints — your role's scope, time, and what opportunities are realistically available.
Output Format
Career Ladder Map — [name], [current] → [target]
1. Side-by-side — each competency at current vs. target, with your honest status:
| Competency | Target-level bar | Where I am now | Gap |
|---|---|---|---|
| e.g. Scope of influence | multi-team | strong within my team | 🟡 partial |
Status: 🟢 already demonstrating · 🟡 partial / inconsistent · 🔴 not yet.
2. The real gaps — the 2–4 competencies (🔴/🟡) that actually stand between you and the level. Be honest — a flattering map wastes quarters.
3. Evidence-generating plan — for each gap, a specific project that would create the proof, plus how you'd get the opportunity (ask your manager, volunteer, scope it yourself):
| Gap | Project that proves it | Opportunity / ask | By when |
|---|
4. Sequencing — what to focus on this quarter vs. next (you can't close every gap at once; pick the highest-signal ones).
5. Manager alignment — what to confirm with your manager so you're calibrated on the same bar (the #1 cause of surprise "not yet"s).
Quality Checks
- Both levels are mapped against the actual rubric, not a generic guess
- Your current status is honest (🟢/🟡/🔴), not aspirational
- Each gap has a specific project that generates evidence — not "get better at X"
- The plan names how you'll get the opportunity, not just the goal
- It's sequenced (this quarter vs. next), and includes a manager-calibration step
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 · 92 tokens per session scan A 1b6af67dd118
career-ladder-map is a cursor rule published in the GitHub repository mohitagw15856/pm-claude-skills (1,352 stars, last pushed 3d ago), licensed MIT. It adds 92 tokens to every session and 815 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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