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
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skillsnpx agentmods add rules/mohitagw15856/pm-claude-skills/pricing-calculatorWrote 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/pricing-calculator)<a href="https://agentmods.dev/rules/mohitagw15856/pm-claude-skills/pricing-calculator"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/pricing-calculator/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/pricing-calculator"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/pricing-calculator.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 | $0.00083 | $0.00814 |
| Opus 5 | $0.00042 | $0.00407 |
| Sonnet 5 | $0.00017 | $0.00163 |
| Haiku 4.5 | $0.00008 | $0.00081 |
Grade A, and why
pricing-calculator 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pricing Calculator Skill
Pricing decisions are usually made on gut and defended with a spreadsheet built under deadline. This
skill does the math cleanly: the margin on each tier, the break-even volume, and the revenue impact of
a price change under an explicit elasticity assumption — so a pricing proposal rests on numbers, with
the assumptions visible. (For the strategy — model, packaging, positioning — pair with
pricing-strategy; this runs the numbers.)
Required Inputs
Ask for these only if they aren't already provided:
- The scenario — set a tier price to a margin target, find break-even, or model a price change.
- Costs — variable cost per unit/seat, and fixed costs if you want break-even.
- Current price & volume (for a price-change model).
- Elasticity assumption — expected % volume change per % price change (state it; it's the key lever and it's an estimate).
Output Format
Pricing Model: [product / scenario]
1. The numbers (via the helper):
- Per tier: price, variable cost, gross margin %, contribution per unit.
- Break-even: units (or MRR) to cover fixed costs at this price/margin.
- Price-change impact: at +X% price with an assumed Y% volume change → net revenue and margin effect, vs. status quo.
| Scenario | Price | Volume | Revenue | Margin |
|---|---|---|---|---|
| Today | ||||
| Proposed |
2. The recommendation — what the math supports, and the volume drop you could absorb before the change loses money (the break-even elasticity — the most decision-useful number).
3. Assumptions — elasticity is an estimate; state it, and how sensitive the conclusion is to it.
Programmatic Helper
scripts/pricing.py (stdlib only) runs the margin / break-even / price-change math:
# in.json: {"current_price":50,"variable_cost":10,"current_volume":1000,"price_change_pct":0.2,"volume_change_pct":-0.1,"fixed_costs":20000}
python3 scripts/pricing.py in.json
python3 scripts/pricing.py in.json --json
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 · 72 lines · 83 tokens per session scan A dbba3f2adc35
pricing-calculator is a cursor rule published in the GitHub repository mohitagw15856/pm-claude-skills (1,352 stars, last pushed 3d ago), licensed MIT. It adds 83 tokens to every session and 814 once invoked, about $0.0004 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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