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/solar-breakevenWrote 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/solar-breakeven)<a href="https://agentmods.dev/rules/mohitagw15856/pm-claude-skills/solar-breakeven"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/solar-breakeven/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/solar-breakeven"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/solar-breakeven.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 | $0.00111 | $0.01330 |
| Opus 5 | $0.00056 | $0.00665 |
| Sonnet 5 | $0.00022 | $0.00266 |
| Haiku 4.5 | $0.00011 | $0.00133 |
Grade B, and why
solar-breakeven scanned grade B with 1 finding 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 8d 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.
Strips warnings and disclaimersmediumAnti-refusal
Omitting safety caveats hides risk from the user and is a common jailbreak preamble.
- [ ] Do not moralize either way — solar pencils brilliantly on some roofs and poorly on others; the table decides, not the vibe How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Solar Breakeven Skill
Every solar quote comes with a payback claim, and the claim always assumes the sunny version: full incentive eligibility, generous net metering forever, zero maintenance. This skill runs the honest model — net cost after verified incentives, offset that degrades ~0.5%/yr, electricity prices that inflate, and the inverter that dies around year 12 — and reports the breakeven year with its assumptions labeled. The biggest risk stays outside every model and gets named instead: net-metering policy is a regulatory decision that can change under you, and it moves paybacks by years.
What This Skill Produces
- The year-by-year table — savings, cumulative, vs-cost — from the script
- The breakeven year — and the net gain at the 25-year warranty horizon
- The quote check — the installer's payback claim vs. this model, with the assumption gaps named
- The not-modeled list — net-metering risk first, financing interest, roof interactions
Required Inputs
Ask for these if not provided:
- The quote — installed cost, claimed incentives (flagged verify-eligibility — incentives have income, tax-liability, and program caps), the claimed payback for comparison
- The bill — current monthly, and the offset % the installer claims (their number, tested; 80–95% is typical for a well-sized system)
- Ownership horizon — moving in 6 years changes everything; solar's value transfer at sale is uncertain and the model says so
- Financing — cash or loan; a loan adds interest the breakeven must also clear (run [the loan math] separately and add it — the script models the cash case)
Programmatic Helper
python3 scripts/solar_breakeven.py --cost 22000 --incentive 6600 --bill 190
python3 scripts/solar_breakeven.py --cost 22000 --incentive 6600 --bill 190 --offset 90 --json
Deterministic. Defaults: 85% offset, 3% electricity inflation, 0.5%/yr degradation, $2,000 inverter at year 12, 25-year horizon — every one overridable to match the quote's claims, which is how quotes get tested.
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.
- 8d ago First seen · 80 lines · 111 tokens per session scan B 5f6e964d3960
solar-breakeven is a cursor rule published in the GitHub repository mohitagw15856/pm-claude-skills (1,357 stars, last pushed today), licensed MIT. It adds 111 tokens to every session and 1,330 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it B with 1 finding (strips warnings and disclaimers). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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