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.
npx skills add mohitagw15856/pm-claude-skills --skill credit-memogit 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/skills/mohitagw15856/pm-claude-skills/credit-memo)<a href="https://agentmods.dev/skills/mohitagw15856/pm-claude-skills/credit-memo"><img src="https://agentmods.dev/badge/skills/mohitagw15856/pm-claude-skills/credit-memo/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/skills/mohitagw15856/pm-claude-skills/credit-memo"><img src="https://agentmods.dev/badge/skills/mohitagw15856/pm-claude-skills/credit-memo.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 | $0.01285 |
| Opus 5.5 | $0.00033 | $0.00514 |
| Sonnet 5.5 | $0.00017 | $0.00257 |
| Haiku 4.5 | $0.00008 | $0.00128 |
Grade A, and why
credit-memo 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 2d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Credit Memo Skill
A credit memo has one job: let a committee member who has never met the borrower decide whether the bank gets its money back. This skill writes that document — the story, the structure, the numbers, and the risks — with the discipline that every risk carries a mitigant or an explicit acceptance, and every rating has a stated rationale.
What This Skill Produces
- A borrower story (business, ownership, management, why they need the money)
- A facility structure table (amount, tenor, pricing, security, guarantees, covenants)
- Repayment sources: primary, secondary, tertiary — each tested
- A financial-ratio spread with trends and covenant headroom
- Risk factors, each paired with a mitigant or an explicit acceptance
- Risk-rating rationale and a clear recommendation
Required Inputs
Ask for what's missing; from a thin brief, draft with every inferred figure labelled [assumed — verify]:
- Borrower — business, ownership, years operating, management
- Request — facility type, amount, tenor, purpose, proposed pricing and security
- Financials — 2–3 years of revenue, EBITDA, debt, interest expense, working capital; projections if available
- Existing exposure and relationship history
- Proposed covenants and the institution's rating scale, if available
Credit Framework
Borrower story. What the business does, who owns and runs it, and why they need the money now — growth, refinance, working-capital cycle, or distress dressed as growth. The purpose must match the tenor and structure (don't fund long-term assets with short-term debt).
Repayment sources — the core of the memo:
- Primary: operating cash flow. Test with DSCR = cash available for debt service ÷ total debt service. Common framing: ≥1.25x is conventional comfort; 1.0–1.25x is tight and needs a covenant fence; <1.0x means the deal relies on the secondary source — say so in those words.
- Secondary: collateral. State value, valuation date and basis, advance rate, and realistic liquidation value under stress — not appraisal value.
- Tertiary: guarantor/sponsor support. Verified net worth and liquidity, and the honest note that guarantees are a negotiating position, not cash.
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.
- 2d ago First seen · 83 lines · 83 tokens per session scan A 0abf21c55720
credit-memo is a skill published in the GitHub repository mohitagw15856/pm-claude-skills (1,449 stars, last pushed today), licensed MIT. It adds 83 tokens to every session and 1,285 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-10-12.
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