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/loan-covenant-review)<a href="https://agentmods.dev/rules/mohitagw15856/pm-claude-skills/loan-covenant-review"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/loan-covenant-review/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/loan-covenant-review"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/loan-covenant-review.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 | $0.00089 | $0.01148 |
| Opus 5 | $0.00044 | $0.00574 |
| Sonnet 5 | $0.00018 | $0.00230 |
| Haiku 4.5 | $0.00009 | $0.00115 |
Grade A, and why
loan-covenant-review 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 9d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Loan Covenant Review Skill
Covenants are the bank's smoke detectors — but only if someone reads them as trends, not snapshots. This skill runs the quarterly discipline: where is each covenant now, which direction is it moving, when does the trend cross the line, and what do we do before it does.
What This Skill Produces
- A covenant compliance table: required vs actual vs headroom, with trend
- Trajectory-to-breach analysis for any tightening covenant
- Waiver/amendment options with typical pricing implications
- Qualitative early-warning indicators checked
- A watch-list / risk-grade recommendation
Required Inputs
Ask for what's missing; with partial data, compute what's computable and mark the rest [awaiting financials]:
- Facility & covenant package — each covenant's definition, required level, test frequency, cure rights
- Current-quarter financials and at least 2–4 prior quarters for trend
- Compliance certificate figures if the borrower has submitted one
- Relationship context — prior waivers, recent management contact, sector conditions
Review Framework
1. Covenant table. For each covenant: required level, actual, headroom % = (actual − required) ÷ required (sign-adjusted so positive = compliant for both maximum-leverage and minimum-coverage covenants). Recompute actuals from the definitions in the agreement — borrower certificates use borrower-friendly add-backs; note any definitional divergence.
2. Headroom bands:
| Headroom | Status | Response |
|---|---|---|
| >20% | Comfortable | Routine monitoring |
| 10–20% | Monitor | Note trend; quarterly attention |
| <10% | Early warning | Trajectory analysis, proactive borrower dialogue |
| Breached | Breach | Reservation of rights, waiver/amendment track, risk-grade review |
3. Trajectory-to-breach. For anything under 20% or trending down 2+ quarters: extend the trend 2–4 quarters and state the projected breach quarter with the assumption ("on the last 3 quarters' EBITDA slope, leverage crosses 3.5x in Q2"). Label it a trend projection, not a forecast. Seasonality: compare year-on-year quarters before calling a trend.
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.
- 9d ago First seen · 76 lines · 89 tokens per session scan A a4ce535de44e
loan-covenant-review is a cursor rule published in the GitHub repository mohitagw15856/pm-claude-skills (1,357 stars, last pushed yesterday), licensed MIT. It adds 89 tokens to every session and 1,148 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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