Datapack Builder
w95/awesome-claude-corporate-skills
Build professional financial services data packs from various sources including CIMs, offering memorandums, SEC filings, web search, or MCP servers.
Cash runway as a distribution, not a number — Monte Carlo simulated.
Install Runway Monte Carlo
$ npx skills add mohitagw15856/pm-claude-skills --skill runway-monte-carlo -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mohitagw15856/pm-claude-skills runway-monte-carlo --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/runway-monte-carlo .claude/skills/runway-monte-carlo && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "runway-monte-carlo" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/runway-monte-carlo into .claude/skills/runway-monte-carlo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "runway-monte-carlo", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/runway-monte-carloType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mohitagw15856/pm-claude-skills --skill runway-monte-carlo -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mohitagw15856/pm-claude-skills runway-monte-carlo --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/runway-monte-carlo .agents/skills/runway-monte-carlo && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "runway-monte-carlo" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/runway-monte-carlo into .agents/skills/runway-monte-carlo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "runway-monte-carlo", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mohitagw15856/pm-claude-skills --skill runway-monte-carlo -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mohitagw15856/pm-claude-skills runway-monte-carlo --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/runway-monte-carlo .cursor/skills/runway-monte-carlo && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "runway-monte-carlo" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/runway-monte-carlo into .cursor/skills/runway-monte-carlo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "runway-monte-carlo", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mohitagw15856/pm-claude-skills.git --path skills/runway-monte-carlo--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mohitagw15856/pm-claude-skills --skill runway-monte-carlo -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mohitagw15856/pm-claude-skills runway-monte-carlo --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/runway-monte-carlo .gemini/skills/runway-monte-carlo && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "runway-monte-carlo" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/runway-monte-carlo into .gemini/skills/runway-monte-carlo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "runway-monte-carlo", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mohitagw15856/pm-claude-skills runway-monte-carloInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mohitagw15856/pm-claude-skills --skill runway-monte-carlo -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/runway-monte-carlo .github/skills/runway-monte-carlo && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "runway-monte-carlo" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/runway-monte-carlo into .github/skills/runway-monte-carlo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "runway-monte-carlo", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mohitagw15856/pm-claude-skills --skill runway-monte-carlo -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mohitagw15856/pm-claude-skills runway-monte-carlo --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/runway-monte-carlo .opencode/skills/runway-monte-carlo && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "runway-monte-carlo" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/runway-monte-carlo into .opencode/skills/runway-monte-carlo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "runway-monte-carlo", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
runway-monte-carlo- GitHub stars
- 1.4k
- Token cost
- ~973 tokens
- SKILL.md length
- 474 words
- Files
- 2 (incl. scripts)
- Skills in repo
- 1,348
- Repo updated
- First seen
- Licence
- MIT
At a glance
Cash runway as a distribution, not a number — Monte Carlo simulated.
- Works in 4 steps: The distribution — P10 (unlucky), P50… → The death curve — % of simulated paths… → The decision line — the one that… → …
- Someone asks how long their cash lasts
- SKILL.md covers Required Inputs, Output Format, Programmatic Helper and Quality Checks, plus 2 more sections
- Runs Python scripts from its folder; calls python3
What it does
Runway Monte Carlo is an agent skill from mohitagw15856/pm-claude-skills. Cash runway as a distribution, not a number — Monte Carlo simulated. Use when someone asks how long their cash lasts, when to start fundraising, or how burn/revenue volatility changes their runway; especially when the naive cash÷burn answer is driving a decision. Produces P10/P50/P90 runway, month-by-month death probabilities, and a real .xlsx with editable assumptions and a live naive-runway formula — via the bundled zero-dependency simulator.
Its SKILL.md is about 970 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/runway_sim.py`).
It sits in Business, Finance & HR, covering Excel spreadsheets and Fundraising and pitch decks. It works with Microsoft Excel. The repository describes itself as: 1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in… The licence is MIT.
When your agent uses it
- Someone asks how long their cash lasts
- To start fundraising
- How burn/revenue volatility changes their runway
- Especially when the naive cash÷burn answer is driving a decision
Example prompts
- “/runway-monte-carlo”
Requirements
- Python 3
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- The distribution — P10 (unlucky), P50 (median), P90 (lucky) runway in months, the survival probability at the horizon, and the naive…
- The death curve — % of simulated paths out of cash by each month; the months where it steepens are the danger window.
- The decision line — the one that matters: raise while P10 exceeds your fundraise time (6-9 months for most), not P50. Say explicitly when…
- Stated model limits — normal noise (no fat tails), no seasonality, no fundraise events modelled. If their reality has lumpy enterprise…
What it can do on your machine
Read from SKILL.md and the folder at commit 1cbf1f0. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Runway Monte Carlo loads about 973 tokens when it runs. Until then it costs about 117 tokens; SKILL.md has 474 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from mohitagw15856/pm-claude-skills at commit 1cbf1f0, republished under its MIT licence (© mohitagw15856). 474 words, ~973 tokens.
Download SKILL.mdSave it as
.claude/skills/runway-monte-carlo/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- runway-monte-carlo
- description
- Cash runway as a distribution, not a number — Monte Carlo simulated. Use when someone asks how long their cash lasts, when to start fundraising, or how burn/revenue volatility changes their runway; especially when the naive cash÷burn answer is driving a decision. Produces P10/P50/P90 runway, month-by-month death probabilities, and a real .xlsx with editable assumptions and a live naive-runway formula — via the bundled zero-dependency simulator.
Runway Monte Carlo
"Cash divided by burn" is one path through a fan of thousands. Real burn wobbles, revenue growth compounds or doesn't, and the difference between the median path and the unlucky-decile path is the difference between a calm raise and a bridge round. This skill runs the simulation — thousands of paths, actual random draws by the bundled script — and reports runway the way it actually behaves: as percentiles.
Required Inputs
- Cash today and monthly gross burn — the two non-negotiables.
- Monthly revenue and monthly revenue growth (optional — zero for pre-revenue).
- Volatility (optional, defaults: burn σ 10%, growth σ 25% of the growth rate) — from the requester's history if they have it, defaults if not, stated either way.
- Horizon (default 36 months) and simulation count (default 5,000).
Output Format
- The distribution — P10 (unlucky), P50 (median), P90 (lucky) runway in months, the survival probability at the horizon, and the naive cash÷net-burn number alongside for contrast.
- The death curve — % of simulated paths out of cash by each month; the months where it steepens are the danger window.
- The decision line — the one that matters: raise while P10 exceeds your fundraise time (6-9 months for most), not P50. Say explicitly when the P10 clock crosses that line.
- Stated model limits — normal noise (no fat tails), no seasonality, no fundraise events modelled. If their reality has lumpy enterprise revenue, say the P10 is optimistic.
Programmatic Helper
This skill ships scripts/runway_sim.py — zero dependencies, deterministic with --seed:
python3 scripts/runway_sim.py run runway.xlsx --cash 2400000 --burn 210000 --burn-vol 0.12 \
--revenue 60000 --rev-growth 0.05 --rev-vol 0.3It prints the percentiles (naive=16.0mo P10=19 P50=>36 P90=>36 survive(36mo)=56.8%) and writes an .xlsx with an Assumptions sheet (editable cash/burn/revenue cells, live naive-runway formula) and a Death curve sheet. Requires a code-execution environment.
Show full SKILL.md (197 more words)Show less
Quality Checks
- The simulation actually ran (script output quoted) — percentiles were not eyeballed
- P10 is the headline, with the raise-timing implication stated in months and dates
- The naive cash÷burn number appears next to the distribution so the requester sees what volatility does to it
- Assumptions and their sources (history vs default) are listed — defaults are labelled as defaults
- Model limits stated: no fat tails, no seasonality, no modelled fundraise
Anti-Patterns
- Do not report only the median — the median is the number that feels fine right up until the P10 path happens to you
- Do not silently invent volatility — a made-up σ changes the answer more than the burn does; label defaults
- Do not model the hoped-for fundraise inside the simulation — runway exists to time the raise, not assume it
- Do not extend the horizon to make survival look better — report the horizon with the number
- Do not present 56.8% survival as "about half" in one place and "likely fine" in another — one number, one interpretation, used consistently
Example Trigger Phrases
- "How long does our cash really last?"
- "When should we start fundraising?"
- "Simulate our runway with volatile revenue."
- "Give me runway as a range, not one number."
© mohitagw15856, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file (scripts) in skills/runway-monte-carlo of mohitagw15856/pm-claude-skills.
- SKILL.md
- scripts/runway_sim.py
Open the folder on GitHubat commit 1cbf1f0
Compare with similar skills
Runway Monte Carlo next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Runway Monte Carlo this skillmohitagw15856/pm-claude-skills | 1.4k | — | ~973 | Automated safety check: Pass | MIT | |
| Datapack Builderw95/awesome-claude-corporate-skills | 244 | 1 repos | ~6k | Automated safety check: Pass | MIT | |
| Cn Ib Diligence WorkpaperQiushenZou/cn-investment-banking-skills | 102 | — | ~1.4k | Automated safety check: Pass | Apache-2.0 | |
| Officecli Commonly TemplatesTeam-Commonly/commonly | 1.4k | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| Investment Due Diligence Reportxiaoyuge886/aigc | 198 | — | ~2.1k | Automated safety check: Pass | MIT | |
| Mx Finance Datahiboys/ExploreFinance | 365 | — | ~518 | Automated safety check: Pass | None |
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Related
Works with
Categories
Questions about Runway Monte Carlo
What does Runway Monte Carlo do?
Cash runway as a distribution, not a number — Monte Carlo simulated. Runway Monte Carlo is an agent skill from mohitagw15856/pm-claude-skills. Cash runway as a distribution, not a number — Monte Carlo simulated.
When should I use Runway Monte Carlo?
Runway Monte Carlo fits situations like: someone asks how long their cash lasts; to start fundraising; how burn/revenue volatility changes their runway; especially when the naive cash÷burn answer is driving a decision.
How do I install Runway Monte Carlo in Claude Code?
Run `npx skills add mohitagw15856/pm-claude-skills --skill runway-monte-carlo -a claude-code`. Or copy the skill folder (skills/runway-monte-carlo in mohitagw15856/pm-claude-skills) into .claude/skills/runway-monte-carlo in your project. Claude Code loads it when a task matches its description.
How do I install Runway Monte Carlo in Codex?
Run `npx skills add mohitagw15856/pm-claude-skills --skill runway-monte-carlo -a codex`. Or copy the skill folder (skills/runway-monte-carlo in mohitagw15856/pm-claude-skills) into .agents/skills/runway-monte-carlo in your project. Codex loads it when a task matches its description.
Can I use Runway Monte Carlo in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mohitagw15856/pm-claude-skills --skill runway-monte-carlo -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/runway-monte-carlo, .gemini/skills/runway-monte-carlo, .github/skills/runway-monte-carlo and .opencode/skills/runway-monte-carlo in your project.
What does Runway Monte Carlo need to run?
Going by SKILL.md and its folder, Runway Monte Carlo needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does Runway Monte Carlo access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Runway Monte Carlo safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Runway Monte Carlo use?
Runway Monte Carlo is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Runway Monte Carlo use?
About 973 tokens (SKILL.md is roughly 3.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Runway Monte Carlo?
Skills that share tags, products or a category with Runway Monte Carlo: Datapack Builder (w95/awesome-claude-corporate-skills, 244 stars), Cn Ib Diligence Workpaper (QiushenZou/cn-investment-banking-skills, 102 stars), Officecli Commonly Templates (Team-Commonly/commonly, 1.4k stars) and Investment Due Diligence Report (xiaoyuge886/aigc, 198 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Runway Monte Carlo?
mohitagw15856 (a GitHub user) maintains it in mohitagw15856/pm-claude-skills, which has 1,434 GitHub stars. The repository holds 1,348 skills in this directory. The repository was last updated on October 9, 2026.
Source: mohitagw15856/pm-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.