Show HN: Captan – Open-Source Cap Table Management CLI
Show HN (score: 5)Description
Instead of juggling spreadsheets or paying for expensive SaaS cap table solutions, Captan stores everything in a simple JSON file that you can version-control in Git.
It supports:
- Stakeholders (founders, employees, investors)
- Security classes (Common, Preferred, Option Pool)
- Share issuances
- Option grants with vesting schedules (monthly, cliff)
- SAFEs (record + simulate conversion at a priced round)
- Cap table math (Outstanding vs Fully Diluted)
- CSV/JSON exports
- Audit log ("the ship’s log")
Overall a JSON in git will offer better auditability and version control than most commercial solutions out there.
Modeling different scenarios is super easy, just create a git branch and model whatever you need.
Quick taste:
---------------------------------------
npm install -g captan
$captan init --name "Acme, Inc." --pool-pct 20
$captan enlist stakeholder --name "Alice Founder"
$captan issue --security sc_common --holder sh_alice --qty 5000000
$captan chart
Example output:
Captan — Cap Table (as of today)
Name Outstanding %
Alice Founder 5000000 100.00%
Totals
Issued equity: 5000000
Vested options: 0
Outstanding total: 5000000
Fully diluted total: 7000000
---------------------------------------
Why I built it: early-stage founders (myself included) often don’t need Carta or Pulley yet — just a clean, hackable way to track ownership. I wanted something transparent, developer-friendly, and Git-native.
Repo: https://github.com/acossta/captan
npm: https://www.npmjs.com/package/captan
I’d love feedback on what features would make this more useful to you?
Thanks!
More from Show
Show HN: KeyEnv – CLI-first secrets manager for dev teams (Rust)
Show HN: KeyEnv – CLI-first secrets manager for dev teams (Rust) Hi HN,<p>I built KeyEnv because I was tired of the "can you Slack me the Stripe key?" workflow.<p><pre><code> The problem: My team's secrets lived in a mix of Slack DMs, shared Google Docs, and .env files that definitely weren't in .gitignore at some point. Enterprise tools like Vault required more DevOps time than we had. Doppler was close but felt heavier than we needed. What KeyEnv does: keyenv init # link project keyenv pull # sync secrets to local .env keyenv run -- npm start # inject secrets, run command That's basically it. Secrets are encrypted client-side (AES-256-GCM) before leaving your machine. Zero-knowledge architecture—we can't read your secrets even if we wanted to. Technical details: - Single Rust binary, no runtime dependencies - Works offline (cached secrets) - RBAC for teams (owner/admin/member/viewer) - Service tokens for CI/CD - Full audit trail Honest tradeoffs: - SaaS only, no self-hosted option - Fewer integrations than Doppler - If you need dynamic secrets or PKI, use Vault Pricing: Free tier (3 projects, 100 secrets), $12/user/month for teams. Would love feedback on the CLI UX and any rough edges. Happy to answer questions about the architecture. </code></pre> <a href="https://www.keyenv.dev" rel="nofollow">https://www.keyenv.dev</a>
Show HN: WebTerm – Browser-based terminal emulator
Show HN: WebTerm – Browser-based terminal emulator
Show HN: WebGPU React Renderer Using Vello
Show HN: WebGPU React Renderer Using Vello I've built a package to use Raph Levien's Vello as a blazing fast 2D renderer for React on WebGPU. It uses WASM to hook into the Rust code
Show HN: On the edge of Apple Silicon memory speeds
Show HN: On the edge of Apple Silicon memory speeds I have developed open source CLI-tool for Apple Silicon macOS. It measures memory speeds in different ways and also latency. It can achieve up to 96-97% efficiency on read speed on M4 base what is advertised as 120GB/s. All memory operations are in assembly.<p>I would really appreciate for results on different CPU's how benchmark works on those. I have been able to test this on M1 and M4.<p>command : 'memory_benchmark -non-cacheable -count 5 -output results.JSON' (close all applications before running)<p>This will generate JSON file where you find sections copy_gb_s, read_gb_s and write_gb_s statics.<p>Example M4 with 10 loops: "copy_gb_s": { "statistics": { "average": 106.65421233311835, "max": 106.70240696071005, "median": 106.65069297260811, "min": 106.6336774994254, "p90": 106.66606919223108, "p95": 106.68423807647056, "p99": 106.69877318386216, "stddev": 0.01930653530818627 }, "values": [ 106.70240696071005, 106.66203166240008, 106.64410802226159, 106.65831409449595, 106.64148106986977, 106.6482935780762, 106.63974821679058, 106.65896986001393, 106.6336774994254, 106.65309236714002 ] }, "read_gb_s": { "statistics": { "average": 115.83111228356601, "max": 116.11098114619033, "median": 115.84480882265643, "min": 115.56959026587722, "p90": 115.99667266786554, "p95": 116.05382690702793, "p99": 116.09955029835784, "stddev": 0.1768243167963439 }, "values": [ 115.79154681380165, 115.56959026587722, 115.60574235736468, 115.72112860271632, 115.72147129262802, 115.89807083151123, 115.95527337086908, 115.95334642887214, 115.98397172582945, 116.11098114619033 ] }, "write_gb_s": { "statistics": { "average": 65.55966046805113, "max": 65.59040040480241, "median": 65.55933583741347, "min": 65.50911885624045, "p90": 65.5840272860955, "p95": 65.58721384544896, "p99": 65.58976309293172, "stddev": 0.02388146120866979 },<p>Patterns benchmark also shows bit more of memory speeds. command: 'memory_benchmark -patterns -non-cacheable -count 5 -output patterns.JSON'<p>Example M4 from 100 loops: "sequential_forward": { "bandwidth": { "read_gb_s": { "statistics": { "average": 116.38363691482549, "max": 116.61212708384109, "median": 116.41264548721367, "min": 115.449510036971, "p90": 116.54143114134801, "p95": 116.57314206456576, "p99": 116.60095068065866, "stddev": 0.17026641589059727 } } } }<p>"strided_4096": { "bandwidth": { "read_gb_s": { "statistics": { "average": 26.460392735220456, "max": 27.7722419653915, "median": 26.457051473208285, "min": 25.519925729459107, "p90": 27.105171215736604, "p95": 27.190715938337473, "p99": 27.360449534513144, "stddev": 0.4730857335572576 } } } }<p>"random": { "bandwidth": { "read_gb_s": { "statistics": { "average": 26.71367836895143, "max": 26.966820487564327, "median": 26.69907406197067, "min": 26.49374804466308, "p90": 26.845236287807374, "p95": 26.882004355057887, "p99": 26.95742242818151, "stddev": 0.09600564296001704 } } } }<p>Thank you for reading :)
No other tools from this source yet.