zscripts-token-savers/ELEVATOR_PITCH.txt
KellyMichels 827ad41ea6 docs(security): security notes, and a twin for every root .md
Defers to the org policy for how to report and covers what is particular to a
repository that is a sanitised mirror: the most valuable report here is not a
crash, it is something REAL that should not be here - a credential, an internal
hostname, an operator path, an identifier naming a private project. Mail those
rather than filing an issue, because a public issue about a leaked secret
publishes it a second time.

It also says what the automated check is and is not. The sanitisation suite is
a DENYLIST: it proves the absence of known patterns, not the absence of
secrets. Green tests are why a human report is still worth sending.

And the ordinary warning for what these actually are - automation that
archives a tree, uploads it, rebuilds containers and restarts services. Read
before running, nothing here is a sandbox, the config is yours to replace.

TWINS ARE NOW DISCOVERED, NOT LISTED. PAIRS was hand-kept and two files had
outgrown it: ELEVATOR_PITCH.md and TOKEN_SAVINGS.md had no twin at all. Adding
a document and remembering to add it to a list are two acts, and the second is
the one that gets skipped.

The Pester test had the same shape in reverse - it scraped PAIRS out of the
generator's source, so it could only prove the list was self-consistent and a
document nobody listed was invisible to it. It now asks the REPOSITORY what
markdown it has. Proven by deleting SECURITY.txt and watching two tests fail.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-09-11 22:40:03 -05:00

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Evomedia.net Token Savers — https://github.com/evomedia-net/evo.zscripts
Created by Kelly Michels · dev@evomedia.net
Licensed under the MIT License. See LICENSE.
Elevator Pitch
==============
The one-liner
-------------
AI coding agents waste thousands of tokens a day on infrastructure orchestration. Token Savers gives you one-word commands to run those parts yourself — so your agent spends tokens on code, not on SSH.
The 30-second version
---------------------
Every time your AI coding agent runs your infrastructure for you — a deploy, a restart, a health check — the full output lands in its context window: Docker layers, SSH banners, health-check chatter. We measured it per run — at a typical active-day cadence that's ~26,500 tokens of pure script output through the agent, and a single full Docker rebuild adds ~35,000 more. The dollars are small; the context is not — every line of infrastructure noise crowds out the code your agent is supposed to be reasoning about.
Token Savers collapses the infrastructure side into short, one-word commands you run yourself: zdeploy myapp, zrepair myapp, zstart myapp. Describe each project once in zconfig.json — where it lives, what kind it is, where it deploys — and every command just knows. You run the deploy; your agent edits the code. You run the health check; your agent reads the result and fixes whatever's wrong.
Measured per-run; ~26,500 tokens of script output per active development day at a typical cadence — kept out of your agent's context entirely when you run the commands yourself. See TOKEN_SAVINGS.md (TOKEN_SAVINGS.md) for the per-script measurements and method.
Why it's different
------------------
- Built around the AI-agent workflow. The commands are short on purpose — fewer keystrokes for you, fewer tokens when an agent invokes them. But the real saving is the operations you don't hand to the agent at all.
- The project name IS the command. zstart blog, zdeploy api, zbackup store — no flags to memorize, no switches to wire up.
- One config file, zero secrets in git. Server IP, SSH key, paths, and project definitions live in one gitignored JSON. Clone it anywhere, drop in your config, go.
- It verifies the deploy actually landed. Not "did the server return 200" (a stale cache does that too) — it checks that the build number went live, so you know the code you just shipped is the code that's running.
Who it's for
------------
Solo developers and small teams running several containerized web apps (Python, Vite, Next.js, plus edge proxies and stock Docker images) on a single VPS or EC2 box, from a Windows dev machine, over SSH — and using AI coding agents to write the code.
The tagline
-----------
Fewer keystrokes. Fewer tokens. One config to rule your fleet.