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 agentmods add commands/ds1/boilerplate.md/deploygit clone --depth 1 https://github.com/ds1/boilerplate.mdWhat 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 | $0.00000 | $0.00249 |
| Opus 5 | $0.00000 | $0.00125 |
| Sonnet 5 | $0.00000 | $0.00050 |
| Haiku 4.5 | $0.00000 | $0.00025 |
Grade A, and why
deploy 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.
What it actually says
Deploy to Production
Deploy the current project to production.
Steps
-
Detect the deployment platform by checking for:
vercel.jsonor.vercel/-> Vercel (npx vercel --prod)netlify.toml-> NetlifyDockerfile-> Docker-basedpackage.jsonscripts fordeploy- Fall back to asking the user
-
Pre-deploy checks:
- Run
npm run build(or equivalent) to verify the build succeeds - Check for uncommitted changes — warn if working tree is dirty
- Show the current branch and last commit
- Run
-
Confirm with the user: "Ready to deploy [branch] to production via [platform]. Proceed?"
-
Run the deployment command.
-
If the project has a docs site (Docusaurus in
docs/), ask if docs should be deployed too. -
After deployment, update STATUS.md with the deployment timestamp.
By @ds1 — boilerplate.md
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 · 30 lines · 0 tokens per session scan A 398b3ec3e04a
deploy is a command published in the GitHub repository ds1/boilerplate.md (5 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 249 tokens. 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 2026-08-31.
Other commands, from other repositories
create-pr
Create a pull request following the official template.
review-code
Read ALL memory bank code rules + best practices, check the files that changed, and APPLY fixes so they adhere. The active counterpart to /scan (which is read-only). Use after an AI session, before commit, to make changed files compliant.
learn
Command "learn" from chohra-med/expo_boilerplate, covering command: learn — the learning loop (feedback → rules), when to run it, invocation, the loop (6 steps) and 1 — capture.
migrate
Command "migrate" from chohra-med/expo_boilerplate, covering invocation, steps and rule.
audit
Command "audit" from chohra-med/expo_boilerplate, covering invocation, checks and output.
build
Command "build" from chohra-med/expo_boilerplate, covering command: build — run the sdd pipeline over tasks.md, invocation, per-task cycle, gates (constitution) and output.