Borrowing it
Nothing to install: this file belongs to jovandyaz/knowtis-app. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/jovandyaz/knowtis-app/main/.agents/skills/deploying/SKILL.mdgit clone --depth 1 https://github.com/jovandyaz/knowtis-appWrote 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/skills/jovandyaz/knowtis-app/deploying)<a href="https://agentmods.dev/skills/jovandyaz/knowtis-app/deploying"><img src="https://agentmods.dev/badge/skills/jovandyaz/knowtis-app/deploying/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/skills/jovandyaz/knowtis-app/deploying"><img src="https://agentmods.dev/badge/skills/jovandyaz/knowtis-app/deploying.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 | $0.00103 | $0.01534 |
| Opus 5.5 | $0.00041 | $0.00614 |
| Sonnet 5.5 | $0.00021 | $0.00307 |
| Haiku 4.5 | $0.00010 | $0.00153 |
Grade A, and why
deploying 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 1mo 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Diagnosing CI and deploying Knowtis
All deploy targets are CI-driven from GitHub Actions. Neither Vercel's nor Railway's Git integrations are active. Use references/ci-pipeline.md for affected checks and references/deployment.md for runtime topology and configuration.
Mental model
push to main → affected lint/typecheck/test/build + migration drift check
├─ notes affected → Vercel notes project
├─ backoffice affected → Vercel backoffice project
├─ api affected → railway-deploy.sh (waits for terminal status)
└─ mcp affected → railway-deploy.sh (if RAILWAY_MCP_SERVICE_ID is set)
The facts that resolve most deploy confusion
- Vercel never deploys directly from a push — Git deployments are disabled. Check the affected app and its corresponding
deploy-frontendordeploy-backofficejob. railway upuploads the snapshot, then Railway can skip its build viawatchPatterns. Explicitrailway up --ciexits 0 when build logs say “No changed files matched patterns”; a detached deployment may later becomeSKIPPED, observable by polling its exact ID. Compare that state with the Nx affected set and never report it as a successful deployment. The API patterns currently omitpackages/**, so package-only transitive changes require particular scrutiny.- Production migrations run in Railway's release phase. CI applies migrations only to its test database and separately checks generated migration drift.
- CLI return is not sufficient evidence in agent automation. A non-TTY invocation can return after upload, explicit
--cihas a watch-pattern early-success path, and--detachonly queues work. Userailway up --detach --json, capture that exact deployment ID, and poll it toSUCCESS; a healthy endpoint alone may still be the previous deployment. - Healthcheck gates differ by service: API uses
/api/v1/health/pingwith 120 seconds; MCP uses/healthwith 60 seconds. Check the matching service configuration when a build succeeds but never becomes live. - Manual escape hatch: direct Railway deploys bypass CI and are for explicit emergencies only. Prefer the repository's gated deploy script; otherwise use
railway up --detach --json, poll the returned deployment ID toSUCCESS, then verify the service health endpoint before reporting completion.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 78 lines · 103 tokens per session scan A 1e79b3fa1a44
deploying is a skill published in the GitHub repository jovandyaz/knowtis-app (4 stars, last pushed yesterday), licensed MIT. It adds 103 tokens to every session and 1,534 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-31.
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