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 skills add dorayo/orchestrix-skills --skill deploygit clone --depth 1 https://github.com/dorayo/orchestrix-skillsWrote 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/dorayo/orchestrix-skills/deploy)<a href="https://agentmods.dev/skills/dorayo/orchestrix-skills/deploy"><img src="https://agentmods.dev/badge/skills/dorayo/orchestrix-skills/deploy.svg" alt="Measured on agentmods" 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 | $0.00027 | $0.00915 |
| Opus 5 | $0.00014 | $0.00458 |
| Sonnet 5 | $0.00005 | $0.00183 |
| Haiku 4.5 | $0.00003 | $0.00092 |
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 4d 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deploy (Ship Accepted Work, With a Way Back)
The most dangerous skill in the graph. Everything here is designed around two facts: deploys are user-facing, and the only safe deploy is one you can undo.
Core principle: No rollback plan, no deploy. If you cannot state the exact command that undoes this deploy, you are not ready to run the one that does it.
Preconditions — ALL must hold, verify each now
- The work is accepted. Final acceptance happened; you are not deploying
to "see if it works" (that is
smoke-test's job, locally). - The tree is clean and tested.
git statusclean;run-testsgreen on the exact commit being shipped (fresh run, not remembered). - The deploy method is documented in
registry/deploy(or the project's own deploy config/scripts). Not documented → STOP and ask the human how this project ships. NEVER guess a deploy path — a guessed deploy against the wrong target is the worst failure this graph can produce. - The target is unambiguous. "Deploy" without a named target defaults to asking, not to production.
Process
- Write the rollback plan first. Record: the currently-live version identifier (commit/tag/deployment id) and the exact rollback command. Put both in the report BEFORE deploying.
- Inline human gate (this skill's accept). Present: target, version to ship, one-line change summary, rollback command. Deploy only on explicit sign-off. This gate cannot be batched or deferred.
- Deploy with the documented command. Capture the full output to
.orchestrate/verify/deploy-<target>.log. - Post-verify against the LIVE target. A real HTTP request (or the platform equivalent) to the deployed URL: correct status AND expected content, plus one core flow. The deploy tool saying "success" is step 3, not step 4.
- On post-verify failure: roll back immediately with the recorded command, re-verify the old version is live again, and report honestly. A failed deploy cleanly rolled back is a good outcome; a broken prod left up while you debug is not.
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.
- 4d ago Changed · +1 lines 5d58c68a6f6f
- 8d ago First seen · 86 lines · 27 tokens per session scan A e398d9f8fa65
deploy is a skill published in the GitHub repository dorayo/orchestrix-skills (2 stars, last pushed 6d ago), licensed MIT. It adds 27 tokens to every session and 915 once invoked, about $0.0001 per session on Opus 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.
Other skills, from other repositories
release-announcement
Write a release announcement — changelog, blog post, in-app note, or social post — that leads with user impact, names the audience, and includes upgrade/migration steps without filler.
multi-agent-release-manager
Cleans up the workspace, formats code, runs presubmit checks, and uploads CLs to Gerrit.
release-notes
Generate user-facing release notes from tickets, PRDs, or changelogs. Creates clear, engaging summaries organized by category (new features, improvements, fixes). Use when writing release notes, creating changelogs, announcing product updates, or summarizing what shipped.
pack-submit
Package one of this agent's own skills as a standalone community pack and submit it to the aeon registry as a PR.
changelog-composer
Generates structured changelogs and release notes from git history and PRs, classifying breaking changes, features, fixes, performance, docs. Triggers on: "generate changelog", "write release notes", "what changed since", "prepare release", "release notes for", "diff since tag".
updater_guide
Guidance for checking for and installing Row-Bot updates.