Omnara is an open-source platform for running managed AI agents, handling their execution and state while developers choose the models, tools, machines, and user experience. Developers use it to build internal or customer-facing agent applications, while teams can interact with agents through its dashboard or Slack connector. The catalogue skill supports workflows built around Omnara.
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 omnara-ai/omnara --skill slack-coding-agentgit clone --depth 1 https://github.com/omnara-ai/omnaraWrote 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/omnara-ai/omnara/slack-coding-agent)<a href="https://agentmods.dev/skills/omnara-ai/omnara/slack-coding-agent"><img src="https://agentmods.dev/badge/skills/omnara-ai/omnara/slack-coding-agent/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/omnara-ai/omnara/slack-coding-agent"><img src="https://agentmods.dev/badge/skills/omnara-ai/omnara/slack-coding-agent.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 | $0.00068 | $0.02421 |
| Opus 5.5 | $0.00027 | $0.00968 |
| Sonnet 5.5 | $0.00014 | $0.00484 |
| Haiku 4.5 | $0.00007 | $0.00242 |
Grade A, and why
slack-coding-agent 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 3d 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 — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deploy the Slack Coding Agent
You are setting up an Omnara agent for the user from agent.yaml in this
folder. The goal: a coding agent the user's team can mention in Slack, in
Discord, or on a GitHub pull request, which works on one of their GitHub
repositories and opens pull requests, and which the user has watched answer
once.
The steps below are the usual path, with the exact commands. Skip anything that's already done (for example, the token and profile exist and the user only wants a different model), and follow the user's lead if they want a different order.
- Start from
agent.yamlas written. If the user wants something different (the instruction, tools, or model), change it and tell them what you changed. - If the user wants the agent to read their issue tracker (Linear, Jira, and
so on), add the tracker's MCP server in an
mcp:block, store its credential withnpx omnara secrets mcp-oauth(OAuth) or as agenericsecret (API key), and add a short instruction section on how to use it. Tell the user that an OAuth connection acts as whoever approves it, so its writes appear under that person's name. - If a command fails,
npx omnara <command> --helpand docs.omnara.com have the details. - Stop only where a step says to ask the user. Ask in a sentence or two of plain language, together with the next step's question if one comes right after, then end your turn and wait for the reply.
- Where a step gives a default, use it without asking and say in a line what you picked, so the user can change it.
- When a step needs a token, the user can paste it in the chat or add it to a
.envfile in the current directory, whichever they prefer; offer both. If they paste it, write it to.envyourself so the commands work as written.
The commands use the Omnara CLI (npx omnara); add --json to read IDs.
They're a reference, not a requirement: the Omnara MCP tools, the
REST API, and the SDK work
too, and the flags map directly to API fields.
What ships with it
2 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.
- 3d ago Changed · -154 lines 1453a2abccb6
- 8d ago Changed · +146 lines · +11 tokens per session c8ece343a125
- 9d ago Changed · +1 lines 9bfd4317df9e
- 14d ago First seen · 191 lines · 57 tokens per session scan A dd27a8c42718
slack-coding-agent is a skill published in the GitHub repository omnara-ai/omnara (2,928 stars, last pushed today), licensed Apache-2.0. It adds 68 tokens to every session and 2,421 once invoked, about $0.0003 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 2026-10-03.
Other skills, from other repositories
review-pr
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create-pr
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implement-issue
Implement a GitHub issue or GitLab issue and create a PR/MR.
pr-body
A tool that reviews all commits on the current branch and creates or updates a pull request title and description. A pull request is a proposed code change submitted for review.
respond-github
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contribute-spec-fix
Fix a broken OpenAPI spec in jentic-public-apis with an OpenAPI Overlay, validate it (spectral lint + idempotency check), and contribute it back via a PR to the community catalog. Falls back to applying the same overlay to the local Jentic registry if the user can't wait for maintainer approval, and closes the loop by…