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Linkedin Signal Agent
Deploy or update the LinkedIn Signal Agent on Omnara, an agent that scrapes LinkedIn posts (keyword search plus tracked company and profile feeds) and delivers a daily digest. Use when the user asks to deploy, set up, update, or remove the LinkedIn signal agent.
Archived 2026-10-23 · Source updated 2026-10-11 · License: Apache-2.0. Check the original repository for the latest version.
SKILL.md instructions
# Deploy the LinkedIn Signal Agent
You are setting up an Omnara agent for the user from `agent.yaml` in this
folder. The goal: an agent profile the user has watched run once, reachable
wherever they want it (their own app, Slack, Discord, or the Omnara
console), and
optionally running on a daily schedule.
The steps below are the usual path and have the exact commands. Skip anything
that's already done (for example, the token and profile exist and the user
only wants new queries), follow the user's lead if they want a different
order, and narrate briefly as you go.
- Start from `agent.yaml` as written. If the user wants something different
(the instruction, tools, model, or how they reach the agent), change it and
tell them what you changed.
- If a command fails, read the error and fix it; `npx omnara <command> --help`
and [docs.omnara.com](https://docs.omnara.com) have the details. If you're
stuck, show the user the error.
The commands use the Omnara CLI (`npx omnara`) because its login handles auth
in one step; add `--json` when you need to read IDs from the output. They're a
reference, not a requirement: the Omnara MCP tools, the
[REST API](https://docs.omnara.com/api-reference/openapi.yaml), or the SDK work
too, and the flags map directly to API fields. What matters is the result:
a secret with the token, a profile from the filled-in `agent.yaml`, and
whatever the user picks in steps 7 and 8. Slack and Discord setup is simplest
with the CLI.
## 1. Connect to Omnara
1. Run `npx omnara whoami`. If it reports that you aren't logged in, run
`npx omnara login` in an interactive terminal, share the approval link it
prints, and wait until the user approves.
2. Pick the org and project. `npx omnara whoami --json` lists the user's orgs,
and `npx omnara projects list --org <org-id> --json` lists an org's
projects.
- If there's only one org and one project, use them.
- If there are several of either, ask the user which to use. Suggest the
current defaults from `npx omnara config` if they're set, otherwise the
project named `Default`.
Save the choice with `npx omnara config --org <org-id> --project <project-id>`.
Remember the project ID; later steps need it.
## 2. Choose what to track
LinkedIn keyword search returns plenty of adjacent hype, so the agent's
precision comes from knowing who the user is. Ask about their product, their
audience, and what kind of post would make them want to reply, then write
three values:
- `TEAM_CONTEXT`: one paragraph, on a single line, covering what the product
does, who it's for, its main competitors, and what a strong demand signal
looks like (for example, "a team describing building this in-house").
This matters more than the queries.
- `LINKEDIN_SEARCH_QUERIES`: LinkedIn post searches as a JSON array on one
line. Boolean syntax works (up to 5 operators and 500 characters per
query), and cost scales per query, so prefer one boolean query over
several. Escape inner double quotes, for example
`["\"managed agents\" OR \"agent infrastructure\" OR \"durable agents\""]`.
Use `[]` to skip keyword search.
- `LINKEDIN_TARGET_URLS`: company pages or profiles whose last-day posts are
scanned even without a keyword match, such as competitors and category
voices, as a JSON array on one line, for example
`["https://www.linkedin.com/company/langchain/"]`. Use `[]` to skip tracked
feeds.
At least one of the two lists must be nonempty. Show all three to the user (as
plain text and lists, not JSON) and adjust until they're happy.
## 3. Store the Apify token
LinkedIn's API has no public post search, so the agent scrapes through
[Apify's hosted MCP server](https://mcp.apify.com) running two scrapers that
need no LinkedIn account or cookie:
[harvestapi/linkedin-post-search](https://apify.com/harvestapi/linkedin-post-search)
and
[harvestapi/linkedin-profile-posts](https://apify.com/harvestapi/linkedin-profile-posts).
The user needs a free Apify account
([console.apify.com/sign-up](https://console.apify.com/sign-up), no credit
card); the API token is on the **API & Integrations** page under
**Settings**. Both scrapers are billed per post, and a scan is capped at 200
search posts plus 10 per tracked feed, about $0.50 at most.
1. Check for an existing secret:
`npx omnara secrets list --owner-kind project --owner-project-id <project-id> --name linkedin-signal-agent-apify-token --json`.
If one exists, ask whether to reuse it. To reuse it, note its `id` and skip
to step 4. To change its value, have the user update it on the
**Secrets** page of the Omnara dashboard (the ID stays the same) and skip to
step 4. If only `reddit-signal-agent-apify-token` exists, it holds the
same kind of Apify token; offer to reuse its `id`.
2. Ask the user to add the token to a `.env` file in the current directory
and tell you when it's saved (pasting it in the chat also works):
```sh
APIFY_TOKEN=...
```
3. Create the secret:
```sh
set -a && . ./.env && set +a
npx omnara secrets create --owner-kind project --owner-project-id <project-id> \
--name linkedin-signal-agent-apify-token --material-kind generic \
--material-value "$APIFY_TOKEN" --json
```
Note the `id` (`sec_…`) from the output.
## 4. Pick the model
`npx omnara grant models list --json`: each item has `model.provider_config`
and `model.name`. Ask the user which model to use. Suggest `openai/gpt-6.1-sol`
on `omnara-openrouter` if it's granted (it replaces GPT-6 Sol, which the
instruction was tested with); otherwise suggest a strong general-purpose model from the list. Name a couple
of alternatives rather than the whole list, and show everything if they ask.
The choice gives `MODEL_PROVIDER_CONFIG` and `MODEL_NAME`.
This agent needs no machine pool: the Apify MCP server does all the fetching.
## 5. Create the agent
1. Copy `agent.yaml` from this folder to `./linkedin-signal-agent.yaml` in
the current directory. If this folder isn't available locally, download
https://raw.githubusercontent.com/omnara-ai/omnara/main/examples/linkedin-signal-agent/agent.yaml
instead.
2. In the copy, replace every placeholder:
| Placeholder | Value |
| --- | --- |
| `{{TEAM_CONTEXT}}` | from step 2, on one line |
| `{{LINKEDIN_SEARCH_QUERIES}}` | from step 2, the JSON array |
| `{{LINKEDIN_TARGET_URLS}}` | from step 2, the JSON array |
| `{{APIFY_TOKEN_SECRET_ID}}` | the `sec_…` ID from step 3 |
| `{{MODEL_PROVIDER_CONFIG}}` | from step 4 |
| `{{MODEL_NAME}}` | from step 4 |
Then confirm nothing is left: `grep -n '{{' linkedin-signal-agent.yaml`
must print nothing.
3. Check for an existing profile: `npx omnara profiles list --name linkedin-signal-agent --json`.
- None: `npx omnara profiles create --name linkedin-signal-agent --file ./linkedin-signal-agent.yaml --json`
- Exists: `npx omnara profiles update <agent-profile-id> --file ./linkedin-signal-agent.yaml --json`
Note the profile's `id` and `current_config_id` from the output.
## 6. Run a first scan
```sh
npx omnara agents launch --profile <agent-profile-id> --config <current-config-id> \
--message "Run the LinkedIn scan now." --json
```
Give the user the link to watch it work:
`https://app.omnara.com/projects/<project-id>/agents/<agent-id>`. The scrapes
take a few minutes, mostly a quiet stretch of `get-actor-run` calls while the
agent waits. The user can reply in the console to ask for reply drafts or
push back on the filtering.
## 7. Choose where to use it
Ask where the user wants to talk to the agent, offering these in this order.
Any combination is fine.
**Their own app, existing or new (recommended).** Put the agent where the
user's team already works: inside their existing product or internal tool, or, if there's no
natural home, a small UI built for it. Both are the same integration: launch
agents from the profile and stream their replies with the TypeScript SDK
(`@omnara/sdk`) or the REST API; see [docs.omnara.com](https://docs.omnara.com).
Anything else that can call the API (an alerting webhook, a CI job, a script)
can start the agent the same way. The app needs an org API key: the user
creates one on the dashboard's **API Tokens** page (**Organization** tab →
**New token**), then grants it a role on this project from the key's detail
panel. Help them wire it in, or build the UI with them.
**Slack.** The bot answers wherever it's mentioned, and thread replies become
instructions to the agent.
If `npx omnara integrations list --json` already has an integration named
`linkedin-signal-agent-slack` from an earlier run of this skill, reuse it
whatever its state, since names are unique in a project. If
`npx omnara integrations get <integration-id> --json` doesn't list this profile
under `settings.launcher.profiles`, add it with
`npx omnara integrations profiles <integration-id> --profile-ids <agent-profile-id>`;
the flag replaces the list, so repeat each profile already there. Then, if its
`state` is `active`, skip to its last step. If it's `disconnected`, setup didn't
finish: skip step 2, and redo step 1 only if the token in `.env` has expired.
1. The user creates an app configuration token at
[api.slack.com/apps](https://api.slack.com/apps) under **Your App
Configuration Tokens** → **Generate Token**. It expires after about 12
hours. Have the user add it to `.env` as `SLACK_APP_CONFIG_TOKEN=...`.
2. Create the integration with this profile in its launcher, so a mention
starts this agent, and note the `itg_…` ID it returns:
```sh
npx omnara integrations create --name linkedin-signal-agent-slack \
--integration-kind slack_thread \
--settings '{"launcher":{"profiles":["<agent-profile-id>"]}}' --json
```
The name is permanent and names the agent's Slack tools
(`int__linkedin-signal-agent-slack__post_message`).
3. Create the Slack app and connect it:
```sh
set -a && . ./.env && set +a
npx omnara integrations slack <integration-id> --app-name "LinkedIn Signal Agent" \
--app-configuration-token "$SLACK_APP_CONFIG_TOKEN"
```
Ask before choosing a different app name; it's how the team mentions the
bot. It opens a Slack authorization page that the user approves before it
expires.
4. Tell the user to invite the bot to a channel
(`/invite @LinkedIn Signal Agent`) and mention it: "@LinkedIn Signal Agent
run the scan".
**Discord.** Works like Slack: the bot answers in a new thread wherever
it's mentioned in a server channel, and replies in the thread go to the
same agent. It doesn't answer direct messages.
If an integration named `linkedin-signal-agent-discord` already exists, reuse it
the same way: add this profile if it's missing. If it's `active`, skip to
step 5; Omnara can't tell whether steps 5 and 6 were done in Discord, so check them
with the user. If it's `disconnected`, skip step 3 and do the steps that weren't
done, passing the current `setup_revision` from
`npx omnara integrations get <integration-id> --json` in step 4.
1. The user creates an application named "LinkedIn Signal Agent" in the
[Discord Developer Portal](https://discord.com/developers/applications);
ask before choosing a different name, since it's how the team mentions
the bot. They copy the **Application ID** and **Public Key** from
**General Information**. Under **Bot**, they select **Reset Token** to copy
the bot token, turn on **Message Content Intent**, and turn off **Public
Bot** so only they can add it (if Discord refuses, first set
**Installation** → **Install Link** to **None**). Have the user add the
values to `.env`:
```sh
DISCORD_APPLICATION_ID=...
DISCORD_PUBLIC_KEY=...
DISCORD_BOT_TOKEN=...
```
2. Store the bot token and note the `sec_…` ID. If a secret named
`linkedin-signal-agent-discord-bot-token` already exists
(`npx omnara secrets list --owner-kind project --owner-project-id <project-id> --name linkedin-signal-agent-discord-bot-token --json`),
reuse its ID; if the user has reset the token since, have them paste the new
one into it on the dashboard's **Secrets** page (the ID stays the same).
Otherwise:
```sh
set -a && . ./.env && set +a
npx omnara secrets create --owner-kind project --owner-project-id <project-id> \
--name linkedin-signal-agent-discord-bot-token --material-kind generic \
--material-value "$DISCORD_BOT_TOKEN" --json
```
3. Create the integration with this profile in its launcher, and note the
`itg_…` ID and `setup_revision` it returns:
```sh
npx omnara integrations create --name linkedin-signal-agent-discord \
--integration-kind discord_thread \
--settings '{"launcher":{"profiles":["<agent-profile-id>"]}}' --json
```
The name is permanent and names the agent's Discord tools
(`int__linkedin-signal-agent-discord__post_message`).
4. Connect the bot. Omnara checks the token and finds the bot's user:
```sh
set -a && . ./.env && set +a
npx omnara integrations configure <integration-id> \
--expected-setup-revision <setup-revision> \
--provider-tenant-id "$DISCORD_APPLICATION_ID" \
--credential-secret-id <secret-id> \
--provider-config "{\"public_key\":\"$DISCORD_PUBLIC_KEY\"}" --json
```
5. Under **General Information**, the user sets **Interactions Endpoint URL**
to `https://app.omnara.com/api/integrations/discord/<application-id>/interactions`
and saves; the buttons on the bot's questions need it. Discord checks the
URL when it's saved, so this has to come after step 4.
6. The user adds the bot to their server by opening this link, which asks
only for the permissions the bot needs:
`https://discord.com/oauth2/authorize?client_id=<application-id>&scope=bot&permissions=309237746752&integration_type=0`.
Then they mention it in a channel: "@LinkedIn Signal Agent run the scan".
**Omnara console.** Already done: every agent launched from the profile shows
up in the console.
## 8. Run it daily (optional)
A schedule works with any of the above. Ask whether the user wants a daily
scan, and for the time and timezone (default: weekdays at 9am in the user's
timezone). Set `--cron` and `--timezone` from their answer:
```sh
npx omnara crons create --name linkedin-signal-agent-daily \
--target-type profile --target-agent-profile-id <agent-profile-id> \
--cron '0 9 * * 1-5' --timezone America/Los_Angeles \
--message-template 'Run the daily LinkedIn scan.' --json
```
If `npx omnara crons list --name linkedin-signal-agent-daily --json` already
shows a trigger, change it with `npx omnara crons update <cron-trigger-id>`
(same flags) instead of creating a second one.
Each firing launches a fresh agent from the profile. It shows up in the
console, and the user's app can pick it up through the SDK or API. To get
each digest in a Slack or Discord channel, mention the bot in that channel
once, then
create the trigger with `--target-type agent --target-agent-id <agent-id>`
(the agent ID from that conversation's console URL), so every digest posts to
that thread.
## 9. Wrap up
Summarize what you created: the secret name, the profile, and the Slack or
Discord integration or cron trigger if any. Then tell the user:
- **Change the queries or anything else:** ask a coding agent with this
skill. It reuses the secret and updates the profile in place.
- **Remove it:** delete the cron trigger (`npx omnara crons delete <id>`),
delete the Slack and Discord integrations, if any
(`npx omnara integrations delete <integration-id>`), or, if other agents
share it, rerun `npx omnara integrations profiles` with only their
profiles. Then run `npx omnara profiles delete <agent-profile-id>` and
`npx omnara secrets delete <secret-id>` (skip the secret if another agent
shares it).
With Discord, also delete the bot token secret
(`npx omnara secrets delete <secret-id>`) and the application in the
Discord Developer Portal.