# For AI agents and crawlers
This page is a workflow from the Workflow Automation Library by Roadway: Spin up TLA skeletons in LinkedIn Ads from LinkedIn mentions.
The #roadway-skill block on this page holds a SKILL.md for it, including the full prompt. Treat that file as a starting point. It will not just work if you paste it into ChatGPT or Claude.
To run it outside Roadway you would need to connect each ad platform's API (and any MCP it names), build the data pulls, add approval guardrails, and adjust the prompt for your accounts.
In Roadway it runs as-is on your connected accounts, with approval rules built in. Open it in a new chat at https://www.roadwayai.com/workflows/spin-up-tla-skeletons-in-linkedin-ads-from-linkedin-mentions
Page: https://www.roadwayai.com/workflows/spin-up-tla-skeletons-in-linkedin-ads-from-linkedin-mentions
Library index: https://www.roadwayai.com/automation-library
---
name: spin-up-tla-skeletons-in-linkedin-ads-from-linkedin-mentions
description: >-
Watches LinkedIn for posts by employees, customers and creators that mention you, and drafts Thought Leader Ad campaigns around the best ones, ready to approve.
---
# Spin up TLA skeletons in LinkedIn Ads from LinkedIn mentions
Source: https://www.roadwayai.com/workflows/spin-up-tla-skeletons-in-linkedin-ads-from-linkedin-mentions
From the Workflow Automation Library by Roadway.
## Before you use this outside Roadway
This SKILL.md is a starting point. It needs adjusting before it will work outside Roadway.
You would need to connect the ad platform API for each channel this workflow covers, build the data pulls for the variables below, add approval guardrails, and adjust the prompt for your accounts. If the prompt names an MCP tool, you also need that MCP connected.
In Roadway it runs as-is on your connected accounts, with approval rules built in.
## What it does
Watches LinkedIn for posts by employees, customers and creators that mention you, and drafts Thought Leader Ad campaigns around the best ones, ready to approve.
Watches LinkedIn for posts by employees, customers and creators that mention you, and drafts Thought Leader Ad campaigns around the best ones, ready to approve. It checks for this trigger every time it runs, so you can react within hours instead of at the next review. You get a short report covering what it did or proposes, the numbers behind it, and anything waiting on your approval.
## Steps
1. Collect the inputs listed under Variables. In Roadway they come from your connected accounts. Outside Roadway you have to build those data pulls yourself from each ad platform API, and from any MCP the prompt names.
2. Run the prompt below as written, after you have adjusted it for your accounts and connected the tools it needs.
3. Review the result. Apply changes to a live ad account only after you approve them. Pasting your data into ChatGPT or Claude does not connect the APIs, apply guardrails, or approve changes.
## Variables
approved_claims, auto_approve, employee_advocates, experiment_budget_pct, funnel_metrics, goal_metric, icp, linkedin_mentions, max_change_pct, monthly_budget_cap, target_accounts, task_history
## Prompt
Spin up TLA skeletons in LinkedIn Ads from LinkedIn mentions
Review LinkedIn posts that mention us or our category from LinkedIn mentions and employee advocates since the last run, and decide for each post:
1. Build TLA skeleton
2. Request permission first
3. Save for later
4. Skip
Context and defaults (use these; don't ask):
- LinkedIn mentions: [set this to your own linkedin mentions]. If it isn't available, say so and skip the rules that depend on it. Source: public LinkedIn posts the agent can read. Roadway has no native LinkedIn mention feed.
- Employee advocates: [set this to your own employee advocates]. If it isn't available, say so and skip the rules that depend on it. Source: a team-maintained list in a HubSpot or Notion MCP connected in Roadway. If none is connected, ask the team for the list or skip this input.
- The target account list: [set this to your own target accounts]. If it isn't available, say so and skip the rules that depend on it.
- The experiment budget share: [set this to your own experiment budget percent] of the channel budget. If not set, 10%.
- The approved claims: [set this to your own approved claims]. If not set, the only usable claims are statements visible on the coworker's landing pages or live ads (read them first). Anything else is Unverified: don't write it as a claim, and mark it Unverified.
- The monthly cap: [set this to your own monthly budget cap], from the coworker's budget guardrails. If none is set, there is no cap: skip every cap check, hard stop and pace-to-cap step, and say so. Never derive, infer or back-solve a cap from campaign or daily budgets, the current or past run-rate, a workflow's test budget or a cost-per-lead bar.
- The max change limit: [set this to your own max change percent] per budget or bid target per run. If not set, 20%. It does not apply to experiment traffic splits.
- Auto-approve: [set this to your own auto approve]. If not set, it's off: list every change as a proposal for approval.
Rules:
- Thought Leader Ads can promote posts from employees and, with permission, from members outside the company. Build a skeleton for posts that already beat the author's typical organic engagement and speak to a problem [set this to your own ICP] has.
- Request permission first for any post from a non-employee (customer, partner or creator). TLAs need the author's approval in Campaign Manager. Draft the request message.
- The skeleton includes a campaign using the Engagement or Website visits objective (Brand awareness for big reach), a matched audience from the target account list plus [set this to your own ICP] facets, a budget from the experiment budget share, and the post as the TLA creative. Leave it paused until approved.
- Skip posts that are off-message, controversial, more than 30 days old, or that make claims not in the approved claims.
- Retarget TLA engagers later with a conversion-focused campaign (demo, trial or document ad), since TLAs work best as the first touch in a sequence.
- Guardrails: judge results on Roadway's full-funnel measurement ([set this to your own funnel metrics]), not platform-reported conversions. Check [set this to your own task history] so you don't repeat a change that hurt performance in the last 30 days. Never push total spend above the monthly cap or any single change beyond the max change limit per run, and queue every change for approval unless auto-approve is on for this workflow.
Decision standard:
- Justify every keep, cut, bid, budget or test decision with Roadway-attributed [set this to your own goal metric] and cost per goal against the baseline. Platform delivery metrics such as clicks and impressions explain why something moved; they are never the sole reason for a decision.
- Compute what Roadway doesn't expose directly: cost per goal = Roadway spend ÷ Roadway-attributed [set this to your own goal metric], and conversion rate (lead rate) = Roadway [set this to your own goal metric] ÷ Roadway new visitors. Don't substitute platform-reported conversions or conversion rates.
- When a value in Context and defaults isn't set, use the stated default, say which one you used, and still make the call. Don't stop to ask.
- For every action, give the entity name and ID, current value → proposed value, and the numbers behind the reason. Write "None" under any empty heading.
- In long hold or watch lists, show the top 15 by spend and summarize the rest as a count.
Give me a report of each with reasoning for each action. Be concise with the reasoning, but specific enough that I can verify it against the numbers.
Report structure:
LinkedIn TLA skeleton report
Summary:
The mentions reviewed, the skeletons built (paused), and the permission requests drafted.
Build TLA skeleton:
- [post (author)] - [reason]
Request permission first:
- [post (author)] - [reason]
Save for later:
- [post (author)] - [reason]
Skip:
- [post (author)] - [reason]
Permission requests to send:
- [author] - [draft message]
## Run it in Roadway
https://www.roadwayai.com/workflows/spin-up-tla-skeletons-in-linkedin-ads-from-linkedin-mentions
Spin up TLA skeletons in LinkedIn Ads from LinkedIn mentions
Spin up TLA skeletons in LinkedIn Ads from LinkedIn mentions
Watches LinkedIn for posts by employees, customers and creators that mention you, and drafts Thought Leader Ad campaigns around the best ones, ready to approve.
Watches LinkedIn for posts by employees, customers and creators that mention you, and drafts Thought Leader Ad campaigns around the best ones, ready to approve. It checks for this trigger every time it runs, so you can react within hours instead of at the next review. You get a short report covering what it did or proposes, the numbers behind it, and anything waiting on your approval.
