create_linkedin_ads_campaign
Create a LinkedIn campaign inside an existing campaign group. Created DRAFT — it spends NOTHING until activated with set_linkedin_ads_status(confirm:true) — and a campaign on its own carries no creative, so it cannot serve an impression. Budget amounts are in the ad account’s currency; tell the u...
This record as markdown: /tools/hermoso/create-linkedin-ads-campaign.md
What create_linkedin_ads_campaign does on Hermoso
AI agents use create_linkedin_ads_campaign to create or update resources in Hermoso, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Hermoso environment.
Why create_linkedin_ads_campaign is rated Medium
An AI agent can call create_linkedin_ads_campaign faster than any human can review: one bad instruction and it creates or modifies resources in Hermoso by the hundred, each call as confident as the last.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs create_linkedin_ads_campaign safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Hermoso, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For create_linkedin_ads_campaign, this is the rule to start with:
create_linkedin_ads_campaign stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Hermoso, apply this rule, and every create_linkedin_ads_campaign call is checked against it from then on.
Questions about create_linkedin_ads_campaign
Create a LinkedIn campaign inside an existing campaign group. Created DRAFT — it spends NOTHING until activated with set_linkedin_ads_status(confirm:true) — and a campaign on its own carries no creative, so it cannot serve an impression. Budget amounts are in the ad account’s currency; tell the user that LinkedIn may spend UP TO 150% of a daily budget on a high-opportunity day before they pick a number. Two LinkedIn behaviours to repeat rather than hide: on manual, target-cost or cost-cap bidding a unitCost of 0 means the campaign never delivers, and LinkedIn DEFERS some validation on DRAFT objects, so a clean create can still fail at activation — never promise it will run. TARGETING IS MANDATORY on LinkedIn — a campaign with no audience is refused outright — so pass locations (and optionally include/exclude facets like titles, industries, seniorities or staffCountRanges), or a raw targetingCriteria. Resolve every targeting value with search_linkedin_ads_targeting first: they are opaque URNs and MUST NOT be invented. LinkedIn’s own enums for type, objectiveType and costType are passed straight through, and LinkedIn’s refusal is surfaced verbatim if one is wrong. Read back before you are told it exists. It is categorised as a Write tool in the Hermoso MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Hermoso MCP server in PolicyLayer and add a rule for create_linkedin_ads_campaign: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Hermoso. Nothing to install.
create_linkedin_ads_campaign is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the create_linkedin_ads_campaign rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for create_linkedin_ads_campaign. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
create_linkedin_ads_campaign is provided by the Hermoso MCP server (https://app.hermoso.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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