ppc_campaign_searchLightweight campaign name lookup. Returns campaign names and IDs only (no metrics). Use this to find campaign IDs before calling other tools.
| Name | Required | Description | Default |
|---|---|---|---|
| ad_type | No | ||
| profile_id | No | Which advertising profile (see account_profiles). Optional when the token has exactly one. | |
| name_contains | Yes | Search substring for campaign name. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already establish readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context by disclosing the exact return scope: campaign names and IDs only, with no metrics. This is especially valuable because there is no output schema to communicate the return shape.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, tightly packed with the core behavior, return scope, and usage intent. The key differentiator ('no metrics') is front-loaded, and every sentence earns its place without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup tool with strong read-only annotations, the description covers the essential return values and the intended workflow. It does not mention pagination, result limits, or how ad_type filtering interacts with results, but given the schema covers parameters well and the tool is deliberately lightweight, the definition is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67%, with name_contains and profile_id already explained in the input schema; the ad_type enum is self-documenting to some degree. The description reinforces the search-by-name behavior but does not add significant new parameter semantics beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies this as a lightweight campaign name lookup that returns only campaign names and IDs, explicitly stating it excludes metrics. This distinguishes it from metric-heavy sibling tools like ppc_campaign_details or ppc_campaigns, and the stated goal of finding campaign IDs before calling other tools gives immediate purpose clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: use this tool to find campaign IDs before calling other tools. It also implicitly excludes metric-related use cases by saying 'no metrics.' However, it does not explicitly name an alternative tool or state when not to use it, so it falls just short of full alternative/exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.