Review Facebook ad campaign performance by campaign ID and date range, then get practical recommendations to improve results.
Analyze campaign performance and return practical recommendations.
| Name | Required | Description | Default |
|---|---|---|---|
| campaign_id | Yes | ||
| date_preset | No | last_7d |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full behavioral disclosure. It mentions 'recommendations' but doesn't say whether the tool is read-only, what analysis it performs, whether it can mutate campaign state, or what kind of output to expect. With an output schema present, some return info is covered, but the operation's safety profile and behavior remain opaque.
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?
A single, efficient sentence that is front-loaded with the core action. No wasted words, though it is arguably too terse given the tool's complexity.
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 tool that presumably performs complex analysis and returns recommendations, the description is severely incomplete. It doesn't explain what 'analyze' entails, what recommendations look like, or how it differs from similar tools. The output schema may cover the return format, but behavioral gaps remain.
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 0%. The description adds no information about the two parameters: campaign_id (required) and date_preset. It doesn't explain what date_preset values are valid or what time period the analysis covers. The description fails to compensate for the lack of schema documentation.
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?
States a verb 'analyze' and resource 'campaign performance', plus a benefit ('return practical recommendations'). However, it doesn't distinguish this from siblings like get_insights or compare_performance, which also analyze performance data. The purpose is clear but generic.
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?
No guidance on when to use this vs get_insights, compare_performance, or get_campaign_details. The description implies analysis but offers no context about appropriate scenarios or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.