fleet_get_brand_reportRead one live brand report in full by slug, including the creative intelligence payload used on the public brand page — proof points for outreach and positioning. Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Brand report slug from fleet_list_brand_reports. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=false. The description adds that the report includes a creative intelligence payload, but does not disclose additional behavioral traits like rate limits or authorization requirements. With annotations covering safety, the description adds modest context.
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?
The description is a single concise sentence that front-loads the action and includes relevant context like the payload and read-only nature. Every phrase adds value; no filler.
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?
Given the tool's simplicity (one parameter, no output schema), the description fully explains what the tool does and what it returns. It provides enough context for an agent to use it correctly without additional information.
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 100% for the single slug parameter, which is described as 'Brand report slug from fleet_list_brand_reports'. The description also mentions 'by slug' reinforcing the source. No additional parameter semantics are provided beyond what the schema already states, so baseline 3 applies.
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 states the tool reads a live brand report in full by slug, including the creative intelligence payload. It distinguishes itself from sibling tools like fleet_list_brand_reports by specifying it retrieves a single report, not a list.
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 implies usage after obtaining a slug from fleet_list_brand_reports, and mentions the report contains 'proof points for outreach and positioning', hinting at when it is useful. No explicit alternatives or exclusions are given, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Despite the high tool count, most tools have distinct purposes with thorough descriptions that specify when to use each. Some overlap exists among creative direction tools (call_creative_worlds vs chat_with_creative_worlds), but the descriptions clarify usage patterns.
Naming conventions are inconsistent overall: some follow verb_noun (create_powersource_url, decode_ad), others use noun_verb or compound names (adformula_intelligence, fleet_analytics_overview). However, subgroups like dispatch_* and list_*_presets maintain internal consistency.
112 tools is far beyond the typical 3-15 range for well-scoped servers. While the server covers a broad domain, the sheer number likely overwhelms agents and suggests insufficient consolidation of related operations.
The tool set covers core creative intelligence workflows: brand analysis, ad decoding, script generation, creative direction, and research. Minor gaps exist (e.g., no social media publishing tools), but the main use cases are well-supported.