fetch_assetResolve a generated asset reference (a /generated/… path or any URL) to a clickable absolute URL + a direct download URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | the asset url or /generated/ path | |
| name | No | optional filename for the download |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds the core behavior of resolving a reference into two URLs, which is useful context beyond the annotations. It clearly communicates the operation without overspecifying, and there is no contradiction.
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, front-loaded sentence that states the action and output immediately. There is zero waste, and the critical nuance (accepts /generated/ paths or any URL) is included. It is appropriately sized for the task.
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 no output schema, the description explicitly defines the return values (absolute URL and download URL). The input requirements are covered by the schema, and the annotations establish safety. For a simple resolver, this fully equips an agent to call the tool correctly without missing 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 both parameters (url and name), so the schema already documents them. The description repeats the purpose but adds no new meaning about parameter formats or usage beyond what the schema states. With full schema coverage, the baseline of 3 is appropriate.
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 states a specific verb ('Resolve'), a clear resource ('a generated asset reference'), and the exact output ('clickable absolute URL + direct download URL'). It distinguishes itself from the many sibling tools by describing a unique transformation (path/URL resolution) that no other sibling appears to do, so an agent can easily tell it apart.
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 explains what the tool does but gives no guidance on when to use it over alternatives. There are no explicit conditions, exclusions, or references to sibling tools for similar tasks. In a large set of sibling tools, the agent must infer usage solely from the purpose, which is not sufficient per the rubric.
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.
With 293 tools, the surface is enormous and many tools have overlapping purposes—multiple posting tools (post_to_meta, post_to_linkedin, schedule_post, etc.), multiple analytics tools per channel, and several search tools (search_meta_ads, search_instagram, search_reddit...). While each description is detailed, the volume makes it difficult for an agent to reliably distinguish between similar tools without careful reading, leading to frequent misselection.
The naming is largely consistent with a verb_noun pattern (post_to_*, list_*, create_*, delete_*, update_*, manage_*). There are clear families for major operations. A few outliers like 'google_business_account', 'hermoso_capabilities', and 'store_get' break the pattern, but the overwhelming majority follow a predictable structure, making navigation somewhat easier.
293 tools is far beyond any reasonable scope for a single MCP server, even for a comprehensive marketing platform. The calibration guide flags 50+ as an extreme mismatch, and this is nearly six times that threshold. Such a large surface overwhelms context windows, increases the probability of misselection, and makes it impractical for agents to learn or use effectively.
The tool set covers a vast domain: ad creation and rendering, posting across nine+ social channels, analytics and reporting, file management (Drive/OneDrive), competitor research, brand management, and more. It appears to provide CRUD and lifecycle coverage for most resources. While there may be minor gaps given the immense scope, the overall coverage is impressively comprehensive.