list_libraryBrowse this workspace's Library — every image/video generated in the Studio, newest first (the same Library the web app shows). Returns served URLs you can open directly or hand to fetch_asset for a download link, plus each asset's kind, model, and age. Free, read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | filter by asset kind (default 'all') | |
| limit | No | max assets to return (default 20, max 60) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description's 'read-only' is redundant. However, it adds valuable behavioral context: that URLs are directly openable 'served URLs', that they can be passed to fetch_asset, that results are newest-first, and that each asset includes kind, model, and age. This goes beyond the annotations without 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 two sentences with no filler. It front-loads the primary purpose, then packs in scope, ordering, output content, and a usage hint (fetch_asset). Every clause earns its place; it is efficient and highly scannable.
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 read-only list tool with no output schema, the description fully covers what an agent needs: the scope, ordering, what is returned (served URLs, kind, model, age), and how to use the results (open directly or pass to fetch_asset). Annotations cover safety, and the limit parameter handles pagination. Nothing missing.
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 coverage is 100%: both 'kind' and 'limit' have descriptive comments (enum choices, defaults, max). The description does not add any parameter-specific meaning beyond what the schema already provides, so 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 ('Browse'), a resource ('this workspace's Library'), and the exact scope ('every image/video generated in the Studio'), plus sorting ('newest first'). It also distinguishes itself from sibling tools like fetch_asset (for download links) and other list_* tools (only workspace-generated assets). No ambiguity.
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 clearly implies when to use this tool (to browse workspace library assets) and even suggests a complementary tool (fetch_asset for download links). It notes the tool is 'Free, read-only', which is a usage guideline. However, it does not explicitly exclude other list tools (e.g., list_drive_files) or provide a decision rule, but the context makes it obvious.
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.