get_drive_fileFetch one Drive file’s metadata — name, type, size, modified time, a webViewLink to open it and a webContentLink to download it. Pass fileId (from list_drive_files). Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| fileId | Yes | the Drive file id (from list_drive_files) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds concrete behavioral detail beyond the annotations (readOnlyHint, destructiveHint): it exactly specifies the metadata fields returned and the two links (webViewLink and webContentLink). This goes beyond a mere read-only hint, providing the agent with expected output. No contradiction with annotations.
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 concise sentences: the first lists the returned fields, the second provides input sourcing and a read-only note. Every word is functional, no filler, and the most important information (what it does) is front-loaded. Perfectly sized for a simple tool.
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 single-parameter, read-only fetch tool with no output schema, the description fully compensates by listing the expected return fields and providing the input provenance. It gives the agent everything needed to call the tool correctly: how to get the fileId, what to expect in return, and that it is safe (read-only). Nothing essential is 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?
The single parameter fileId is fully documented in the schema (100% coverage), and the description repeats the source ('from list_drive_files') without adding new semantics. Since schema coverage is high, the baseline is 3; the description does not meaningfully enhance understanding of the parameter beyond what the schema already states.
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 explicitly states the verb 'fetch' and the resource 'one Drive file's metadata', and lists the specific fields returned (name, type, size, modified time, webViewLink, webContentLink). This clearly distinguishes it from sibling tools like list_drive_files (many files), update_drive_file (mutation), and delete_drive_file (deletion). The purpose is unambiguous.
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 context: it tells the agent to pass a fileId from list_drive_files, implying the correct workflow (list first, then fetch details). It also notes the tool is read-only, guiding safe usage. However, it does not explicitly mention when not to use it or contrast with alternatives like get_onedrive_file, leaving some inference required.
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.