delete_skillDelete one of the workspace’s CUSTOM skills by id (from list_skills). Built-in skills/recipes can’t be deleted. Minor + re-creatable, so no confirm needed.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | the custom skill id (from list_skills) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already signal destructiveHint=true and idempotentHint=true. The description adds the context that this is a 'Minor + re-creatable' operation, so no confirmation is needed, and clarifies the constraint that built-in skills are excluded. This goes beyond the annotations by explaining the low risk and reversibility, which helps an agent decide when to invoke without confirmations.
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 primary action and constraint are front-loaded in the first sentence, and the risk/re-confirmation note is efficiently placed in the second. Every clause contributes meaningful information—no fluff or redundancy.
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 delete operation with a single required parameter and no output schema, the description is fully adequate. It tells the agent what id to use, what can't be deleted, and the low risk level (no confirm needed). The inclusion of 're-creatable' addresses concerns about destructiveness. No essential information 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?
Schema description coverage is 100% for the single parameter 'id', and its description already states 'the custom skill id (from list_skills)'. The tool description essentially repeats this information without adding new semantic details (e.g., format, constraints, or examples). Thus, the description adds no value beyond the schema, so it sits at the baseline.
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 action ('Delete'), a specific resource (workspace's CUSTOM skills), and clarifies that built-in skills/recipes cannot be deleted. It also references the source of the id (from list_skills), which distinguishes this from other delete_* siblings. This 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 explicitly limits usage to custom skills and notes that built-in skills/recipes can't be deleted, providing a clear condition. It also directs the agent to list_skills to obtain the id. However, it doesn't explicitly name alternative tools or say 'do not use for built-in skills' in a direct command, though the implication is strong.
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.