Lists skills saved in your Web2MD cloud account as a compact id, name, and description summary; use the companion get_skill tool to fetch a full SKILL.md body.
List the skills saved in your Web2MD cloud account. Returns a compact list (id, name, description). Use get_skill to fetch the full SKILL.md body of one.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries the full burden. It does disclose the return shape (a compact list of id, name, description) and that results are account-scoped ('your Web2MD cloud account'), which is useful behavioral context. It says nothing about pagination/limits on a potentially unbounded list, ordering, or whether it is read-only, which leaves real gaps for a no-annotation tool.
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?
Three short sentences, front-loaded with what the tool returns before the sibling cross-reference. Every sentence carries a distinct piece of information (purpose, return shape, alternative) with no repetition of the title or 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?
For a zero-parameter list tool with no output schema, the description covers purpose, return fields, and the sibling alternative, which is enough to invoke it correctly. The only missing element is how large/complete the returned list is (pagination or truncation behavior), a minor gap given the tool's simplicity.
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 tool takes zero parameters, so there is nothing for the description to disambiguate — baseline 4 applies. The mention of id/name/description refers to the response, not inputs, and does not mislead about call signature.
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 uses a specific verb and resource ('List the skills saved in your Web2MD cloud account') and immediately scopes the output ('Returns a compact list (id, name, description)'). It explicitly distinguishes itself from the sibling get_skill, so an agent can pick between them without opening either schema.
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?
It routes the agent to the alternative clearly: 'Use get_skill to fetch the full SKILL.md body of one,' which implicitly tells the agent not to use this tool for full content. What it lacks is explicit when-not-to-use guidance, such as whether it is scoped to a workspace or paginated, but the core selection condition is stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.