get_toolRetrieve full details for a Plug and Ship tool by slug, including description, stars, install command, remote endpoint, license, tags, and last commit.
Full details for one tool by its Plug and Ship slug (from search_tools): description, stars, install command, remote endpoint, license, tags and last commit.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Tool slug, e.g. 'github-mcp-server' |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so safety is covered. The description adds genuine value by enumerating the returned payload (stars, install command, remote endpoint, license, tags, last commit), which matters because there is no output schema. It does not mention behavior for a nonexistent slug.
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?
One sentence, front-loaded with the action and key, then a tight enumeration of returned fields. No filler, every clause earns its place.
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?
With no output schema, listing the returned fields is exactly the right compensation, and read-only/idempotent/open-world behavior is covered by annotations. Minor gap: no mention of error behavior for an unknown slug.
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% and the single slug parameter is well documented with a pattern and example, so the baseline is 3. The description adds the provenance of the value ('from search_tools'), which is real semantic value the schema cannot express.
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?
States a specific verb and resource ('full details for one tool') and narrows the lookup key to a Plug and Ship slug, which separates it from list_best/trending/search_tools. It also names search_tools as the origin of the slug, so the agent can route between the two tools without opening a 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?
The parenthetical '(from search_tools)' tells the agent this is a follow-up step in an existing workflow, which is clear usage context. It stops short of explicit when-not-to-use guidance or stating what to do for an unknown/ambiguous slug.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.