get_tool
Fetch one aicoolies tool by slug from the public catalog.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Tool slug, for example cursor |
Fetch one aicoolies tool by slug from the public catalog.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Tool slug, for example cursor |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. 'Fetch' implies a read-only operation and 'public catalog' suggests no authentication, but the description does not mention behavior for unknown slugs, output format, or error handling. This is adequate but not rich.
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 a single focused sentence with no filler. The key identifying information is front-loaded: fetch, one tool, by slug, public catalog.
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 one-parameter retrieval tool, the description covers the essential context. There is no output schema, so a note about return format or not-found behavior would improve completeness, but the core operation is sufficiently described.
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%, with the single required parameter 'slug' already documented in the schema. The description adds little beyond repeating 'by slug', so a baseline score 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 ('Fetch'), a specific resource ('one aicoolies tool'), and the key discriminator ('by slug'). This clearly distinguishes it from sibling tools like search_tools and list_developer_resources.
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 gives clear context: use this when you know a tool's slug and want a single tool from the public catalog. It does not explicitly name alternatives or exclusions, but the slug-based single-item retrieval is an evident trigger condition.
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.
Each tool has a clearly separate role: catalog index vs metadata vs single-tool fetch vs search vs developer resources. Even get_tool and search_tools are distinguishable because one requires an exact slug while the other returns matching records.
All names follow a snake_case verb_noun pattern (get_catalog_context, get_catalog_meta, get_tool, list_developer_resources, search_tools). The verbs correspond to the action, and the naming is predictable across the set.
Five tools is appropriate for a read-only public catalog server. Each tool covers a necessary access pattern (context, metadata, single fetch, search, developer resources) without redundant entries.
The domain is catalog access, and the surface covers the full read path: metadata first, full context, specific tool lookup, search, and developer resources. No obvious write or lifecycle operations are needed for this public catalog use case.