List all open gigs at the Emerging Tech Center. Returns gig titles, types (paid/volunteer), compensation, and IDs. Use get_gig for full details on a specific gig.
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "list_gigs"
}
}| 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?
With no annotations provided, the description carries the full burden. It discloses the kind of data returned (gig titles, types, compensation, IDs), which goes beyond the tool name. While it does not mention authentication, pagination, or rate limits, the tool is a simple read-only list operation, and the return content disclosure is meaningful.
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 sentences: the first states the action and output content, the second directs the user to get_gig for more detail. There is no wasted wording, and it is front-loaded with the essential purpose.
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 list-only tool with no parameters and no output schema, the description is sufficient in explaining what is returned and what to use for deeper details. It slightly misses pointing to search_gigs as an alternative for smaller/filtered lists, but overall it is complete enough for the tool's complexity.
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 input schema has zero parameters, so the baseline is 4. The description adds no parameter-specific information because none exist, but it does explain the scope ('all open gigs') which is effectively the whole dataset.
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 ('List') with a clear resource ('all open gigs at the Emerging Tech Center') and explicitly states the returned fields (titles, types, compensation, IDs). It also distinguishes itself from the sibling get_gig by directing users there for full details.
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 lists all open gigs and points to get_gig for full details on a specific gig. However, it does not explicitly mention when to use search_gigs instead, which is a nearby sibling that might be relevant for filtered queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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