Get coffee chat stats for requests sent, received, and accepted, so you can measure networking activity in your job search.
Get coffee chat statistics (requests sent, received, accepted, etc.).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v3.2.5Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It does not state that this is a read-only operation, whether the counts are scoped to the current user or a time window, or anything about aggregation behavior — significant gaps for a stats tool with zero annotation coverage.
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?
A single compact sentence with the resource front-loaded and the metric list in a parenthetical. No wasted text, though the trailing 'etc.' leaves the return shape vague rather than tight.
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?
The tool is simple (no params, no annotations), but with no output schema the description is the only place the return shape could be defined, and it only gestures at it with 'etc.' without stating the time range or whether counts are user-scoped. Adequate but leaves real gaps.
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 no parameters and schema coverage is 100%, so there is nothing for the description to compensate for. Baseline 4 applies.
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+resource ('Get coffee chat statistics') and enumerates the metrics returned (requests sent, received, accepted), which lets an agent distinguish it from mutation siblings like send_coffee_chat_request. It does not, however, differentiate itself from other stats readers such as get_dashboard_stats or get_scraping_stats.
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?
Usage is only implied by the name and metric list: an agent can infer this is the read-only aggregate view of coffee chat activity. There is no explicit statement of when to prefer this over get_coffee_chat_requests (raw list) or the other *stats tools, and no preconditions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.