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WilliamAxelC

lablab-mcp

by WilliamAxelC

check_my_status

Check your Lablab.ai status: active hackathons, deadline countdowns, rank, points, and recent submissions. Optionally provide a username.

Instructions

Quickly check what you currently have going on on Lablab.ai, including active hackathons, deadlines countdown, rank, points, and recent submissions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usernameNoOptional Lablab.ai username (e.g. 'WilliamA'). Defaults to configured user.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry the behavioral burden. Calling it 'check' implies a read-only, non-mutating operation, and the description helpfully notes it defaults to the configured user, but it never states read-only/safety semantics, auth requirements, or whether the snapshot is cached or live.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One well-formed sentence, front-loaded with the verb and the scope, with the returned fields enumerated compactly. No wasted words, though it is a single long sentence rather than a structured breakdown.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter read tool with no output schema, the description does the necessary work by listing what the status includes (hackathons, deadlines, rank, points, submissions). Minor gap: no note on whether output is scoped to the configured user vs. the passed username beyond the schema's own default note.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There is a single parameter with 100% schema description coverage, so the schema already documents the optional username and its default. The description adds nothing about the parameter (e.g., how it behaves for a username other than the configured one), so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('check') and resource ('your status on Lablab.ai') and enumerates the payload (active hackathons, deadlines, rank, points, recent submissions), so the agent knows exactly what comes back. It does not, however, differentiate itself from the closely related sibling get_user_profile, which an agent could easily confuse it with.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The word 'currently' and 'quickly' imply a lightweight, on-demand status lookup, but there is no explicit when-to-use guidance and no mention of get_user_profile as the alternative for full profile data. Usage is inferable but not stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.