Skip to main content
Glama

scan_for_leads

Scans public job boards and auto-tracks capability matches to identify freelance leads.

Instructions

Scan public job boards and auto-track capability matches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It implies both a read (scan boards) and a write (auto-track matches), yet says nothing about whether leads are created or deduplicated, what 'capability matches' are compared against, or any rate limits — the write side-effect is the most important thing to disclose and it is left implicit.

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?

A single front-loaded sentence with no filler. It is tight, though 'auto-track capability matches' is jargon that could be replaced with plainer language at no length cost.

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

Completeness3/5

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

An output schema exists, so return values need not be described, and there are no parameters to document. However, for a zero-config tool with no annotations and a crowded sibling set, the definition needs at least a pointer on how it differs from hunt_jobs and what 'auto-track' mutates — that gap keeps it at minimum viable.

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

Parameters4/5

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

The tool takes zero parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. No compensating detail is needed.

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 and resource ('Scan public job boards') plus a secondary effect ('auto-track capability matches'), so the agent knows this reads external boards and writes matches. It does not distinguish itself from close siblings like hunt_jobs or chase_leads, which leaves an ambiguity an agent must resolve elsewhere.

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

Usage Guidelines2/5

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

There is no guidance on when to invoke this versus hunt_jobs, hot_leads, or chase_leads, nor any stated preconditions or frequency limits. 'Auto-track' hints at a downstream workflow but never says when or why to trigger the scan.

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