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run_betalist_topics_startups

Retrieve startups for a BetaList topic by slug or URL, returning name, tagline, logo, and link. Use pagination to collect up to 250 records per topic.

Instructions

Startups of one BetaList topic (slug like generative-ai, category/topic, or a BetaList topic URL): name, tagline, logo and link. 1 point per returned record.

Input Schema

NameRequiredDescriptionDefault
topicYesTopic slug or URL. e.g. generative-ai
max_itemsNoMax items (up to 250)
start_pageNoStarting page

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.1

TDQS

B3.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It usefully discloses a cost signal ("1 point per returned record") and enumerates the returned fields, which is more than nothing. However, it says nothing about pagination behavior despite start_page/max_items, rate limits, or auth requirements.

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 compact sentence front-loads the verb and resource, then lists the returned fields and the cost note. No filler or repetition; appropriately sized for a simple list tool.

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?

With no output schema, the description compensates by enumerating returned fields (name, tagline, logo, link). Combined with 100% schema coverage on inputs, an agent has enough to call it correctly. The only missing piece is how it relates to sibling topic/startup tools.

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?

Schema coverage is 100%, so the schema already documents all three parameters including the topic example and the 250-item cap. The description adds mild value by clarifying the topic can be a slug, a category/topic, or a BetaList URL, but mostly restates the schema.

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: retrieve startups belonging to one BetaList topic, and even names the return fields (name, tagline, logo, link). It is clear what the tool does, but it never distinguishes itself from siblings like run_betalist_startups, run_betalist_startups_latest, or run_betalist_startups_search, leaving ambiguous which one to pick.

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?

The description implies usage (fetch startups for a single topic) but gives no explicit when-to-use guidance, no exclusions, and never names the alternate BetaList tools. With three near-identical siblings in the list, the absence of routing guidance is a real gap.

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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