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demandscope

demandscope

by baobabcat
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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github_trend

Compare GitHub repository creation across two time windows to detect accelerating supply or interest, helping validate digital-product ideas.

Instructions

GitHub repos created in the last N days vs the prior window; growth_ratio > 1 means accelerating supply/interest.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "github_trend"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYes
window_daysNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It explains the growth_ratio semantics and the comparison window, which is useful, but it does not describe output shape, data limits, or whether the result is a list of repos or an aggregate metric.

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?

The description is a single focused sentence with no filler. The key comparison and metric interpretation are front-loaded, though the meaning of query could have been added without much loss of conciseness.

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

Completeness2/5

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

For a tool with no annotations, no output schema, and a required query parameter, the description is too thin. It leaves critical unknowns: what format query takes, what the response contains, and how growth_ratio is derived beyond the vague 'vs prior window' phrasing.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It indirectly explains window_days via 'last N days' and 'prior window', but the required query parameter is entirely unexplained, leaving the agent to guess what should go in it.

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?

The description identifies GitHub repos as the resource and defines the core trend metric (growth_ratio comparing recent vs prior window). It is specific enough to distinguish this from a plain repository info tool, though it lacks an explicit verb like 'returns' or 'computes'.

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 use this tool versus siblings such as github_repo_signal or hn_trend. The context implies it is for trend analysis, but no explicit conditions or alternatives are provided.

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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