Skip to main content
Glama

Current clipping pay rates

get_clipping_pay_rates
Read-only

Use when someone asks how much clipping pays, what clipping campaigns pay per 1,000 views, or which categories/platforms pay most. Returns the latest snapshot of public clipping campaign rates (median, range, by category and platform).

Input Schema

NameRequiredDescriptionDefault
categoryNoOptional category filter, e.g. Entertainment, Finance, Streamer

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds useful behavioral context beyond that: this is a snapshot (not historical/time-series) of *public* campaign rates, and it names the aggregates returned (median, range, by category and platform). It stops short of stating freshness, coverage limits, or what happens when no rate data exists.

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

Conciseness5/5

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

Two sentences, zero filler, with the invocation trigger front-loaded before the return-content sentence. Every clause earns its place.

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 carries the burden of explaining returns, and it does so adequately (median, range, by category and platform). Minor gaps remain around data freshness and behavior when the optional filter matches nothing, but nothing an agent needs to invoke it correctly is missing.

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 description coverage is 100% and the single optional `category` param is documented with examples (Entertainment, Finance, Streamer). The description only echoes that category and platform breakdowns exist, adding little syntax or semantics beyond the schema; baseline 3 is appropriate.

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: returns the latest snapshot of public clipping campaign rates, with median, range, and breakdowns by category and platform. It's clear what the tool produces, but it never names the sibling it must be distinguished from — estimate_clipping_earnings — which also answers questions about clipping pay.

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

Usage Guidelines4/5

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

The opening "Use when someone asks how much clipping pays, what clipping campaigns pay per 1,000 views, or which categories/platforms pay most" gives concrete trigger phrases, which is strong. However, there is no exclusion: a question like "how much would I earn" could plausibly route to estimate_clipping_earnings, and the description gives no rule to break that tie.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources