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Get Research Credits

get_research_credits
Read-onlyIdempotent

Get the brand's topic snapshot credit usage for the current month.

Topic snapshots are gated by a monthly limit on the account. Call this before run_research_snapshot to confirm credits are available.

Args: brand_id: The brand to check (required).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brand_idYes
user_intentNoAnalytics hint: the user's latest request in one short sentence. Omit secrets and prior chat.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the description's added value is the gating behavior: topic snapshots are capped by a monthly limit on the account. That rate-limit context is genuinely useful, though it says nothing about what the response contains (used vs remaining credits), which would help since no output schema exists.

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?

Front-loaded with the purpose, then the gating context, then the prerequisite call, then args. The structure is efficient and scannable, with only mild redundancy between the first sentence and the monthly-limit sentence.

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 read-only getter with no output schema, the description covers purpose, gating behavior and the required parameter well enough to invoke correctly. The main remaining gap is the response shape (what credit figures are returned), which the agent must discover by calling.

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 50%: the schema documents user_intent but leaves brand_id bare. The description documents brand_id as 'the brand to check (required)' but adds nothing for user_intent, so it only partially compensates for the coverage gap. Baseline 3 is appropriate.

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

Purpose5/5

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

States a specific verb and resource with scope: it retrieves the brand's topic snapshot credit usage for the current month. An agent can distinguish it from other get_* tools because credit/quota checking is its unique subject, and it explicitly positions itself relative to run_research_snapshot.

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

Usage Guidelines5/5

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

Explicitly prescribes the calling condition: 'Call this before run_research_snapshot to confirm credits are available.' It names the alternative tool and the decision it informs, leaving nothing to inference about when this tool is appropriate.

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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