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Glama

Account status & quota

get_account_status
Read-only

Your Ranklogs plan/tier, lookups balance and monthly allowance, and which Ranklogs features are enabled.

This is the quota pre-check tool: check here before planning research-heavy work. Free — calling it never consumes lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
planYes
lookupsYes
verdictYes
features_enabledYes
lookups_remainingYes

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already mark it as readOnly, and the description adds a meaningful behavioral detail beyond that: 'Free — calling it never consumes lookups' and clarifies it provides quota balance and feature flags. This gives the agent a clearer model of side effects and cost, though it doesn't discuss authorization or other advanced behavior.

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?

The description is compact, front-loaded, and every sentence earns its place. The first sentence explains what the tool returns, and the second gives the usage context and cost guarantee. There is no filler or repetition of schema/annotation information.

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

Completeness5/5

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

For a zero-parameter, read-only account status tool with an output schema and clear annotations, the description is complete. It tells the agent what data is available, when to call it, and that it has no quota cost. Nothing necessary for correct invocation is missing.

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 has zero parameters and the schema coverage is 100%, so there is no parameter documentation burden. The description adds useful context about what data the tool surfaces (plan, balance, allowance, features), which is more than the empty schema provides.

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 clearly states the tool's purpose: it reports the Ranklogs plan/tier, lookups balance, monthly allowance, and enabled features. It goes beyond a generic label by framing itself as the 'quota pre-check tool,' but it does not explicitly differentiate itself from sibling tools by name.

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 description gives explicit when-to-use guidance: 'check here before planning research-heavy work.' It also adds a practical reassurance that calling it never consumes lookups. It does not mention when not to use it or name alternative sibling tools, so it falls short of a 5.

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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TDQS

A3.7/5.0
Disambiguation3/5

Most tools are distinct get_* analytics, but several overlap in purpose: get_ai_visibility vs get_share_of_voice are easy to confuse, and get_project_overview/get_content_action_plan/get_audit_summary all offer prioritized fixes. Descriptions help, but an agent could easily misselect for a generic 'what should I fix?' query.

Naming Consistency5/5

All names follow a consistent snake_case verb_noun pattern (add_, get_, generate_, list_, analyze_, research_), and the get_* prefix dominates read operations. Even win_prompt is a verb_noun and fits the style.

Tool Count2/5

27 tools is past the 25+ threshold and creates a heavy selection surface for an agent. While the SEO/AI-visibility domain is broad, many tools return overlapping 'health/fix/visibility' data and the set would benefit from consolidation.

Completeness3/5

Core workflows (projects, keywords, content briefs, audits, backlinks, AI visibility) are covered, but lifecycle gaps exist: keywords and AI prompts can be added but not removed, there is no list-AI-prompts tool, and no project creation/update is exposed. These are workable but notable missing operations.

Resources