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Who you are

get_viewer
Read-only

Report who the person is currently acting for on Gemalli: role, interface language and, when signed in, the company they represent and their plan. An anonymous person is a valid answer and comes back as a guest, not an error. If the person signed in after talking to you anonymously, previous_guest carries the identifier of that earlier conversation so you can carry the history over, and linked_at separates a link you have not seen before from one you have already handled. credits tells whether platform credits are on (enabled), the balance and total granted when signed in, buy_url (null means no payment page yet: send the person to Office Live) and action_costs, the only map from a tool to its action and price: call something free only when its credits is 0, never offer an action whose credits is null. wallets carries one entry per credit kind with its balance and low: low true means that kind is running out and the panel should show the remaining-credits note. Every paid answer carries the same wallets, freshly counted after the charge — prefer those over this first reading. Never returns another party's data and never returns secrets.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Annotations only cover the safety profile (read-only, not destructive, not open-world); the description goes far beyond them, disclosing that anonymous access is a valid non-error result, that previous_guest/linked_at carry conversation-link semantics, that buy_url null means no payment page, that credits null must never be offered, and that it never returns another party's data or secrets.

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

Conciseness3/5

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

Front-loaded with the purpose, and most sentences do work since there is no output schema to carry the return-value detail. However it is a single dense run-on paragraph mixing identity, billing, credits and privacy semantics with no structural separation, making it harder to scan than it needs to be.

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?

With no output schema, the description carries the full burden of explaining return values, and it does so thoroughly (role, language, company, plan, guest/previous_guest, linked_at, credits, buy_url, action_costs, wallets and the low flag). Nothing an agent needs to interpret the response 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 takes no parameters and schema coverage is 100%, so the baseline is 4. There is nothing for the description to disambiguate beyond confirming the call takes no input.

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 resource (the current viewer's identity, role, interface language, company and plan) and is clearly distinguishable from all siblings, which are feedback, product, sanction and quote tools. An agent can tell what this returns without opening any schema.

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?

Gives strong guidance on interpretation and downstream behavior ('call something free only when its credits is 0', 'prefer those [fresh wallets] over this first reading', 'send the person to Office Live' when buy_url is null), which implicitly tells the agent when this reading applies. It lacks an explicit 'call this when...' trigger, but the routing conditions relative to other answers are clear.

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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