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Kamy

by dev.kamy

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Read-only

Read everything about the authenticated Kamy account in one call: profile, plan and plan status, the plan's limits (renders per month, API keys, seats, custom templates, overage pricing, priority queue), month-to-date render usage, and whether documents rendered on this plan carry Kamy's own watermark. This is the only tool that answers any of those questions — there is no separate quota tool. Call it before render_batch, create_schedule, or any long series of renders: usage.renders.remaining is how many the API will still accept, and every render tool fails with 402 QUOTA_EXCEEDED once it hits zero, a failure nothing can recover from within the same calendar month. quota and remaining are null on unmetered plans, which means unlimited, not zero. Also check watermarkPolicy.appliedToRenders before generating something the user intends to send on: it is true on the free plan and cannot be turned off per render. Read-only, spends nothing, and works with any valid API key regardless of its scopes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already indicate read-only and non-destructive. The description adds critical behavioral context: that render tools fail with 402 QUOTA_EXCEEDED when quota is zero, that quota/remaining are null on unmetered plans (meaning unlimited), and that watermarkPolicy.appliedToRenders must be checked. Also notes it works with any valid API key regardless of scopes.

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 relatively long but every sentence adds value. It is front-loaded with the primary purpose. Could be slightly trimmed, but the density of useful information justifies the length.

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 fully explains the return values: profile, plan, plan status, limits, usage, watermark. It covers edge cases (null on unmetered plans, watermark behavior) and explains the critical usage context for checking remaining quota. Complete for a complex, data-rich tool.

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?

No parameters, so baseline is 4. The description compensates by explaining what the tool returns, but no parameter documentation is needed.

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?

The description clearly specifies that it reads everything about the authenticated Kamy account: profile, plan, limits, usage, and watermark. It explicitly states it is the only tool answering these questions, distinguishing it from all sibling tools.

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?

Provides clear when-to-use guidance: call it before render_batch, create_schedule, or any long series of renders to check remaining quota. Explains consequences of not checking (402 QUOTA_EXCEEDED). Does not explicitly list when not to use, but the context is strong.

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

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct action or resource with minimal ambiguity. For example, `render_pdf`, `render_docx`, `render_xlsx`, and `pptx` are clearly different output formats, while `merge_pdfs`, `split_pdf`, and `edit_pdf` target different PDF operations. The signature tools (`create_signature_request`, `get_signature_request`, etc.) are also clearly separated by lifecycle stage. No two tools appear to do the same thing.

Naming Consistency5/5

Tool names follow a highly consistent `verb_noun` pattern throughout, such as `create_signature_request`, `get_signature_request`, `list_signature_requests`, and `remind_signature`. This pattern is applied uniformly across all major domains (render, signature, template, webhook, trace), making the API predictable and easy for an agent to navigate.

Tool Count4/5

With 59 tools, this is a large surface area, but it is justified by the breadth of functionality: document rendering in multiple formats, e-signatures, template management, webhooks, scheduling, and a crypto/audit trail. While large, each tool has a distinct purpose, and the count feels appropriate for the scope of a comprehensive document automation API. A surface this large risks being overwhelming, but the internal organization is logical.

Completeness5/5

The tool surface is remarkably complete, covering the full lifecycle for multiple domains. For e-signatures, there are tools for CRUD (requests, templates), sending (individual, bulk, envelope), monitoring (get, list), reminders, and certificates. For documents, it covers creation, conversion, editing, merging, splitting, and verification. The inclusion of utility tools like `get_started`, `validate_payload`, and the audit trail tools further solidifies this as a well-considered, production-ready API surface.

Resources