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Kamy

by dev.kamy

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Read-only

Query this account's Kamy Trace records, newest first, filtered by feature, status, provider, tag, or time window. Returns record metadata — model, tokens, latency, status, content hash, recorded_at — plus next_cursor for paging; it does not return the stored prompt and output bodies. Use it to answer questions like 'how many flagged calls last week?' or to locate a specific record's id before opening it in the dashboard. Read-only. Requires a Kamy API key with the trace:read scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNoReturn records whose tags array contains this tag.
limitNoPage size, 1-100. Default 25.
sinceNoISO-8601 timestamp, inclusive lower bound.
untilNoISO-8601 timestamp, exclusive upper bound.
cursorNoPass the `next_cursor` from the previous response to fetch the next page.
statusNoExact-match filter on outcome.
featureNoExact-match filter on the feature label.
providerNoExact-match filter on provider.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description's read-only mention adds little beyond them. However, it adds valuable context about auth requirements (requires Kamy API key with trace:read scope) and pagination (next_cursor, no return of prompt bodies), which annotations don't cover. The description aligns with annotations.

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 concise: four sentences, each adding value. It front-loads the core function (query traces with filters, newest first), then details return data and exclusions, provides usage examples, and ends with access requirements. No wasted words.

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?

Given the 8 parameters with 100% schema coverage but no output schema, the description adequately describes output fields and pagination. It lacks details on default ordering (newest first is mentioned), but covers key behavioral aspects. The tool is a filtered list query with good annotations, so completeness is solid.

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%, so the baseline is 3. The description lists filter dimensions (feature, status, provider, tag, time window) and mentions returned fields (model, tokens, status, etc.), but doesn't add significant meaning beyond what the schema already provides for each parameter. It provides a useful high-level summary but doesn't deepen parameter understanding.

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 states the tool queries Kamy Trace records with specific filters (feature, status, provider, tag, time window) and returns metadata. It clearly distinguishes itself from sibling tools like trace_record (which likely returns a single record) and other sibling tools that deal with documents, signatures, or attestations.

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?

The description explicitly says when to use it (e.g., 'how many flagged calls last week?' or locating a record ID before opening the dashboard) and implies when not to (it does not return stored prompt/output bodies). It also states it is read-only and requires a specific API key scope, providing clear context for appropriate use.

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