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Kamy

by dev.kamy

Get provenance chain

get_provenance_chain
Read-only

Replay everything recorded under one run_id — artifacts from attest_artifact and calls from record_agent_action — in order, with each record's link to its parent hash. Use it to answer 'what did this agent actually do, and in what sequence?' during an incident review, a handover, or an audit. Returns { run_id, chain_intact, records: [...] }, where chain_intact is the server's verdict on whether the parent-hash links are unbroken across the run. Read-only. Requires a Kamy API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
run_idYesThe run_id you passed to attest_artifact / record_agent_action.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and destructiveHint, so the 'Read-only' line is redundant. However, the description adds valuable context beyond the annotations: results are ordered, chain_intact represents the server's verdict on hash-link integrity, and an API key is required. This is more depth than typical read-only tools.

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?

Four sentences, each adding critical information: the action, the data sources, the use case, the return shape, the chain_intact meaning, read-only status, and auth requirement. Nothing is redundant or fluff; it is front-loaded with the core behavior.

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?

Despite lacking an output schema, the description explicitly returns { run_id, chain_intact, records: [...] } and explains chain_intact. It covers purpose, usage context, parameter origin, auth requirement, and read-only nature. For a single-parameter read-only tool with good annotations, this is fully sufficient.

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 coverage is 100%, with run_id already described as 'The run_id you passed to attest_artifact / record_agent_action.' The description adds minimal new semantics—it reinforces that run_id is a single ID and ties it to prior calls, but this largely mirrors the schema. 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?

The description clearly states the tool replays all records under a run_id, specifically artifacts from attest_artifact and calls from record_agent_action, in order with parent-hash links. This distinguishes it from siblings like trace_record or trace_search by focusing on a single run's full provenance chain.

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 explicitly says to use this tool when you need to answer 'what did this agent actually do, and in what sequence?' during incident review, handover, or audit. It gives concrete use cases but does not mention when not to use it or name explicit alternatives, so it stops 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

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