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Record agent action

record_agent_action

Append one signed tool_call -> tool_result pair to a tamper-evident ledger. Call it after any consequential tool invocation — a payment, an outbound email, a write into a customer system — so there is a hash-chained record of what the agent asked for and what came back, signed at write time. Pass a stable run_id to keep an entire agent run in one chain, and parent_sha256 to link records explicitly; read the result back with get_provenance_chain. Returns { record_id, content_sha256, signature, recorded_at, verify_url }. Requires a Kamy API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolYesName of the tool that was invoked.
run_idNoYour identifier for this agent run. Reuse it across records to build one chain.
serverYesIdentifier of the MCP server (or tool provider) the call went to, e.g. 'kamy'.
statusNoOutcome of the call. Defaults to ok.
tool_callNoThe request you sent — typically the arguments object, verbatim.
latency_msNoWall-clock duration of the call.
tool_resultNoThe result you received back, verbatim.
parent_sha256Nocontent_sha256 of the previous record in this run, to link the chain explicitly.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate this is not read-only, not destructive, and not open-world. The description adds value by disclosing the tool's write behavior (signed hash-chained record), authentication requirement ('Requires a Kamy API key'), and the return format details. However, it doesn't explicitly state if the tool is idempotent or how errors are handled.

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 earning its place: first defines the core action, second gives usage context, third explains key parameters and return value, fourth states authentication. No filler or repetition.

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 an 8-parameter, 2-required tool with full schema coverage and no output schema, the description is complete. It covers what the tool does, when to use it, how to use it (key parameters), what it returns, and its authentication needs. The return format is described sufficiently without an output schema.

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 adds context for run_id (using across records) and parent_sha256 (to link explicit chain), but it doesn't add meaning beyond the schema descriptions for other parameters. The enum for status is already clear in the schema.

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 uses a specific verb ('append') and resource ('tool_call -> tool_result pair to a tamper-evident ledger'), clearly distinguishing the tool from its siblings. It explicitly states the tool is for recording signed pairs after consequential tool invocations, which is unique among sibling tools like ask_kamy or trace_record.

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 gives explicit when-to-call guidance: 'Call it after any consequential tool invocation — a payment, an outbound email, a write into a customer system'. It also provides a clear when-not-to-call hint by implication (only for consequential actions) and references a sibling, get_provenance_chain, for reading results back.

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.