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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

A4.7/5.0
Behavior4/5

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

Annotations already signal mutability (readOnlyHint: false, destructiveHint: false), so the description doesn't need to repeat that. The description adds behavioral context: the ledger is tamper-evident, records are hash-chained, and results include a verify_url. It also discloses a prerequisite (requires a Kamy API key). The only gap is no mention of rate limits or idempotency, but the behavioral coverage is strong.

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 tightly written—three sentences, no filler. The first sentence delivers the core action and purpose, the second provides usage scenarios and chaining mechanics, and the third lists return fields and a prerequisite. Every sentence earns its place.

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?

Given the tool's moderate complexity (8 params, 2 required, no output schema), the description covers all essential aspects: what the tool does, when to use it, how to structure the chain, what it returns, and a prerequisite. The agent has enough context to invoke this correctly without referencing external documentation.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds value by explaining why certain parameters matter beyond their schema types: run_id is for chaining records, parent_sha256 explicitly links the chain, tool_call and tool_result should be verbatim. This is substantial added context that helps the agent use the tool correctly.

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 verb ('append'), the resource ('signed tool_call -> tool_result pair to a tamper-evident ledger'), and distinguishes the tool from siblings (e.g., get_provenance_chain for reading back, verify_attestation for verification). It explicitly says when to call it—after any consequential tool invocation—and lists non-obvious use cases (payment, email, write).

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 provides explicit when-to-use guidance: after any consequential tool invocation. It names a specific sibling (get_provenance_chain) for reading back results, which gives the agent an alternative. It also explains how to structure calls (stable run_id, parent_sha256 to link records), leaving no ambiguity.

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

A4.2/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose with detailed descriptions that differentiate similar tools (e.g., render_pdf vs render_async vs render_batch, create_signature_request vs create_envelope). No two tools overlap in a way that would cause confusion.

Naming Consistency5/5

All tool names follow a consistent lower_snake_case verb_noun pattern (e.g., attest_artifact, convert_document, list_renders). No mixing of conventions or ambiguous verb choices.

Tool Count4/5

47 tools is high but reflects the broad scope of the platform (document generation, signing, auditing, scheduling, webhooks, verification). Some informational tools could be merged, but the count is still reasonable for the domain.

Completeness3/5

The tool set covers the core document lifecycle well but has notable gaps: no tool to delete renders, no tool to void/cancel signature requests, and no CRUD for templates (only list and schema). The inability to pause schedules via MCP is also a gap.

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