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chatlog_write

Append a chat turn to the chat log with required provenance. Async-queued write returns the row ID immediately.

Instructions

Append one chat turn to the chat log DB. Provenance (host_agent, provider, model_id, conversation_id) is required. Writes are async-queued — returns the row id immediately.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
roleYes
contentYes
timeoutNo
user_idNo
agent_idNo
cost_usdNo
databaseNo
metadataNo{}
model_idYes
providerYes
tokens_inNo
host_agentYes
latency_msNo
tokens_outNo
turn_indexNo
conversation_idYes
Behavior3/5

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

The description discloses that writes are async-queued and return the row id immediately, which is useful. However, it does not cover potential failure modes, idempotency, or other side effects. With no annotations, the description carries the full burden but only partially fulfills it.

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 concise with two sentences, the first stating the core purpose and the second adding key behavioral details. It is front-loaded and efficient, though it could briefly mention a few more parameter details without becoming verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (16 parameters, no output schema, no annotations), the description is too sparse. It covers the basic function and async nature but fails to explain the majority of parameters or provide context about error handling, return values beyond row id, or usage scenarios.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must compensate but only mentions the six required parameters by name without explaining their semantics or any optional parameters. It adds minimal meaning beyond the schema titles.

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 action ('append one chat turn') and the resource ('chat log DB'), and distinguishes it from sibling tools like chatlog_search (read) and chatlog_status (check status) by focusing on writing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context by noting the required provenance fields and async-queued behavior, but does not explicitly state when to use this tool over alternatives or when not to use it. No exclusions or alternatives are mentioned.

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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