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Log several time entries

time.log_entries_batch
Idempotent

Use this when logging multiple entries at once: an end-of-day recap, a pasted list, or after time.propose_entries has been confirmed. Each entry is validated independently; partial success is reported per row with the same statuses as time.log_entry. Do not call before the user has confirmed proposed entries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entriesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already indicate this is a write operation with idempotentHint=true, but the description adds useful behavioral detail: each entry is validated independently, partial success is reported per row, and statuses match time.log_entry. It does not add details about auth requirements or output shape, but the added behavior exceeds what annotations alone provide.

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 four sentences, each earning its place: when to use it, behavioral guarantees, error-reporting model, and an explicit prohibition. It is front-loaded with the most decision-relevant information and contains no filler.

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 tool's complexity (batch write, 10-field entry schema, no output schema), the description covers the key operational concerns: use cases, partial failures, and confirmation prerequisite. It does not describe the exact success/error response format, but it references statuses from time.log_entry, which is reasonably complete for invocation.

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?

Schema description coverage is 0%, so the description should compensate by explaining the entries parameter, but it does not. However, the schema's nested property descriptions are thorough, so the agent can still understand fields like start, duration, and project. The description itself contributes little to parameter semantics.

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 a specific verb and resource: 'logging multiple entries at once.' It also gives concrete use cases (end-of-day recap, pasted list, after confirmation of proposed entries), which clearly distinguishes it from the single-entry time.log_entry and the proposal-stage time.propose_entries siblings.

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?

It explicitly states when to use the tool ('Use this when logging multiple entries at once') and provides a direct exclusion: 'Do not call before the user has confirmed proposed entries.' This gives the agent actionable selection criteria without needing to inspect siblings.

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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