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productive_log_time

Log worked hours to Productive.io projects with fuzzy project matching, optional notes, and date specification.

Instructions

Create a time entry on a Productive.io project.

Args: project: Project name (fuzzy match, e.g. "1099 Acme") or numeric id. hours: Hours worked (float, e.g. 2.5). Converted to minutes internally. note: Optional description of the work. date: ISO date (YYYY-MM-DD). Defaults to today. service_hint: Optional service name/id if the project has multiple services. Once chosen, remembered as the project default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectYes
hoursYes
noteNo
dateNo
service_hintNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description discloses key behaviors: fuzzy matching for project, hours conversion, defaults for date, and the remembered service_hint trait. It does not cover auth requirements or rate limits, but these are less critical for a creation tool.

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 concise: a clear one-line purpose followed by a well-structured bullet list of parameters. Every sentence adds value without redundancy.

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 number of parameters and absence of annotations, the description is thorough. It covers all parameters, explains defaults, conversions, and a behavioral nuance (service_hint remembered). The output schema exists to handle return values, so the description is complete.

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

Parameters5/5

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

Schema description coverage is 0%, so the description fully compensates by explaining each parameter's meaning, format (ISO date, float), conversion (hours to minutes), default behavior (date defaults to today), and special behavior (fuzzy match, service_hint remembered).

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 'Create a time entry on a Productive.io project.' with a specific verb and resource. It distinguishes from sibling tools like productive_update_time_entry and productive_delete_time_entry.

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 purpose is clear (creating a time entry), and the description implies when to use it. However, it does not explicitly state when not to use or provide alternatives.

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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