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G-Hensley
by G-Hensley

extract_story_ideas

Mines journal entries to find story-worthy moments for LinkedIn Personal Stories, using optional date range filters.

Instructions

Identify story-worthy moments from journal entries for LinkedIn Personal Stories

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
from_dateNoStart date (YYYY-MM-DD). Default: 30 days ago
to_dateNoEnd date (YYYY-MM-DD). Default: today
Behavior2/5

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

With no annotations, the description bears full responsibility for behavioral disclosure. It states the tool 'identifies' story-worthy moments, suggesting a read operation, but it does not describe side effects, permissions needed, or return format. The lack of output schema makes the missing description of output a notable gap.

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 a single, efficient sentence that front-loads the verb. It contains no wasted words, but some may argue it could be slightly expanded to include output type without losing conciseness.

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 lack of annotations and output schema, and the presence of many sibling tools, the description is incomplete. It does not specify what the tool returns (e.g., list of story titles or paragraphs) or any processing constraints, leaving the agent with insufficient context for correct invocation.

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 coverage is 100% because both parameters (from_date, to_date) have descriptions in the input schema. The tool description adds no additional meaning beyond the schema, so baseline 3 is appropriate.

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 tool identifies story-worthy moments from journal entries for LinkedIn Personal Stories. It uses a specific verb 'identify' and resource 'story-worthy moments', distinguishing it from sibling tools like add_idea (which adds ideas) or search_journal (which searches entries).

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 implies usage when the user wants to find LinkedIn story ideas from journal entries, but it does not explicitly state when to use this tool versus alternatives like get_content_ideas or add_idea. No exclusions or when-not-to-use guidance is provided.

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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