timezone

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: the tool interprets natural language questions, selects appropriate data sources, fills arguments automatically, and returns results. However, it doesn't disclose potential limitations like rate limits, authentication needs, or error conditions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly front-loaded with the core functionality in the first sentence, followed by supporting details and concrete examples. Every sentence adds value without redundancy, making it efficient and well-structured for quick understanding.

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

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

For a single-parameter tool with no output schema and no annotations, the description provides good context about what the tool does and how to use it. The examples help illustrate the range of possible questions. However, without information about return formats or error handling, there's a minor gap in completeness.

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

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

Schema description coverage is 100%, so the schema already documents the single 'question' parameter. The description adds minimal value beyond the schema by emphasizing 'natural language' and providing examples, but doesn't explain parameter constraints or format requirements beyond what's in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('ask a question', 'get an answer') and resources ('best available data source'), distinguishing it from sibling tools like time converters or memory tools. It explicitly explains that Pipeworx handles tool selection and argument filling, which is unique among the listed siblings.

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

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

The description provides explicit guidance on when to use this tool ('just describe what you need') and when not to use alternatives ('no need to browse tools or learn schemas'). It contrasts this with the implied need for more technical approaches in other tools, making the usage context clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the search functionality and return format (tools with names and descriptions), but doesn't mention performance characteristics, error handling, authentication requirements, or rate limits. It provides basic operational context but lacks detailed behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly concise with two sentences that each serve distinct purposes: the first explains what the tool does, the second provides crucial usage guidance. Every word earns its place, and the most important information (the tool's core function) is front-loaded.

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

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

Given the tool's moderate complexity (search functionality with 2 parameters), 100% schema coverage, and no output schema, the description provides good contextual completeness. It explains the tool's purpose, when to use it, and the general return format. The main gap is the lack of output schema which would help understand the exact response structure, but the description compensates reasonably well by mentioning what gets returned.

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

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

The schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema - it mentions searching by describing needs which aligns with the 'query' parameter, but provides no additional syntax, format, or usage details. This meets the baseline expectation when schema coverage is complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('search', 'returns') and resource ('Pipeworx tool catalog'), distinguishing it from sibling tools that handle time-related functions. It explicitly mentions searching by describing needs and returning relevant tools with names and descriptions.

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

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

The description provides explicit guidance on when to use this tool ('Call this FIRST when you have 500+ tools available and need to find the right ones for your task') and distinguishes it from alternatives by focusing on tool discovery rather than time conversion or listing functions like the sibling tools. It clearly establishes the primary use case scenario.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Delete' implies a destructive mutation, the description doesn't specify whether this operation is reversible, what permissions are required, what happens on success/failure, or any rate limits. For a destructive tool with zero annotation coverage, this is a significant gap in behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. It's appropriately sized for a simple tool and front-loads the core action ('Delete'), making it easy to parse quickly.

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

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

For a destructive tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'stored memory' means in this context, what format the key should be in, what happens after deletion, or any error conditions. Given the complexity of a deletion operation, more context is needed.

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

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

The schema description coverage is 100%, with the parameter 'key' fully documented in the schema as 'Memory key to delete'. The description adds no additional semantic meaning beyond what the schema provides, so it meets the baseline score of 3 where the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Delete') and resource ('stored memory'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'recall' (which likely retrieves memories) or 'remember' (which likely stores memories), missing an opportunity for sibling differentiation.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing memory key), exclusions, or how it relates to sibling tools like 'recall' or 'remember', leaving the agent with no contextual usage information.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full burden. It describes the tool's behavior (retrieval or listing based on key presence) and mentions persistence across sessions, which adds useful context. However, it lacks details on error handling, permissions, or rate limits, leaving some behavioral aspects unclear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, with two sentences that efficiently convey purpose, usage, and context. Every sentence earns its place by adding value, with no redundant or vague phrasing.

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

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

Given the tool's moderate complexity (1 optional parameter, no output schema, no annotations), the description is mostly complete. It covers purpose, usage, and parameter semantics well, but lacks details on return values or error cases, which could be helpful for an agent.

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

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

Schema description coverage is 100%, so the schema already documents the 'key' parameter. The description adds semantic meaning by explaining that omitting the key lists all memories, which clarifies the parameter's optional nature and its effect on behavior, going beyond the schema's basic description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Retrieve a previously stored memory') and resource ('by key'), distinguishing it from sibling tools like 'remember' (store) and 'forget' (delete). It explicitly mentions retrieving context saved earlier, which clarifies the tool's purpose beyond just the name.

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

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

The description provides explicit guidance on when to use this tool vs. alternatives: 'Retrieve a previously stored memory by key, or list all stored memories (omit key).' It distinguishes between retrieval by key and listing all, and mentions context from earlier sessions, giving clear usage context without exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: the tool performs a write operation ('Store'), specifies storage duration ('persistent memory' vs. '24 hours'), and mentions session-based context. However, it lacks details on error conditions (e.g., key collisions, size limits) or response format, which would elevate it to a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose in the first sentence, followed by usage guidance and behavioral details in subsequent sentences. Each sentence adds value without redundancy (e.g., explaining persistence rules, use cases), and there is no wasted text. It efficiently conveys necessary information in three concise sentences.

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

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

Given the tool's moderate complexity (write operation with session-based persistence), no annotations, and no output schema, the description does well by covering purpose, usage, and key behavioral traits. However, it lacks details on error handling or return values, which would be helpful for an agent. It compensates partially but not fully for the absence of structured fields, keeping it from a perfect score.

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

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

Schema description coverage is 100%, with both parameters ('key' and 'value') well-documented in the schema (e.g., 'key' examples like 'subject_property', 'value' as 'any text'). The description adds minimal semantic context beyond the schema, such as implying the 'value' can include 'findings, addresses, preferences, notes', but this is redundant with the schema's 'any text' description. Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Store a key-value pair') and resource ('in your session memory'), distinguishing it from sibling tools like 'recall' (which retrieves) and 'forget' (which removes). It explicitly mentions what gets stored ('intermediate findings, user preferences, or context across tool calls'), making the purpose unambiguous and distinct from alternatives.

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

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

The description provides explicit guidance on when to use this tool: 'Use this to save intermediate findings, user preferences, or context across tool calls.' It also distinguishes it from sibling tools by implying alternatives (e.g., 'recall' for retrieval, 'forget' for deletion), and includes context about persistence ('Authenticated users get persistent memory; anonymous sessions last 24 hours'), which helps determine when it's appropriate based on session type.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.