Tarot Draw

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

No annotations are provided, so the description carries full burden. It discloses that the tool selects the best data source and fills arguments automatically, which implies some decision-making but does not detail limitations or behaviors like latency, scope of data sources, or potential errors. Still, it is mostly transparent for a high-level tool.

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 concise: three sentences plus examples. It is front-loaded with the main purpose and efficiently adds examples for clarity. Every sentence adds value.

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 simplicity (one parameter, no output schema), the description is sufficiently complete. It explains the input and the behavior. However, it lacks details on what happens if the tool cannot find an answer, but that is a minor gap for a high-level query tool.

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%, and the description adds meaning beyond the schema by explaining that the question should be in natural language and providing examples of what constitutes a valid request. This compensates for the schema's minimal 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 tool answers questions in plain English by selecting the best data source and filling arguments. It distinguishes itself from sibling tools by abstracting away tool selection and schema learning, which is a unique value proposition.

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 explains when to use this tool (when you need an answer from data without browsing tools) and provides examples. It does not explicitly exclude cases or mention alternatives, but the sibling tools are different enough (e.g., discover_tools, remember) that the usage context is 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?

Description clearly states it returns 'most relevant tools' and indicates it performs a search, which implies no side effects. No annotations provided, so the description carries full burden; it does well but could mention if it modifies state or has auth needs.

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?

Two sentences, front-loaded with purpose and then usage guidance. No wasted words; every sentence adds value.

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 simplicity (2 params, no output schema, no nested objects), the description is nearly complete. It explains what the tool does, when to use it, and how to call it. Could optionally mention that it searches tool descriptions, but not necessary.

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 coverage is 100%, so baseline is 3. The description provides a concrete example query ('analyze housing market trends') that adds meaning beyond schema. For the limit parameter, description doesn't add extra semantics beyond schema's default and max, but overall adds value.

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?

Description clearly states it searches the Pipeworx tool catalog by describing what you need, returning relevant tools with names and descriptions. It uses a specific verb ('search') and resource ('tool catalog'), and distinguishes from siblings by its unique discovery purpose.

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?

Explicitly says 'Call this FIRST when you have 500+ tools available and need to find the right ones for your task.' This provides clear when-to-use guidance and implies it's a prerequisite before other tools.

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?

No annotations provided, so description must cover behavioral traits. It says 'Delete' implying destructive action, but does not mention irreversibility, authorization needs, or what happens if key doesn't exist.

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?

Extremely concise: one sentence with essential info. No wasted words, but could be slightly improved by front-loading the key parameter importance.

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?

Tool is simple (1 param, no output schema), but description omits behavioral details (e.g., idempotency, error handling) that would help an agent use it correctly.

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 coverage is 100% (1 parameter described in schema). Description adds no additional meaning beyond schema, so baseline 3 is appropriate.

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 action ('Delete'), the resource ('stored memory'), and the identifier ('by key'). It distinguishes itself from sibling tools like 'recall' (retrieve) and 'remember' (store).

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 implies the tool is for deleting memories, but does not explicitly state when to use it vs. other tools or any prerequisites (e.g., memory must exist). Sibling tools are not mentioned.

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?

No annotations provided, so description carries full burden. Clearly states that the tool retrieves or lists memories, which is non-destructive. However, does not mention any side effects, rate limits, or whether listing returns full contents or just keys. Still, core behavior is transparent.

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?

Two sentences, no filler. Front-loaded with the core action. Every part adds value.

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 no output schema, description could explain what is returned (e.g., full memory content or just summary). But for a simple retrieval tool, the description is adequate. No annotations, but the tool is straightforward.

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 baseline is 3. Description adds value by clarifying the two usage modes (with key vs without) and the purpose of the parameter. Slightly redundant with schema but useful context for an agent.

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?

Description uses specific verbs ('retrieve', 'list') and a clear resource ('stored memory by key'). Distinguishes between single retrieval and listing all, and explicitly states the use case: 'retrieve context you saved earlier'. Differentiates from sibling tools like 'remember' and 'forget'.

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?

Provides explicit guidance on when to use the tool ('to retrieve context you saved earlier'), and describes two distinct usage modes (with key vs omit key). Does not mention alternatives but clearly implies this is for retrieval, not storage or forgetting.

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?

No annotations provided, so description carries full burden. It discloses persistence behavior: authenticated users get persistent memory, anonymous sessions last 24 hours. This adds important context beyond basic store operation.

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?

Three sentences, each purposeful: function, use case, persistence details. No wasted words, well-structured.

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 simple schema (2 string params), no output schema, and no nested objects, the description is complete. It covers what, why, and behavioral notes, leaving no gaps.

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 baseline is 3. Description adds value by explaining the purpose of stored data (findings, preferences, context) and providing example keys, enhancing agent understanding of parameter usage.

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 states the tool stores a key-value pair in session memory, specifying it saves findings, preferences, or context. It clearly differentiates from sibling tools like 'forget' and 'recall' by focusing on storage.

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 gives clear usage: save intermediate findings, preferences, context. It implies use across tool calls but does not explicitly state when not to use it or compare with alternatives.

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