Yc Rejection

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

The description discloses key behavioral traits: Pipeworx picks the right tool, fills arguments, and returns the result. This explains the automatic routing and argument filling. With no annotations provided, the description carries the burden and does well.

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 at two sentences plus examples. It is front-loaded with the core purpose, then expands with examples. 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 complexity (simple interface with one parameter, no output schema), the description is complete. It explains what the tool does and how it works. However, it could mention that there is no guarantee of correctness or source transparency.

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 the schema already documents the single 'question' parameter. The description adds context that the question should be in natural language and provides examples, which is helpful but not strictly necessary beyond 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: asking natural language questions to get answers from the best data source. It uses specific verbs like 'ask' and 'get an answer', and distinguishes from sibling tools that are for tool discovery, memory, or rejection handling.

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 clear usage context: 'No need to browse tools or learn schemas — just describe what you need.' It gives examples of what to ask. However, it doesn't explicitly say when NOT to use this tool or mention alternatives among siblings.

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?

Although no annotations are provided, the description adds behavioral context: it returns 'the most relevant tools with names and descriptions' and acts as a search/filter mechanism. It does not mention any destructive effects or side effects, which is appropriate for a search tool. A small gap is that it doesn't clarify if the tool requires any authentication or has rate limits, but given the simplicity of a search, this is acceptable.

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 three sentences, each adding value: first states the action, second describes output, third gives usage guidance. No filler or redundancy.

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 complexity (simple search, two parameters, no output schema, no annotations), the description is fairly complete. It explains the purpose, when to use, and what to expect. It could mention whether results are ordered by relevance, but that is implied. Overall, adequate for an agent to use 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 description coverage is 100%, so baseline is 3. The description does not add additional meaning beyond the schema; it provides a high-level use case ('analyze housing market trends') but no further details on parameter semantics. Since the schema already covers both parameters adequately, this score 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 uses a specific verb+resource ('Search the Pipeworx tool catalog') and clearly states the tool's purpose: returning relevant tools with names and descriptions. It also distinguishes itself from siblings by positioning as the first call to find tools among 500+ available.

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 states when to use this tool: 'Call this FIRST when you have 500+ tools available and need to find the right ones for your task.' This provides clear context and differentiates from siblings that likely serve different purposes.

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 the description must carry full burden. It does not disclose whether deletion is irreversible, if any confirmation is needed, or if associated data (e.g., memory metadata) is also removed. The description is minimal.

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 sentence, front-loaded with the action and resource. It is concise and efficient, with no wasted words.

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 required param, no output schema), the description is functional but lacks behavioral details (e.g., error cases, idempotency). An agent might need to infer what happens if the key does not exist.

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% with a single parameter described as 'Memory key to delete'. The description adds no extra meaning beyond what the schema already provides. 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') and the resource ('stored memory by key'). It effectively distinguishes from siblings like 'remember' (create) and 'recall' (retrieve), though it does not explicitly differentiate from 'forget' itself.

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?

No explicit guidance on when to use vs. alternatives, but the purpose is clear enough that an agent can infer it's for deletion. The sibling context (recall, remember) provides implicit differentiation.

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 the burden. It reveals that omitting key lists all, which is a behavioral trait. However, it does not state if retrieval is read-only, if it affects the memory state, or any side effects.

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 action and key behavior. Every word is necessary and no filler. Perfectly concise.

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 optional parameter, no output schema), the description is complete enough. It explains the two modes of use. No further detail is needed for a straightforward retrieval 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 coverage is 100% for the single parameter 'key', with a clear description in the schema. The description adds meaning by explaining the effect of omitting the key (list all), which is beyond the schema's 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 retrieves a memory by key or lists all memories if key is omitted. It distinguishes from siblings by mentioning 'previously stored memory' and 'earlier in the session', which is distinct from remember (store) 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?

The description tells when to use (retrieve context saved earlier) and implies when not (omit key to list all). It does not explicitly mention alternatives or when to avoid, but the context is clear enough for an agent.

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?

Discloses persistence difference between authenticated (persistent) and anonymous (24-hour) sessions. With no annotations, the description carries full burden and does well, though it could mention if values overwrite on same key or if there are size limits.

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 serving a clear purpose: what the tool does, when to use it, and persistence behavior. No wasted words.

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 simple 2-parameter tool with no output schema, the description is thorough. It explains persistence, which is critical for session memory. Could add a note about overwriting behavior or maximum key/value length.

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%, and the description adds context by giving examples of key values (subject_property, target_ticker) and explaining the value can hold any text. This goes beyond the schema's generic descriptions.

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?

Clearly states it stores a key-value pair in session memory, with specific use cases like saving findings, preferences, or context. Distinguishes from sibling tools like recall (retrieve) and forget (delete).

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 when-to-use: 'save intermediate findings, user preferences, or context across tool calls'. Also explains persistence behavior for authenticated vs anonymous sessions, which helps the agent decide usage.

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