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

The description explains that Pipeworx picks the right tool, fills arguments, and returns the result, which gives insight into its autonomous behavior. Since no annotations are provided, the description carries the full burden; it does a good job of explaining what the tool does internally, but it could add more detail about potential limitations or edge cases.

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 (four sentences) and front-loaded with the core purpose. It includes examples to clarify usage. However, the last sentence listing examples could be slightly trimmed or integrated, but overall it is well-structured and informative without 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 that there is only one parameter and no output schema, the description is fairly complete. It explains the tool's purpose, behavior, and provides examples. It could be improved by mentioning the type of output (e.g., 'returns a text answer') or potential delays, but overall it covers the essential information for an AI agent to 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% (only one parameter 'question'), and the description adds some meaning by stating that the question should be in plain English and providing examples. However, it does not elaborate on any constraints on the question (e.g., language, complexity) beyond what the schema already implies. Baseline 3 is appropriate since schema coverage is high and description adds moderate 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?

The description clearly states that the tool accepts a plain English question and returns an answer from the best available data source. It distinguishes itself from sibling tools by emphasizing that the user does not need to browse tools or learn schemas, which is a unique capability compared to the other tools that are more direct or memory-related.

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 examples of appropriate usage (e.g., 'What is the US trade deficit with China?') and implies that the tool is for general questions where the best data source is uncertain. However, it does not explicitly state when NOT to use it or mention alternative tools for specific cases, such as when the user already knows which tool to use.

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 were provided, so the description must carry the burden. It discloses return data types and resource URIs, but lacks details on authentication, rate limits, or error behavior. The read-only nature is implied but not explicit.

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 two sentences, front-loaded with the primary action, and includes all essential information without 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?

Despite lacking an output schema, the description explains that the tool returns 'paired data + pipeworx:// resource URIs' and details type-specific fields. It also notes the efficiency benefit. Could expand on error handling or limitations, but overall adequate.

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 input schema covers both parameters with 100% description coverage, but the description adds valuable context: it explains that 'values' are tickers/CIKs for companies and drug names, and specifies the 2-5 range, which surpasses the schema's minimal 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?

The description explicitly states 'Compare 2–5 entities side by side in one call' and distinguishes two entity types with specific data fields. It also notes it replaces 8-15 sequential calls, clearly differentiating it from sibling tools.

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 clearly implies when to use (for comparative data across multiple entities) and highlights efficiency gains. It does not provide explicit when-not-to-use guidance, but the 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?

No annotations are provided, so the description carries the full burden. It discloses the search and return behavior but does not mention any side effects, idempotency, or limitations (e.g., whether the catalog is static or updates). A 3 is appropriate as it is clear but lacks depth for a search tool with no annotations.

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 two sentences with no wasted words. It front-loads the core action and result, then adds a clear usage directive. Every sentence is purposeful.

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 (2 params, no output schema, no nested objects), the description is complete. It explains the search function, return type, and optimal usage context. However, it could mention that the tool is read-only (though not required) but the current content is sufficient for a search 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%, so the baseline is 3. The description does not add additional meaning beyond the schema's parameter descriptions, which already define 'query' and 'limit' well. The description's mention of 'default 20, max 50' for limit is already in the schema, so no extra 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?

The description clearly states the tool's purpose: 'Search the Pipeworx tool catalog by describing what you need. Returns the most relevant tools with names and descriptions.' It specifies the verb (search), resource (tool catalog), and result (relevant tools). It also differentiates from siblings by emphasizing discovery among 500+ tools.

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 explicitly tells when to use: 'Call this FIRST when you have 500+ tools available and need to find the right ones for your task.' This provides clear guidance on invocation timing and context, effectively distinguishing from sibling tools that serve other 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 are provided, so the description carries full burden. It states the tool deletes, but does not disclose whether deletion is permanent, reversible, or if it requires special permissions. No mention of side effects or 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?

The description is a single, concise sentence that directly states the purpose. No filler words. Could be slightly improved by adding a use case, but it's already efficient.

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 simple nature of the tool (1 parameter, no output schema, no nested objects), the description is adequate. However, it could benefit from noting that deletion is permanent or that the key must 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?

The input schema already describes the key parameter with 100% coverage, so the description adds no additional meaning beyond what the schema 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'), which aligns with the tool name 'forget'. It distinguishes from siblings like 'recall' and 'remember' which are for retrieval and storage respectively.

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 usage for deletion, but does not provide guidance on when to use this vs alternatives like 'remember' or 'recall'. No exclusions or prerequisites are 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 are provided, so the description carries the full burden. It discloses the rate limit (5 per day) and the free nature, but does not discuss what happens after sending (e.g., no response, acknowledgment) or other behavioral traits like idempotency. Adequate but could be richer.

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 brief (two sentences) and front-loaded: first sentence states the purpose, second adds usage guidelines and rate limit. Every sentence is necessary and 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?

For a one-way feedback tool with no output schema, the description covers the essential aspects: purpose, use cases, content guidelines, and rate limits. It is complete enough for an agent to decide when and how to invoke it. Minor gap: no mention of whether a response is expected.

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 input schema has 100% description coverage, so the baseline is 3. The description adds no additional meaning beyond what the schema already provides (enums for type, descriptions for message and context). The advice against including user prompt is a usage guideline, not parameter semantics.

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 this tool sends feedback to the Pipeworx team, listing specific use cases (bug reports, feature requests, data gaps, praise). It distinguishes itself from siblings like ask_pipeworx or memory tools by being the dedicated feedback channel.

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 explicitly tells when to use (for various feedback types) and provides instructions on what to include (describe in terms of tools/data) and what not to include (user prompt verbatim). It also mentions rate limits, though it does not explicitly exclude use cases or compare to 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?

No annotations provided, so description carries full burden. It discloses that omitting key lists all memories, which is helpful. However, it does not mention what happens if key doesn't exist or if memory is empty, leaving minor gaps.

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 fluff, front-loaded with purpose. 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 simple tool with one optional parameter and no output schema, description adequately covers functionality. Slightly more detail on error cases could improve, but overall complete enough.

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. Description adds 'omit to list all keys' which is already in schema's description. No additional meaning beyond 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 verb 'retrieve' and resource 'memory by key' or 'list all stored memories'. It distinguishes from siblings like 'remember' (store) and 'forget' (delete), making purpose unambiguous.

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 clear context: use to retrieve saved context. Implicitly differentiates from 'remember' (store) and 'forget' (delete), but lacks explicit exclusions or when-not-to-use scenarios.

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 memory persistence behavior (authenticated users get persistent, anonymous lasts 24 hours). Since no annotations are provided, description carries full burden. Could be more transparent about overwriting behavior (e.g., what happens if key exists).

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 with clear structure: first sentence states core action, second sentence gives usage context. 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 simple input schema (2 required string params, no output schema) and no annotations, description covers essential aspects: purpose, usage, and persistence. Could mention overwrite behavior but not critical for a simple key-value store.

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 already provides clear parameter descriptions (key with example values, value as any text). 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?

Description clearly states 'Store a key-value pair in your session memory' with specific verb ('store') and resource ('key-value pair in session memory'). It distinguishes from siblings like 'forget' (remove) and 'recall' (retrieve) by focusing on saving data.

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 ('save intermediate findings, user preferences, or context across tool calls'). Notes persistence differences for authenticated vs anonymous users. Lacks explicit exclusion criteria for when not to use.

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 are provided, so the description carries the burden. It discloses the tool is read-only (resolving entities), lists returned fields (ticker, CIK, company name, pipeworx:// URIs), and mentions version 1 constraints. It does not explicitly state side effects or authentication requirements, but for a lookup tool this is adequate.

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 with no redundant information. It front-loads the core action, uses bullet-like clarity in the second sentence, and concludes with the benefit. Every sentence earns its place.

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 covers the purpose, inputs, and outputs (ticker, CIK, name, URIs). It also provides version context and a comparison to alternative approaches. Minor gap: no mention of error cases or response format, but overall complete for typical use.

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 descriptions for both parameters. The description adds value by providing concrete examples (AAPL, 0000320193, Apple) and confirming the type enum only includes 'company' in v1. This enhances understanding beyond the schema alone.

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 resolves entities to canonical IDs across Pipeworx data sources, specifies the supported type (company) and input formats (ticker, CIK, name). It distinguishes from siblings by mentioning it replaces 2–3 lookup calls, implying consolidation of lookups.

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 usage guidance: it accepts ticker, CIK, or name for company entities, and notes it replaces multiple calls. It does not explicitly state when not to use or list alternatives, but the context is clear enough for an agent to decide.

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