Etherscan

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

The description discloses that Pipeworx internally selects tools and fills arguments, but does not mention potential side effects, error handling, or limitations. Given the absence of annotations, the description partially covers behavioral traits but leaves gaps in transparency.

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 with three sentences followed by examples. It front-loads the purpose and maintains clarity without unnecessary details. 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?

The description covers the core behavior sufficiently for a simple tool with one parameter. However, it lacks details on error responses or handling of ambiguous queries, but given the simplicity and lack of output schema, the completeness is 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?

With 100% schema coverage and only one parameter ('question'), the description adds little beyond the schema's own description. The baseline of 3 is appropriate as the parameter is self-explanatory from 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 function: answering natural language questions by automatically selecting and invoking the appropriate underlying tool. This distinguishes it from siblings like compare_entities or discover_tools, which are specific tools, making the 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?

The description implicitly guides when to use the tool: when the user prefers plain English over manually browsing schemas. It provides examples of queries, but lacks explicit statements about when not to use it or alternatives, though the context of sibling tools makes the choice 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 full burden. It discloses the data sources (SEC EDGAR for companies, FDA for drugs) and output format (paired data + URIs), but does not mention side effects, authentication needs, rate limits, or error conditions. For a read-like tool this is adequate but not rich.

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, front-loaded with the core action, and every sentence adds essential information. There is no redundant or extraneous text.

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 (two entity types, multiple data points), the description covers all necessary aspects: entity selection, data provided for each type, output format, and benefit over sequential calls. No output schema is present, but the description compensates adequately.

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 adds meaning beyond the schema by providing examples of valid values for each type (e.g., tickers for companies, drug names) and specifying the data fields returned per type. This enhances understanding beyond the enum and array 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 clearly states the tool compares 2-5 entities side by side, specifies two distinct types ('company' and 'drug') with detailed data fields for each, and explicitly distinguishes it from making multiple sequential calls (8-15). This provides a specific verb+resource and differentiates 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 explains when to use the tool (for side-by-side comparison of 2-5 entities) and implies it replaces multiple sequential calls, but does not explicitly state when not to use it or provide alternatives among the sibling tools. The context is clear but lacks explicit exclusions or alternative suggestions.

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. The description implies a read-only search operation but does not explicitly state behavioral traits like idempotency or side effects. For a search tool, this is adequate but not exemplary.

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 concise sentences with no superfluous text. The first sentence states the core function, the second provides usage guidance.

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 simplicity of the tool (search with two parameters, no output schema), the description fully covers what an agent needs to know: purpose, usage context, and parameter hints.

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 input schema already explains both parameters ('query' and 'limit'). The description adds no additional semantic value beyond what is in the schema, meeting the baseline.

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 ('search') and resource ('Pipeworx tool catalog'), and clearly states the output ('returns the most relevant tools with names and descriptions'). It distinguishes itself from sibling tools by being the meta-discovery tool.

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 advises 'Call this FIRST when you have 500+ tools available and need to find the right ones for your task,' providing clear context and when-to-use guidance.

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, but the description compensates by detailing the returned data (citation URIs) and performance benefit (replaces 10-15 calls). It does not explicitly state read-only behavior, but context implies it.

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 packed with information. First sentence states purpose, second lists data sources, third addresses alternatives. 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 complexity of a multi-source profile and absence of output schema, the description thoroughly explains what is returned and provides guidance on alternative tools. It covers performance context and required input formats.

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%. The description adds meaning: explains that type only accepts 'company', value expects ticker or CIK, and names are not supported (directing to resolve_entity).

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 returns a full profile of an entity, listing specific data sources (SEC filings, XBRL, patents, news, LEI). It distinguishes from siblings like usa_recipient_profile and resolve_entity.

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 (for comprehensive profile) and when not (federal contracts, use usa_recipient_profile instead). Also advises to use resolve_entity first if only a name is available.

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 must fully disclose behavioral traits. It only says 'Delete', which implies a destructive operation, but does not mention side effects (e.g., whether the deletion is permanent, if it requires special permissions, or if it affects related data). This is insufficient for a mutating 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 a single sentence of 7 words, front-loading the key information. It is concise, but slightly more detail (e.g., what happens if key is missing) would not be wasteful.

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 parameter) and the presence of sibling tools (recall, remember) that provide context, the description covers the essential purpose. However, it does not specify behavior for non-existent keys or success confirmation, which might be 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% coverage, with a description for the 'key' parameter ('Memory key to delete'). The tool's description adds no additional meaning beyond the schema. Baseline is 3 since schema already documents the parameter.

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 'Delete a stored memory by key' clearly states the action, resource, and means. It specifies the verb 'Delete' and the resource 'stored memory' with the key-based selection, effectively distinguishing it from sibling tools like 'remember' (store) and 'recall' (retrieve).

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 explicit guidance on when to use this tool versus alternatives. While it's implied that it's for deletion, there is no mention of prerequisites, use cases, or situations where other tools (e.g., 'forget' vs 'recall') would be more appropriate.

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, description adds minimal behavioral context beyond schema: it's a native token balance query defaulting to Ethereum. Lacks details like returned unit or error 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?

Single sentence, no fluff, front-loaded with core function.

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?

Adequate for a simple read tool; could mention return format/unit, but not critical. No output schema, but function is clear.

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 description adds value by listing example chain slugs and clarifying acceptance of numeric chain ID.

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 returns native-token balance for an address on supported EVM chains, with default Ethereum mainnet. Distinguishes from sibling get_token_balance by being specifically for native token.

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 default chain and accepted formats, but does not explicitly state when to use vs alternatives. Implicitly clear from tool name and sibling context.

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?

The description discloses the precondition of contract verification, but given empty annotations, it does not cover failure behavior for unverified contracts, rate limits, or data freshness. The behavioral disclosure is adequate but not comprehensive.

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, front-loaded sentence with no unnecessary words. It efficiently conveys the core purpose 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?

The description does not specify the return format in detail (e.g., JSON structure) and lacks context about external dependencies (e.g., Etherscan API). For a tool with no output schema, more detail would improve 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 coverage is 100% with descriptions for both parameters (chain and address). The description adds no additional meaning beyond the schema, so it meets the baseline without further enrichment.

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 returns a verified contract ABI as JSON, with a condition on verification. It uses a specific verb+resource ('get contract ABI') and is distinct from sibling tools like 'get_contract_source'.

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 retrieving an ABI for verified contracts but does not explicitly state when to use this tool versus alternatives (e.g., get_contract_source for source code). No exclusion criteria or prerequisites beyond verification 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?

Annotations are empty, so the description carries full burden. It specifies 'Verified contract source code,' indicating it only works for verified contracts, but fails to describe behavior for unverified contracts (e.g., error, null). No mention of permissions, rate limits, or other 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?

The description is a single, concise sentence that efficiently conveys the tool's purpose. It is front-loaded and wastes no words, though it could be slightly more informative about return structure.

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, the description lists key return fields (source code, compiler, optimization, license) but does not explain format or optionality. Behavior for unverified contracts is omitted. Adequate but leaves gaps for comprehensive 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 description coverage is 100% (both parameters have descriptions). The tool description adds no additional meaning beyond what the schema already provides. 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 it retrieves 'Verified contract source code, compiler version, optimization settings, and license,' which precisely indicates the tool's function. It distinguishes from sibling tools like get_contract_abi (ABI) and get_balance (balance), as those serve different purposes.

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 when needing contract source code details, but provides no explicit guidance on when to use this tool versus alternatives like get_contract_abi or list_transactions. No when-not or context for selection is given.

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 bears full responsibility for behavioral disclosure. It only states the function without mentioning any side effects, authenticity requirements, or formatting details (e.g., raw vs. human-readable balance).

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 front-loads the purpose. It is efficient, though it could be slightly more informative without sacrificing length.

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 low complexity, 100% schema coverage, and no output schema, the description is adequate but lacks details about return value format (e.g., string or number, decimal handling). It covers the essential purpose but leaves some context 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?

The input schema covers all parameters with descriptions. The description adds no additional semantic value beyond the schema, so baseline score of 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 it returns an ERC-20 token balance for a specific address and contract, using a specific verb and resource. It distinguishes itself from the sibling 'get_balance' tool which likely handles native coin balances.

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 does not provide explicit guidance on when to use this tool versus alternatives like 'get_balance'. Usage is implied but not differentiated, which is a missed opportunity to clarify scope.

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?

Annotations are empty, so the description must cover behavioral aspects. It does not mention whether the operation is read-only, rate limits, pagination behavior, or output format. Beyond listing transaction types, no behavioral traits are disclosed, leaving the agent with minimal transparency.

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 that efficiently conveys the tool's purpose and the key parameter (type) without unnecessary words. It is front-loaded and 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?

Given 8 parameters, no output schema, and empty annotations, the description covers the essential differentiator (type) but lacks details on pagination, chain input, or return structure. It is almost complete for a list tool, with minor 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 coverage is 100% with all 8 parameters described, but the description adds value by explaining the meaning of each type enum value (e.g., 'contract-internal value transfers' for internal). However, it does not elaborate on other parameters like page, sort, or chain, so it adds meaning beyond schema for only one parameter, justifying a slight above-baseline score.

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 'List transactions for an address' and explains the type parameter that distinguishes between transaction categories (normal, internal, erc20, etc.), making the purpose specific and distinct from sibling tools like get_balance or get_contract_abi.

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 transaction history but does not explicitly state when to use this versus alternatives (e.g., for balances use get_balance). No when-not or alternative guidance is provided, only the type parameter explanation.

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 rate limiting (5 messages per identifier per day) and content expectations. The tool is inherently a write operation (sending feedback), which is implied but not explicitly stated as safe or destructive; however, no contradictions 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?

Description is extremely concise: three sentences covering purpose, usage guidelines, and rate limit. No redundant or irrelevant information. Front-loads the core purpose.

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 feedback tool with no output schema and 100% schema coverage, the description fully covers purpose, usage, rate limits, and content rules. No gaps identified.

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 schema provides detailed descriptions for all parameters (e.g., type enum, context object, message). The description adds only minor usage nuance (e.g., 'do not include end-user prompt verbatim'), which is more about usage than parameter meaning. 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 the tool sends feedback to the Pipeworx team and lists specific use cases (bug reports, feature requests, missing data, praise). It is distinct from all sibling tools, which are for queries, comparisons, or memory operations.

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?

Description tells when to use the tool (for feedback types) and provides guidance on what to include (describe tried tools/data) and exclude (end-user's prompt verbatim). Rate limit is stated. Does not explicitly say when not to use, but 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?

With no annotations, the description fully conveys the tool's behavior: it is a read-only retrieval operation, listing or getting a memory. No side effects or hidden behaviors are implied.

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, each serving a purpose. It is concise, front-loaded, and contains no redundant information.

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?

The description covers the essential functionality but does not specify the return format (e.g., the value stored). Since there is no output schema, a brief note on what is returned would improve completeness. However, for a simple tool, it is mostly 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?

Schema description coverage is 100%, and the schema already explains the parameter ('Memory key to retrieve (omit to list all keys)'). The description echoes this without adding new meaning beyond what the schema provides.

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: 'retrieve a previously stored memory by key, or list all stored memories (omit key).' It uses specific verbs and resource, and distinguishes itself from sibling tools '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?

The description includes a usage context: 'Use this to retrieve context you saved earlier in the session or in previous sessions.' It does not explicitly state when not to use or mention alternatives, but the context is clear and sufficient for a simple tool.

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 fully covers behavioral traits: it describes parallel fan-out to multiple sources (SEC, GDELT, USPTO), acceptable date formats (ISO or relative), and the return structure (structured changes + total_changes + URIs). It is transparent about behavior.

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 purpose and then elaborates on specifics. While not extremely concise, every sentence adds value and it avoids verbosity. Could be slightly shorter, but still 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 3 required parameters, no output schema, and no annotations, the description provides complete context: explains the parallel data sources, acceptable date formats, return value structure, and typical use cases. An agent has sufficient information to invoke the tool 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%, but the description adds significant meaning: it explains that 'type' only supports 'company', 'value' can be ticker or CIK, and 'since' accepts both ISO dates and relative strings like '7d', with typical usage '30d' or '1m'. This goes beyond the schema's basic 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 'What's new about an entity since a given point in time' and details the specific data sources (SEC EDGAR, GDELT, USPTO) for company type. This clearly distinguishes it from sibling tools like entity_profile or compare_entities.

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 direct usage guidance: 'Use for "brief me on what happened with X" or change-monitoring workflows.' While it does not explicitly list when not to use it, the context is clear enough for selecting the tool.

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 behavior for authenticated vs anonymous users, implying a write operation. No annotations present, so description carries full burden. Lacks mention of size limits or side effects but 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?

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?

For a simple memory store, description covers purpose, usage, and persistence. No output schema needed, so complete.

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 clear descriptions. Description adds minimal extra meaning beyond schema, such as 'key is for remembering'. 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 the tool stores a key-value pair in session memory, with specific verb 'Store' and resource 'key-value pair'. It is distinct from siblings like 'forget' and 'recall'.

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 use cases: 'save intermediate findings, user preferences, or context across tool calls'. Mentions persistence differences but no explicit when-not-to-use or alternatives.

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, the description carries full burden. It discloses supported inputs and outputs (IDs and URIs), but does not cover error handling, idempotency, or rate 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: purpose, type explanation, and return value plus benefit. No redundant information, front-loaded with key action.

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 adequately explains what it returns and why it's useful. Missing details on exact return format, but sufficient for selection.

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 meaning beyond the schema by explaining the context of each parameter with examples (e.g., ticker, CIK for company).

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: resolving an entity to canonical IDs across Pipeworx data sources. It specifies supported types (company and drug) with examples, and distinguishes from a single-lookup tool by noting it replaces 2-3 calls.

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 when to use (when needing canonical IDs for company or drug) and mentions it replaces multiple calls, but lacks explicit when-not-to-use or alternatives like compare_entities.

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 describes the return verdicts, citation, and delta, and that it's a replacement for multiple calls. Does not explicitly state read-only nature or potential side effects, but fact-checking implies no mutations.

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 efficiently convey purpose, scope, return values, and value proposition. No redundant information.

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 single parameter, no output schema, and no annotations, the description is fairly complete. Could mention limitations (e.g., only US public companies) but overall provides sufficient information for an agent to decide and invoke.

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?

Only one parameter (claim) with schema description providing examples. Description adds value by clarifying the type of claims supported (company-financial), which goes 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?

Clearly states the tool fact-checks natural-language claims against authoritative sources, specifies domain (company-financial) and data sources (SEC EDGAR + XBRL). Distinguishes from siblings by noting it replaces 4–6 sequential agent calls.

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 it supports company-financial claims, implying when to use. Does not explicitly state when not to use (e.g., non-financial claims), but the context of sibling tools provides no alternative for this type of validation.

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