xrade

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

With no annotations provided, the description carries the full burden of behavioral disclosure, but it only gives a conceptual explanation. It does not state whether the tool is read-only, what side effects exist, what output to expect, or any operational constraints.

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 and not verbose, but it lacks a clear action-oriented structure. The single sentence is dense with conceptual nuance yet fails to front-load what the tool actually does.

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 zero-parameter tool, the description should clarify what invoking it returns or how it behaves. Instead, it only provides an abstract definition of 'coverage', which is insufficient for an agent to confidently select and call the 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?

The tool has zero parameters, so the description need not explain parameter meaning. The baseline of 4 applies here because there is no parameter semantics burden at all.

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 defines the concept of 'coverage' as what the record covers and what it has not covered, but it never states an action the tool performs (e.g., 'retrieves', 'returns', 'calculates'). It is semantically informative but does not clearly distinguish the tool from siblings like lookup_token or wrapper_record.

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?

There is no guidance about when to use this tool versus the sibling tools. No conditions, alternatives, or exclusions are mentioned, leaving the agent to infer usage from the name alone.

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 several behavioral traits: results are grouped by legal wrapper, unranked, listed alphabetically, and include unresolved on-chain tokens. This goes beyond a simple 'look up' statement and gives the agent useful expectations about output structure.

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 dense sentences, each earning its place. The purpose is front-loaded, and the output behavior is summarized without extraneous wording. It is structured logically from invocation to result details.

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

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

For a single-parameter lookup tool with no output schema, the description covers both input and output well: search method, grouping, ordering, and inclusion of unresolved tokens. Some domain terms like 'legal wrapper' are not expanded, but the overall description is sufficient for correct invocation and interpretation.

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 fully documents the query parameter with examples, and schema coverage is 100%. The description only repeats that lookups can be by ticker or name, adding no new semantic detail beyond the schema. 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 opens with a clear verb and resource: 'Look up a stock or asset by ticker or name.' It then explains the output specifics (tokenised versions, grouping by legal wrapper, unresolved on-chain tokens), which sets it apart from sibling tools like lookup_token by focusing on stocks/assets and their token representations.

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 states when to use the tool: when you need to look up a stock or asset by ticker or name. It does not explicitly mention alternatives or exclusions, but the usage context is unambiguous and self-contained.

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 the behavioral burden. It explicitly states that an uncovered token gets a definitive 'not covered' answer rather than a blank, and it describes what the lookup returns. It does not cover error cases or permissions, but those are less critical for a read-only lookup 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?

Two tightly packed sentences with no filler. The first sentence establishes purpose and timing, the second details the output and the key edge case. Every phrase 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 the absence of an output schema, the description does a good job of conveying what the tool returns and how it behaves for unsupported tokens. Combined with the schema's full parameter documentation, this is sufficient for a two-parameter lookup 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 schema already explains chain and address formats sufficiently. The description only restates the parameter roles ('by chain and contract address') without adding new semantic detail 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 names a specific verb ('look up'), a specific resource ('token by chain and contract address'), and the output substance ('legal wrapper', entitlements, quotes). It also differentiates itself from siblings by focusing on tokens and pre-trade coverage, rather than stocks or wrapper records.

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 opening phrase 'The pre-trade check' gives clear context for when this tool should be used. It does not explicitly name sibling alternatives or state when not to use it, so it stops just short of fully explicit routing.

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 the full behavioral disclosure burden. It adds valuable transparency by stating that every fact includes supporting quotes, sources, and dates, and that unexamined fields are distinguished from fields no document discloses. It does not cover response format, error behavior, or access requirements, but for a read-oriented record tool these omissions are not critical.

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 compact and front-loaded with the core purpose, followed by a second sentence that adds substantive data-provenance detail. No unnecessary repetition exists, though the phrasing "Fields nobody examined and fields no document discloses are distinguished and say so" is slightly awkward but still informative.

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

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

For a single-parameter tool with no output schema, the description covers the tool's scope, the legal topics included, and important data-quality caveats. It is sufficiently complete for an agent to understand what the tool does and what to expect. A small gap is the lack of explicit output-format or empty-result behavior, but the content list largely compensates.

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 documents the single parameter well, including the "Wrapper slug or name fragment" description and an example. Schema description coverage is 100%, so the description does not need to add parameter-level meaning. It reinforces the "one wrapper" scope, which is consistent with 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 that the tool provides "the full legal record of one wrapper" and enumerates the legal topics covered, such as structure, holder claim, insolvency ranking, and transfer restrictions. The verb is implicit rather than explicit, but the resource and scope are specific. It does not explicitly distinguish itself from siblings like lookup_stock or lookup_token, though the "one wrapper" framing narrows its 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?

Usage is implied: use this when you need the complete legal record and supporting evidence for a single wrapper. The description does not explicitly say when to choose this tool over coverage, lookup_stock, or lookup_token, nor does it mention exclusions or prerequisites. This is adequate but leaves selection guidance to the agent.

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