agentsapi-sec-filings

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

With no annotations, the description carries the burden of behavioral disclosure. It does convey that this is a statistics/read-style operation by listing computed outputs, but it does not mention any side effects, the effect of the optional hours parameter, or default behavior beyond what the schema independently documents.

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 compact sentence that front-loads the purpose and follows with concrete output facets. Every phrase adds information, and there is no redundant or filler content.

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 aggregate tool with one optional parameter and no output schema, the description adequately covers what the tool returns. The exact structural format of the distributions is unspecified, but this is not essential for an agent deciding whether and how to invoke 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?

Schema description coverage is 100% for the single optional hours parameter, so the schema fully documents the parameter. The description itself does not add any parameter-level meaning or examples, thus the 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 opens with a specific action and resource, "获取告警统计概览" (get alert statistics overview), and enumerates exact output dimensions: total count, distribution by type/severity/address, and latest alert time. This clearly separates it from sibling query_alerts, which implies listing individual alerts rather than aggregates.

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 use for aggregate overviews through the word "统计概览", but it does not explicitly state when to choose this tool over query_alerts or when not to use it. The usage context is inferable but not stated.

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 of disclosing behavior. It explains the clustering semantics (shared funding source), but does not state whether the tool is read-only, what exact output is returned, or any limitations such as data coverage, latency, or failure modes.

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, information-dense sentence with no filler. It front-loads the main action and result, then appends the purpose, which is exactly appropriate for a simple one-parameter tool.

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 low-complexity tool with one parameter and no output schema, the description is largely sufficient: it defines the input, the cluster concept, and the intended use. The only gap is that the exact return shape and edge-case behavior are not described, though the description does indicate the result is a set of addresses.

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 documents the parameter as a 0x-prefixed funder address. The description reinforces the role of the parameter but does not add meaning beyond the schema's own parameter 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 states a specific verb ('detect') and a concrete resource: the set of addresses funded by a given funder address, framed as shared-funding-source clustering. It also names the purpose (Sybil/entity identification), which clearly distinguishes it from siblings like query_alerts or get_label.

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 a use case through '用于女巫/实体识别' (for Sybil/entity identification), giving some contextual guidance. However, it provides no explicit comparison with alternatives, no when-not-to-use conditions, and no exclusions.

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 behavioral disclosure burden. It usefully reveals the output dimensions including the 'suspected cross-chain bridge' heuristic, but it does not explicitly state that the operation is read-only, how it handles invalid hashes, or any failure 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?

A single compact sentence that front-loads the core action and then lists concrete output aspects. Every word contributes meaning, with 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?

For a single-parameter tool with no output schema, the description covers the main return facets an agent needs: status, sender/receiver with labels, transfer details, and bridge-suspicion flag. It could be strengthened by noting that the call is read-only and how to handle unknown transactions, but the essential calling context is present.

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 only parameter (txHash) with '0x 开头的交易哈希', giving 100% schema coverage. The description adds no additional parameter-level detail, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('解释') and a specific resource ('一笔交易'), then enumerates what the explanation covers: status, parties with identity labels, transfer details, and suspected cross-chain bridge behavior. This makes the tool's purpose clear, though it does not explicitly contrast with sibling tools like detect_cluster or track_cctp.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is used when an agent needs to understand what a transaction did, but it provides no explicit when-to-use guidance, exclusions, or alternative tool suggestions. Usage context is implied rather than stated.

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 behavioral burden. '查询' implies a read-only lookup, and the description discloses the data source ('10 万实体标签库') and output. However, it does not explicitly confirm non-mutating behavior, coverage limitations, or behavior when an address has no label.

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 with no filler. It front-loads the action and resource, then adds the useful label-library context and return-value description in a compact way.

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-parameter, read-only, lookup-style tool, the description is largely complete: it names the input, the data source, and the expected return value. Since there is no output schema, the description does state what the tool returns ('which entity the address belongs to'), though it could mention edge cases like missing labels.

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 'address' parameter fully, including type, description, and an example. The description adds no new parameter semantics beyond 'EVM address', so the schema is doing the heavy lifting and a baseline 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 uses a specific verb and resource: '查询一个 EVM 地址的身份标签' (query identity label for an EVM address) and states the return value ('返回该地址属于哪个实体'). It is clearly distinguished from the sibling tools by its label/entity focus, though it never explicitly contrasts itself with any sibling.

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 on when to use this tool versus alternatives such as explain_transaction, query_alerts, or detect_cluster. The description only states what the tool does; it gives no selection conditions, exclusions, or prerequisite 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?

With no annotations, the description carries the behavioral burden. It conveys that the tool reads historical alert records and filters them, but it does not explicitly state that it is side-effect-free or describe response format, ordering, or error 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 a single concise sentence with the query action front-loaded and all filter dimensions enumerated efficiently. There is no filler or redundant content.

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 schema covers all parameter constraints and the core purpose is clear. However, with no output schema and no annotations, the description does not clarify return-value shape or usage boundaries relative to sibling tools such as alert_stats.

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 every parameter already has meaning. The tool description only restates the filter dimensions without adding new semantic details, matching the baseline for full schema coverage.

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 operation ('query historical alert records') and lists the filtering dimensions (address, rule type, severity, time range). This makes the action and resource clear, though it does not explicitly contrast the tool with siblings such as alert_stats.

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 use case is implied: the agent should use this tool when historical alert records are needed and filters apply. However, there is no explicit guidance about when not to use it or how it differs from sibling tools.

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

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

No annotations are present, so the description carries the behavioral burden. It discloses that the tool queries by source-chain txHash, returns specific data points, and supports CCTP chains such as Base → Ethereum. It does not mention failure/not-found behavior, but for a read-only lookup this is a minor gap.

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 filler. The purpose is front-loaded, followed by input and output details, then supported chain context. 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?

This is a simple one-parameter tool with no output schema and no annotations. The description supplies the input requirement, the output semantics, and supported chain context, which is enough for an agent to invoke 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 description coverage is 100%, so the baseline is 3. The description reinforces that txHash comes from the source chain and that CCTP chains are relevant, but it adds no format or validation detail beyond what the schema already 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 gives a specific verb ('追踪'/track) and resource (CCTP cross-chain transfer), and it distinguishes the tool from siblings by clearly stating the cross-chain tracking domain. It also lists exactly what the query reveals: which cross-chain transfer, amount, target chain, and arrival status.

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 intended context is clear: use this when you need to follow up a CCTP cross-chain transaction from a source-chain transaction hash and check if funds arrived. It does not explicitly name alternative tools or state when not to use it, so it falls short of a 5.

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