peerlytics

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

With no annotations provided, the description must fully convey behavioral traits. It only states 'Intent detail', which is insufficient to disclose whether the tool is read-only, requires authentication, has side effects, or any other behavioral aspects. The description does not add value beyond the name.

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 extremely short (two words), which might seem concise but is actually an under-specification. It does not earn its place because it fails to provide essential information. A good concise description would front-load the verb and resource while adding context.

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 lack of an output schema and annotations, the description should explain what the tool returns and any other contextual information. It does not describe the output format, data fields, or any constraints. For a tool with a single parameter, this is a major deficiency.

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 one required parameter 'hash' with 0% description coverage. The description does not explain what the hash represents, how to obtain it, or its format, providing no additional meaning beyond the schema. This is a critical gap for a single-parameter tool.

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 'Intent detail' minimally conveys that the tool retrieves details about an intent, but it is essentially a tautology of the tool name. It does not specify what kind of intent or what details are returned, and fails to distinguish it from sibling tools like get_maker or list_intents.

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

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

No guidance is provided on when to use this tool vs alternatives such as list_intents or other get_* tools. There is no context about prerequisites, exclusions, or typical use cases, leaving the agent without decision support.

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 reveals key behavioral differences based on parameter presence and the 400-day hard cap. However, it does not disclose potential edge cases (e.g., conflict between range and from/to precedence) or any authentication/rate-limit requirements, leaving some 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?

Three sentences, each adding critical information without redundancy. The most important purpose is stated first, followed by parameter-driven behavior and a constraint. 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?

The description covers the main modes and a key constraint, but given the number of parameters (6) and no output schema, it could benefit from mentioning the output format or pagination behavior (cursor/offset). It is adequate but not comprehensive.

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?

All 6 parameters are described in the schema, and the description adds value by explaining how parameters change the tool's behavior (cumulative vs per-window). This goes beyond the schema's individual parameter 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 it is a 'Maker/taker leaderboard' and distinguishes between two modes: cumulative (without params) and per-window (with from/to/range). It also notes the hard cap of 400 days, making the tool's purpose and scope 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 explains when to use each mode: without params for cumulative leaderboard, with from/to/range for per-window compute. It does not explicitly mention when not to use this tool or compare to siblings, but the context is sufficient for basic usage 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?

The description informs what data is returned but does not disclose behavioral traits such as read-only nature, authorization requirements, or rate limits. Given the absence of annotations, the description should explicitly state safety or side effects, but it only lists output components, which is minimally 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 a single sentence that front-loads the main concept ('Network orderbook') and concisely lists key outputs. There is no extraneous information, and every phrase adds value, making it highly 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 lack of an output schema, the description adequately summarizes the returned data by naming key components (rate levels, activity, stats, etc.). However, it could benefit from additional structure details, such as whether the output is an array or object, but it is largely complete for an orderbook retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage with descriptions for all four parameters. The tool description adds no additional parameter-specific context beyond what the schema already provides. With full schema coverage, 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 clearly states 'Network orderbook. Full orderbook with rate levels, 24h activity, global stats, FX mid-rates, and DRM-aware level metadata.' This specifies the verb (get) and resource (orderbook) and distinguishes it from siblings by detailing the comprehensive contents, such as global stats and FX mid-rates, which are unique to this 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?

The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. While the sibling list includes many get_* tools, no explicit usage context is given, 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?

With no annotations, the description carries the full burden. It discloses cost, grouping behavior, and response format changes (series[] vs buckets). It could mention read-only nature, but overall it's transparent about key behaviors.

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 extremely concise: four short sentences, no fluff, front-loaded with the core concept. Every sentence adds value (purpose, cost, grouping behavior).

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?

With 10 parameters and no output schema, the description gives a good overview but doesn't explain all filter parameters (maker, platform, etc.). However, schema descriptions cover those, so the tool is adequately documented for an experienced user.

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%, baseline 3. The description adds value by explaining that group_by changes the response structure to series[], which is not clear from the schema alone. It also implies time range usage via from/to/range.

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 provides historical time-series data for deposits, intents, or fulfilled volume at hour or day granularity. It differentiates from sibling tools like get_deposit or get_analytics_summary by focusing on aggregated buckets.

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 cost (60 credits per call) and usage of group_by for multi-series. It does not explicitly state when to use this tool over alternatives like get_analytics_summary, but the context makes it 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 bears the full responsibility for behavioral disclosure. It only states 'Payment platforms metadata', which does not indicate whether the operation is read-only, what the return format is, or any potential side effects. The agent has minimal insight into the tool's behavior beyond the implication of a list operation.

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 extremely concise at three words, with no wasted verbiage. It is front-loaded and each word ('Payment platforms metadata') carries meaning relevant to the tool's domain and output. For a simple no-parameter list, this level of conciseness is appropriate.

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 lack of output schema and annotations, the description should provide more context about what the metadata includes or the structure of the response. It only states 'metadata' without elaboration, leaving significant gaps in understanding the tool's output. Sibling tools like 'get_platform' likely have more detailed descriptions, making this one incomplete by comparison.

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 zero parameters and 100% coverage, so the description has no additional parameter details to provide. With 0 parameters, the baseline is 4, and the description does not need to compensate. The description is adequate in this dimension.

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 'Payment platforms metadata' is a noun phrase that vaguely indicates the tool returns metadata about payment platforms. Combined with the tool name 'list_platforms', the purpose is somewhat clear, but it lacks an explicit verb or action statement that would fully clarify what the tool does. It does distinguish from siblings like 'get_platform' by implying multiple items.

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 guidance on when to use this tool versus alternatives such as 'get_platform' or other listing tools. There is no mention of context, prerequisites, or any when-to-use advice, leaving the agent to infer usage solely from the tool name.

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