zdte.ai SPX Market Structure

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

The annotations already declare read-only, idempotent, and non-destructive behavior. The description adds the useful 'Data only -- not investment advice or a trade recommendation' qualifier and clarifies the output shape as a timeline plus summary, which is consistent with the 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?

One tight sentence delivers the scope, resource, date format, and a safety disclaimer. There is no filler or redundancy; 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?

For a one-parameter, read-only retrieval tool, the description plus schema covers the return content at a useful level (timeline + summary), the date constraint, and valid-date discovery via a sibling tool. It does not enumerate output fields, but no output schema is present and get_field_guide is available as a sibling.

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 single date parameter has a regex pattern and a description pointing to list_history_dates. The description's parenthetical 'YYYY-MM-DD' adds no meaning beyond what the schema already provides, so the schema carries the semantic weight.

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 identifies a concrete resource (per-day SPX market-structure timeline + summary) and scopes it to one replay date. The title 'Replay a Trading Day' adds a clear verb, but the description does not explicitly contrast with siblings like get_market_structure or get_regime.

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 this is for a single historical replay date, and the schema usefully points to list_history_dates for valid date values. However, it does not explain when to prefer get_day over the sibling market-structure or regime tools, leaving alternative selection to inference.

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 already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds meaningful context beyond that: the data is static, versioned, and intended to be called once per session, plus it discloses what information the field guide contains. This goes beyond the annotation baseline.

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 information-dense. The first sentence front-loads the core nature ('Static, versioned dictionary') and enumerates the contents efficiently. The second sentence handles usage and invocation. No unnecessary words or repetition.

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 no output schema present, the description does the necessary work of explaining what the tool returns: field names, units, value sets, meanings, and shared response conventions. It also gives session-level usage guidance. This is complete for a tool of this simplicity.

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?

There are zero parameters, so the schema is fully clear. The description reinforces this with 'No inputs,' which is sufficient. No additional parameter semantics are needed.

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 clear purpose: a static, versioned dictionary of every field the surface emits, with units, value sets, meaning, and shared response conventions. This clearly distinguishes it from siblings like get_day or get_regime, which fetch specific data, whereas this tool provides schema-level reference information.

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 says 'No inputs; call once per session,' which is a direct usage instruction for a reference tool. It doesn't explicitly name alternatives or exclusions, but the context of a field dictionary makes its role obvious relative to the data-fetching 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds meaningful behavioral context beyond those annotations: the data is recomputed roughly every 10 seconds during market hours, it requires a funded X-API-Key, and it is data-only rather than advice. No contradiction with 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 long but front-loaded with the core purpose and update cadence, then systematically lists the included data sets, authentication requirement, and disclaimer. Every clause conveys distinct content, though the long enumeration of metrics could be slightly more scannable.

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 no output schema and no parameters, the description carries the full burden of explaining what the tool returns. It covers the major data areas: strike ladders, forecast bands, GEX, expected move, max pain, session OHLC, order flow, and vanna/charm. It also documents the paid access requirement and non-advice nature, making it sufficiently complete for a zero-parameter read-only endpoint.

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 and an empty input schema, so there are no parameter semantics for the description to clarify. The baseline of 4 applies because nothing is missing or ambiguous regarding inputs.

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 identifies the resource: current computed SPX dealer market structure, including walls, gamma flip, net GEX, and regime. It enumerates many specific data components, so an agent knows what the tool returns. However, it lacks an explicit verb like 'returns' or 'gets' and does not explicitly differentiate itself from sibling tools such as get_regime or get_day.

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 real-time SPX market structure data, especially via 'recomputed ~every 10s during market hours' and 'current computed.' It also warns that the data is not investment advice. However, it provides no explicit guidance about when to prefer this tool over siblings like get_regime or get_day, nor any exclusion criteria.

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 already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior, so the description does not need to repeat those. It adds useful context by specifying the output is exactly the current label plus confidence and nothing else, which aligns with and complements the 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 a single short sentence that immediately conveys the tool's purpose and output scope. Every word earns its place, and the constraint 'only' is front-loaded into the key 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?

For a zero-parameter read-only tool with no output schema, the description adequately tells the agent what to expect: the current regime label and confidence only. It could be more complete by defining possible label values or confidence scale, but the simplicity of the tool and the strong annotations make this sufficient.

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 and the input schema is empty, so there is no parameter semantics burden for the description to carry. The baseline of 4 applies because there are no parameters requiring explanation.

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 identifies the tool as returning the current SPX dealer regime label and confidence, with 'only' emphasizing its narrow scope. It does not use a verb phrase, but the resource and output are unmistakable and it is effectively distinguished from the sibling get_regime_segments by saying it returns only the label and confidence.

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 word 'Current' and 'only' imply this tool is for a point-in-time label and confidence, not for historical or detailed segment data. However, it never explicitly names alternatives like get_regime_segments or states when-not-to-use this tool, leaving some guidance implied rather than explicit.

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 already carry the safety profile: readOnlyHint is true, idempotentHint is true, and destructiveHint is false, so the agent knows this is a safe read. The description adds 'compressed' as an output trait, but it does not disclose pagination, missing-date behavior, or the structure of the returned tape; this is acceptable but not rich context.

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, front-loaded sentence that conveys the resource, the compression aspect, and the date scope without filler. The date format parenthetical is mildly redundant with the schema but does not undermine the overall efficiency.

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 tool, the schema and annotations cover a lot of the burden. However, there is no output schema, and the description does not explain what a 'regime segment tape' contains, how to interpret it, or how it differs from the similar get_regime sibling, leaving some ambiguity for an agent.

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%: the date parameter already has a pattern, format, and a pointer to list_history_dates for valid values. The main description re-states the YYYY-MM-DD format but adds no substantial meaning beyond the schema, so the 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 identifies a specific resource—a compressed dealer-regime segment tape—for a single replay date, so an agent can infer the tool's fetch operation. However, it does not explicitly contrast with the sibling get_regime, leaving the agent to rely on the phrase 'segment tape' for differentiation.

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 the tool: when you need the dealer-regime segment tape for one replay date. It provides no explicit when-not guidance or comparison to sibling tools like get_regime or get_day, and the only alternative-related signal (use list_history_dates for valid dates) lives in the schema rather than the description.

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 annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful scope context ('historical SPX market-structure replay dates') but does not disclose return format, ordering, pagination, or whether the list is exhaustive. It adds some value beyond annotations without contradicting them.

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 with no filler or repetition. It is a phrase rather than a complete imperative sentence, which slightly reduces clarity, but it is still front-loaded and to the point.

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, zero-parameter, read-only listing tool, this description is adequate for an agent to select and invoke it correctly. The absence of an output schema is acceptable because the expected result is conceptually self-evident from the title and description. It would be stronger with an explicit statement that invoking it returns the list of available dates.

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 and a 100% schema description coverage, so there is no parameter semantics burden on the description. The baseline for a no-parameter tool applies, and nothing about inputs needs explanation.

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 identifies the exact resource ('historical SPX market-structure replay dates') and, combined with the title 'List Replay Dates', makes the purpose clear. It is not a tautology and is distinct enough from siblings like get_day or get_regime. However, it lacks an explicit action verb in the description itself, relying on the title for the 'list' action.

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 about when to use this tool versus alternatives such as get_day, get_market_structure, or list_subscriptions. The description only states availability and does not explain prerequisites, expected call flow, or exclusions. An agent must infer the usage context from the tool name and sibling list.

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 already cover the safety profile with readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description doesn't need to restate that this is a safe read operation. It does add the scoping detail 'this agent's active' subscriptions, which is mildly useful. However, it doesn't disclose any return format or pagination behavior, though the bar is lower because annotations are present.

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 wasted words. It delivers the essential information in a compact form, which is ideal for such a simple 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 zero-parameter list tool with no output schema, the description is fully sufficient. It tells the agent what is being listed (event subscriptions), the scope (this agent's), and the filter (active). The sibling context further reinforces that the tool is about event subscriptions, leaving no critical gaps for invocation.

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 and an empty input schema, so there is nothing for the description to explain. According to the rubric, a zero-parameter tool receives a baseline score of 4, and the description adequately serves its purpose without any parameter documentation.

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: 'List this agent's active event subscriptions.' It clearly distinguishes this from sibling tools like subscribe_event and unsubscribe, which perform different actions. No ambiguity remains about what the tool does.

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 makes it clear that this tool is for viewing the agent's own active event subscriptions. While it doesn't explicitly mention alternatives, no real alternative exists for listing subscriptions among the siblings—only creation and deletion tools are present. This is clear context without needing 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?

Annotations already indicate a mutating, non-idempotent, open-world operation, and the description adds no behavioral context beyond restating 'subscribe.' It does not disclose the side effect of registering the callback, possible duplicate-subscription behavior, or what the caller receives in response.

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 sentence with the verb and resource front-loaded and the valid event values shown compactly in parentheses. Every word earns its place and there is no redundant prose.

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 two-parameter tool with complete schema and helpful annotations, the description is minimally sufficient to invoke the tool correctly. It lacks any indication of return values or follow-up management (e.g., listing or unsubscribing), but those are represented by sibling tools and not strictly required for a valid call.

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 both parameters are fully documented in the schema. The description repeats the event enum and callback_url concept but adds no additional semantic detail beyond what the input 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 states a specific action and resource: subscribe a callback URL to a market-structure event, and enumerates the three valid event types. It is unambiguous, though it does not explicitly contrast itself with sibling tools like list_subscriptions or unsubscribe.

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 by the verb 'subscribe' and the event/callback parameters: an agent would use this when it wants to register a callback for one of the listed market-structure events. However, there is no explicit guidance about when not to use it or how it relates to list_subscriptions and unsubscribe.

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 already declare destructiveHint=true, idempotentHint=true, and readOnlyHint=false, so the safety profile is covered outside the description. The description adds no extra behavioral detail beyond confirming removal, but it does not contradict the 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?

One short, front-loaded sentence with no filler; every word contributes to defining the operation.

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 a single required parameter, full schema coverage, and annotations covering destructiveness and idempotency, the description is nearly complete for invoking the tool. It could mention behavior on an unknown subscription_id, but that is a minor gap for a one-parameter unsubscribe operation.

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 schema's parameter description already links subscription_id to subscribe_event's return value. The free-text description adds no additional parameter meaning, 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?

The description uses a specific verb ('Remove') and resource ('event subscription') and qualifies the removal method ('by id'). This clearly distinguishes it from sibling tools like subscribe_event and list_subscriptions.

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?

It implies usage since the schema requires a subscription_id returned by subscribe_event, but it never explicitly states when to use this tool versus its siblings. The context is inferable from the sibling set rather than clearly stated.

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