0DTE Analyst

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

With no annotations supplied, the description carries the full disclosure burden. It does add real behavioral value by flagging that the response includes 'tactical volatility blackout windows,' which is more than a bare listing. However, it says nothing about data freshness, timezone, refresh cadence, or whether the read is cached, which matters for a same-day calendar 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?

One front-loaded sentence with the resource named first and the scope constraint ('today's trading session') attached to it. The event-type enumeration (FOMC, CPI, PPI, NFP) is informative rather than padding, though it is slightly list-heavy.

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 tool with no output schema, the description covers the key gaps: what categories are included, the time window, and the presence of blackout windows. It stops short of describing the shape of an individual event (time, impact rating, affected symbols), which an agent would otherwise have to discover by calling.

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 takes zero parameters, so the baseline is 4. The description usefully clarifies that scope is hard-coded to today's session, telling the agent there is no date argument to supply and no way to query other days.

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?

States a specific verb ('Lists') and a well-scoped resource: scheduled macro events, FOMC, CPI/PPI, NFP, plus volatility blackout windows, all limited to today's session. An agent knows exactly what data comes back. It does not differentiate itself from siblings like get_macro_thesis, but the resource is distinctive enough to avoid confusion.

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 only implied by the phrase 'for today's trading session,' which suggests pre-session or intraday volatility checks. There is no explicit when-to-use guidance, no statement of what to use instead for historical or forward-dated calendars, and no mention of how it relates to get_macro_thesis or get_expected_move.

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 does disclose that results are 'real-time' and specific to 0DTE options on index/ETF symbols, which is meaningful behavioral context. It says nothing about data source, whether it works outside market hours, rate limits, or how an unsupported symbol is handled.

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 tight sentences: the first defines the computation and scope, the second gives the practical use case. Nothing is redundant and the core purpose is front-loaded.

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 one-parameter read-only computation with a fully documented schema, the description covers the essentials. The notable gap is that no output schema exists, yet the description does not indicate the shape of the result (e.g., upper/lower bounds, expected move value), which would help an agent use the return 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%, and the schema already documents the single optional 'symbol' parameter with its default and examples. The description repeats the same example tickers without adding format or validation nuance, so baseline 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 uses a specific verb ('Computes') and named resources ('0DTE Expected Move and standard deviation volatility bounds') scoped to index/ETF symbols. An agent can tell exactly what output this produces. It does not, however, explicitly differentiate itself from the sibling thesis and calendar tools, leaving that inference to the agent.

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 gives a clear intended use case ('understand expected trading ranges and optimal strike placement for credit spreads and iron condors'), which points the agent in the right direction. But there is no guidance on when NOT to use it, no mention of alternatives, and no conditions such as market hours or data freshness requirements.

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 load, and it does disclose that this is a retrieval of a session-scoped snapshot ("today's trading session") and what the response contains field by field. It does not say what happens outside trading hours, how fresh the data is, or whether the values are cached, which are the remaining behavioral gaps.

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 first, payload second, usage trigger third. The enumeration of return fields is dense but each item earns its place because no output schema exists to carry that 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, no-annotation, no-output-schema read tool, the description covers purpose, contents, and when to call it, which is nearly everything an agent needs. Only edge-case behavior (non-trading days, data staleness) is left unaddressed.

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 takes zero parameters and the description correctly introduces none, so there is nothing to mis-specify. Baseline of 4 applies for a no-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 gives a specific verb and resource ("Retrieves the high-level macro thesis for today's trading session") and then enumerates the concrete payload: Analyst's Take bias, Narrative Risk 1-10, VIX and VVIX climate, and scheduled catalysts. The words "macro" and "general market direction" implicitly separate it from get_symbol_thesis, so an agent can route correctly without opening any schema.

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 states a clear trigger condition: use it when a user asks about general market direction, overall trading conditions, or the morning briefing summary. What's missing is an explicit exclusion or a named alternative (e.g. "for a single ticker use get_symbol_thesis instead"), so the agent must infer the boundary with its siblings.

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 carries the full burden, and it does disclose the temporal scope (current 0DTE session) and the specific data returned, including Spot, VWAP, GEX, gamma flip, IV rank, expected move boundaries, put/call walls, and trade flow. 'Retrieves' implies a read-only lookup, but there is no explicit statement about side effects, permissions, rate limits, or failure behavior. The return-field list and session scope are substantial behavioral context for a retrieval 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 front-loaded with the retrieval action and then the returned data set, followed by a usage sentence. It is dense with enumerated fields but each listed field supports the tool's purpose and helps the agent understand what will be returned. There is little wasted wording, though the output list makes the first sentence long.

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?

Because there is no output schema, the description appropriately names the returned data points and specifies that they apply to the current 0DTE session. It also states the symbol scope and primary use cases. It does not cover error behavior or explicit read-only semantics, but for a one-parameter lookup tool it is largely 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?

The input schema already has 100% description coverage, including the symbol parameter's examples and default of SPX. The description adds that the symbol should be an index or ETF and repeats example tickers, but does not add materially more parameter behavior beyond the schema. A baseline 3 is appropriate when the schema already 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 states a specific verb and resource: retrieves 8-point Market Microstructure and technical execution levels for a specific index or ETF for the current 0DTE session. It lists the returned fields, making the tool's purpose concrete. It does not explicitly name or differentiate against sibling tools such as get_expected_move or get_macro_thesis, so it falls short of a 5.

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 gives clear usage guidance: use when a user asks about levels, ranges, support/resistance, or setup viability for a specific symbol. It does not state when not to use the tool or name alternatives such as get_expected_move for a narrower expected-move query, so it lacks explicit exclusions.

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