Option Desk

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds valuable context by explicitly stating it never fetches market data and frames the operation as private analysis, which clarifies data handling beyond the annotations. 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?

Two sentences with no filler. The primary function and the key constraint are front-loaded, making the description easy to parse quickly.

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 tool with 9 parameters, zero schema coverage, and no parameter descriptions, the description is too thin. It does not explain how to supply the option chain, what 'Summarize SYNTH' means, or how the parameters relate to each other. The output schema helps with return values, but the input side remains largely unexplained.

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 0%, so the description must compensate for 9 undocumented parameters, but it does not. It only hints that 'user-supplied option chain' relates to source_data/source_text without explaining rate, expiry, source_format, dividend_yield, or rights_confirmed. This leaves the agent with almost no semantic guidance for filling parameters.

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 and resource: 'Summarize SYNTH or analyze a user-supplied option chain.' It also adds a distinguishing constraint, 'never fetches market data,' which helps separate it from market-data tools. However, 'Summarize SYNTH' is slightly cryptic and does not fully clarify what SYNTH represents.

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 phrase 'for private analysis' and the explicit 'never fetches market data' imply the tool is for user-supplied or synthetic data rather than live market retrieval. No sibling alternatives are named, and there is no explicit when-to-use vs. when-not-to-use guidance beyond that.

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 and idempotentHint=true, and the description adds useful context about the dashboard being short-lived and auto-expiring after one hour. It does not describe auth requirements or failure behavior, but the annotation coverage lowers the burden.

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 no filler; the key action, resource, and expiry constraint are all front-loaded. Every word contributes meaning.

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 delete operation with a strong annotation profile and an output schema, the description covers what is deleted and when. The main gap is token provenance, but this is partially inferable from sibling import tools.

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 0% and the description never mentions the 'token' parameter. An agent must infer that the token identifies which imported dashboard to delete, with no guidance on where the token comes from or its format.

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 ('Delete') and a specific resource ('short-lived imported dashboard') with a clear expiry constraint. This distinguishes it from sibling tools like option_import_snapshot and option_validate_snapshot without needing to inspect schemas.

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 provides clear timing context: deletion is meant to happen before the automatic one-hour expiry, implying this is optional early cleanup. It does not name an alternative or explicit when-not-to-use condition, but the intended scenario is 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?

The description adds meaningful behavioral context beyond the annotations by stating that no live feed or hosted backtest capability exists even with uploaded history, and that the agent should not offer hosted backtests. This exposes a real limitation the agent would otherwise not know from the read-only, idempotent annotations alone.

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 three sentences, each contributing unique and necessary guidance. It front-loads what the tool checks, then clarifies a common misconception about live feed and hosted backtests. There is no repetition, filler, or unnecessary detail.

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 tool with no parameters, a clear purpose statement, and an existing output schema, this description covers the essential guidance: what to inspect, when to call it, and what not to promise. The existence of an output schema means the agent can learn the return format from that field, and the description supplies the operational context around it.

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 input schema is complete and the baseline score is 4. The description does not need to explain any parameter semantics; it refers only to fields returned by the tool rather than 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 begins with a specific verb and resource: 'Check the Option Desk data mode, source, refresh time, and public licence gate.' This distinguishes the tool from sibling plotting, snapshot, and strategy tools and tells an agent exactly what status information is available. It is not a tautology or vague restatement of the tool name.

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 when to use the tool: 'before requesting figures.' It also explicitly warns that no live feed or hosted backtest tool exists and instructs not to offer hosted backtests. However, it does not mention alternative sibling tools by name or describe a condition for choosing another tool. This is clear but not fully explicit about alternatives.

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?

Beyond the annotations (all false), the description discloses a meaningful retention/cleanup behavior ('Delete the artifacts after one hour') and the privacy-bound nature of the dashboard ('bearer-private'). It does not conflict with destructiveHint=false because the deletion is a post-import cleanup directive rather than the import operation itself, but it leaves the exact artifact scope unspecified.

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 short sentences with no filler; the main purpose is front-loaded and the cleanup instruction is a useful second sentence. Every word 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 tool with 10 parameters, 0% schema coverage, and no parameter explanations, the description is too thin. It covers the high-level purpose and one cleanup rule, but an agent would not know what to put in source_data, what rights_confirmed and retention_confirmed mean, or what the dashboard expects.

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 0% and the description provides no guidance on any of the 10 parameters, including the required 'symbol' or how to pass source data via 'source_data'/'source_text'/'source_format'. The only hint is 'user-supplied option-chain data', which is too generic to help an agent populate parameters correctly.

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 ('Import'), a specific resource ('user-supplied option-chain data'), and a destination ('bearer-private interactive dashboard'), which clearly distinguishes it from sibling snapshot, plotting, and validation tools. It is immediately obvious this is the ingestion tool for user-provided chain data.

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 phrase 'user-supplied' clearly indicates the tool is for importing external chain data rather than fetching or computing it, giving the agent a clear selection context. It does not explicitly list exclusions or alternative tools, so it stops 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.

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that plots are 'opaque PNG' and that SYNTH is computed from engine artifacts with no simulation/backtest. It does not disclose behavior like whether the tool requires rights_confirmed=true, how it handles invalid symbols, or what happens when rate/expiry are null. The added context is modest but not contradictory.

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 paragraph of three sentences, reasonably concise and front-loaded with the main action ('Render opaque PNG plots'). It includes useful context about SYNTH's limitations without excessive verbosity. It could be slightly more structured, but it 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?

With 10 parameters, 0% schema coverage, and an output schema present, the description is incomplete. It does not explain the role of most parameters, the meaning of the output schema, or how the tool handles the 'all' plot option. The SYNTH context is helpful but does not make the tool callable for non-SYNTH symbols or custom source data. The description leaves significant gaps for an agent to invoke the tool 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 0%, so the description must compensate for 10 parameters, but it only mentions plot types and the SYNTH symbol. It does not explain the meaning of rate, expiry, data_source, source_data, source_text, source_format, dividend_yield, or rights_confirmed. The description adds no value for the vast majority of parameters, leaving the agent to guess their semantics.

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 ('Render') and resource ('opaque PNG plots'), and enumerates the available plot types (market, Greek ladder, structure comparison). It does not explicitly distinguish itself from sibling tools like option_plots_from_snapshot or option_report_plots, but the mention of 'SYNTH sample' and 'engine artifacts' gives some context. It is clear enough to understand what the tool does, though sibling differentiation is weak.

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 by listing plot types and noting that SYNTH has no simulation/backtest because the hosted service has no price history. It does not explicitly state when to use this tool versus alternatives like option_plots_from_snapshot or option_report_plots. The context about SYNTH is useful but does not provide clear selection criteria among 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description adds value by disclosing that images are stamped with source, capture time, expiry, and warnings, and that temporary files are deleted before the response. This is useful behavioral context beyond the structured 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?

Three concise sentences, front-loaded with the core purpose, followed by two behaviorally important details. No filler 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?

Given nine parameters, zero schema descriptions, and no parameter guidance in the description, an agent cannot reliably determine how to supply the snapshot or set fields like 'rights_confirmed' and 'source_format'. The output schema may cover return values, but input semantics are under-specified.

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 0%, so the description must compensate, but it only hints at snapshot-related parameters. It does not explain required 'symbol', optional 'expiry', 'data_source', 'source_data', 'source_format', 'rights_confirmed', or how they relate to the snapshot input.

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 ('Create') and resource ('opaque market and Greek PNG images'), and scopes it to a 'user-supplied snapshot.' This distinguishes it from generic plotting siblings like option_plots, though it never names the sibling explicitly.

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 phrase 'from a user-supplied snapshot' implies the tool should be used when snapshot data is already available, but there is no explicit when-to-use/when-not-to-use guidance or reference to alternatives such as option_plots or option_import_snapshot.

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 declare readOnlyHint=true and idempotentHint=true, so the description doesn't need to restate safety. However, it does add a critical caveat that dealer signs are an assumption, not observed positions – a meaningful behavioral trait. But with no annotations covering every aspect, it does not disclose other traits like how errors are handled, whether it requires rights_confirmed to be true, or what outputs are returned.

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 two parts: the function and the caveat. It is succinct and front-loaded with the key outputs and inputs. Every word contributes value, and the caveat is placed at the end without bloating length. It is efficient, though slightly terse given the tool's complexity.

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 tool has 9 parameters, all optional, and no schema descriptions, the description is far from complete. It doesn't explain how to construct a 'user-supplied chain' through source_data, source_text, and source_format, nor does it mention the rights_confirmed parameter's role in confirming rights. The output schema exists, but the description could still benefit from stating that outputs are gamma walls, flip, and max pain. The caveat is useful but insufficient for an agent to call correctly without internal knowledge.

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 0%, and the description mentions only 'SYNTH' and 'user-supplied chain' but fails to clarify how the 9 parameters (e.g., rate, expiry, dividend_yield, rights_confirmed) relate to the computation. The parameter names are generic and self-explanatory, but the description does not clarify the distinction between source_data vs source_text vs data_source, which is crucial for generating a user-supplied chain. With 0% coverage and non-trivial parameters, the description must compensate but does not.

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 the tool computes gamma walls, gamma flip, and max pain from either SYNTH or a user-supplied chain. This distinguishes it from sibling tools that handle snapshots, plots, and validation, so an agent can infer its purpose as an analytical computation rather than data retrieval or visualization.

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 explicit guidance on when to use this tool versus alternatives, such as option_chain_snapshot or option_plots. The description implies data source flexibility but does not state when a user-supplied chain is preferred over SYNTH, nor does it mention prerequisites like needing a snapshot first. The sibling tools are not named as alternatives.

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 meaningfully adds the ephemeral one-hour expiry and bearer-URL behavior, which is not present in the annotations. Since annotations only contain false hints, the description carries the behavioral burden; it does so for the most important lifecycle trait, though it omits other possible side effects or prerequisites.

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 two sentences with no wasted words. It front-loads the core purpose and then presents the key expiration behavior, making it easy to parse quickly.

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?

Despite having an output schema, the description is incomplete for a tool with 10 parameters and several non-obvious confirmation flags. Important context is missing: how to provide user-supplied data, what the required rights_confirmed and retention_confirmed flags mean, and how this tool relates to sibling snapshot and plotting tools.

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 0%, and the description does not explain any of the 10 parameters. Ambiguous fields like rate, rights_confirmed, retention_confirmed, and source_text are left entirely undefined, so the agent cannot infer how to populate the parameters correctly.

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 a specific action ('Create a private interactive dashboard') and a distinct resource ('user-supplied data'). It is more informative than a tautology and hints at differentiation from snapshot/plot siblings, but it never explicitly names or contrasts an alternative 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 provides no guidance on when to choose this tool over options like option_import_snapshot, option_plots, or option_strategy_plot. The phrase 'from user-supplied data' implies some context, but there is no explicit when-to-use or when-not-to-use 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?

Beyond the readOnly/idempotent annotations, the description adds meaningful behavioral context: it never fetches live data, uses SYNTH or a user-supplied chain, and returns records (strategy_records, Greek units, scenarios, cost assumptions) that should be used verbatim in tables. This goes well beyond what annotations alone communicate and does not contradict 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 three tight sentences with no filler. The main output and preference statement are front-loaded, and the remaining sentences add high-value guidance about returned records and data-source behavior. 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?

For a tool with 10 optional parameters and zero schema-level descriptions, the description covers the output bundle and data-source constraints well, and the output schema handles return-value details. However, it leaves substantial gaps around several parameters and does not name sibling tools for single-chart alternatives, so an agent may still need to infer significant meaning from parameter titles alone.

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 0%, so the description must carry parameter meaning, but it only hints at 'up to three' payoff charts (strategies maxItems) and 'SYNTH or a user-supplied chain' (data source options). It does not explain rate, expiry, dividend_yield, source_data, source_text, source_format, or rights_confirmed, leaving most parameters under-specified for an agent.

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 ('Return'), a concrete resource set ('market map, Greek ladder, strategy comparison and up to three requested payoff charts'), and a key differentiator ('ONE widget'). It clearly distinguishes this aggregate reporting tool from individual plot calls without needing to open the 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?

The description explicitly says to prefer this tool for multi-chart reports instead of parallel individual plot calls, and cautions against inventing currency or multipliers when using the returned records. It gives clear context for when to choose it, though it does not name specific sibling tools or state exclusions for single-chart requests.

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=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context by enumerating the specific content returned (fields, repair rules, size limits, data-rights, retention policy), going beyond the annotations. It does not contradict annotations; the word 'Return' aligns with read-only 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 sentence that front-loads the verb 'Return' and lists five distinct categories. It is concise and waste-free, though the list is slightly dense. It achieves good structure without being overly 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?

Given that an output schema exists (though not detailed in the prompt), the description need not explain return values in depth. It provides a clear inventory of what the tool covers, which is sufficient for an agent to decide to call it. The only missing piece is explicit usage guidance, but that is covered under usage guidelines. Overall completeness is strong.

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 schema coverage is trivially 100%. Per calibration, 0 params gets a baseline of 4. The description correctly avoids discussing parameters since none exist, and the output schema (though not shown) likely describes the returned structure.

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 starts with 'Return' and specifies the exact resource: accepted CSV and JSON option-chain fields, safe repair rules, size limits, data-rights confirmation, and retention policy. This clearly distinguishes it from sibling tools like option_chain_snapshot (likely data retrieval) and option_validate_snapshot (likely validation).

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 states what the tool returns but does not explicitly say when to use it versus alternatives. It implies usage (when you need schema/field definitions), but lacks explicit routing like 'use for metadata, not for data' or exclusions. For a metadata tool this is a minor gap, but the absence of any alternative guidance makes it a 3.

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 safety (readOnly, idempotent, non-destructive), and the description adds useful context beyond them: the output is an opaque payoff PNG with permanent source and risk warnings. This discloses an important output characteristic that the agent would not infer from annotations or schema.

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, tight sentence with no filler. It front-loads the core action and then adds the essential output/warning behavior, which is appropriate for the tool's complexity.

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 10 parameters, a required symbol, and zero schema descriptions, the description is materially incomplete. It omits required inputs, source format expectations, the rights_confirmed gate, and the distinction between this and near-sibling strategy/plot tools.

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 0%, so the description must compensate, but it only vaguely references a 'user-supplied chain' and does not explain key parameters such as symbol (required), strategy default, source_data, source_text, source_format, or rights_confirmed. The agent would struggle to know how to supply the chain or which parameters matter.

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 ('Build one option structure') and a concrete output ('opaque payoff PNG'), which separates it from generic plot or snapshot tools. It does not explicitly name sibling alternatives, so some ambiguity remains with option_strategy_plot, but the 'user-supplied chain' qualifier adds useful distinction.

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 phrase 'from a user-supplied chain' implies this tool is for user-provided option data, but there is no explicit guidance on when to use this instead of option_strategy_plot, option_plots_from_snapshot, or other siblings. No exclusions or alternatives are named.

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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds valuable behavioral context: the output is an 'opaque PNG' (not interactive), it can use the SYNTH sample chain without user data, and it explicitly warns against starting a localhost dashboard. This goes beyond the annotations and helps the agent understand the tool's side effects and limitations.

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 three sentences, each earning its place: the first states the core function, the second explains data source options, and the third gives an explicit exclusion. It is front-loaded with the most important information and has no fluff.

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 tool's complexity (10 parameters, 0 required) and the presence of an output schema, the description covers the key decision points: what the tool produces, when user data is needed, and what not to do. It doesn't explain the meaning of all parameters, but the output schema and parameter names provide some structure. The description is complete enough for an agent to invoke the tool correctly in most cases.

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 0%, so the description carries the burden for parameter semantics. The description mentions 'SYNTH sample chain' and 'user-supplied chain data', which maps to the 'symbol' and 'source_data'/'source_text' parameters, but it doesn't explain the meaning of 'rate', 'expiry', 'dividend_yield', 'rights_confirmed', or 'strategy' beyond what the schema provides. The description adds some context but doesn't fully compensate for the 0% 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 states a specific verb ('Show') and resource ('option-strategy payoff as an opaque PNG in the conversation'), which clearly identifies the tool's core function. It also distinguishes itself from a localhost dashboard by explicitly saying 'Do not start a localhost dashboard.' However, it doesn't explicitly name a sibling tool to differentiate from, though the mention of 'engine playbook' and 'SYNTH sample chain' hints at the context.

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 clear context on when to use the tool: it can build any structure from the engine playbook on the SYNTH sample chain, and a market ticker requires user-supplied chain data. It also gives an explicit exclusion: 'Do not start a localhost dashboard.' It doesn't explicitly name alternative sibling tools, but the guidance is sufficient for an agent to decide when this tool is appropriate.

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=true, idempotentHint=true, and destructiveHint=false. The description adds a concrete side-effect disclosure: 'Delete all temporary files before the response.' This is useful behavioral context not captured in the annotations and does not contradict them because the deletion is limited to temporary files, not persistent user data.

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 short sentences, each carrying distinct information: purpose, output, and side-effect. The purpose is front-loaded, and there is no redundant or filler text.

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 9 parameters, zero schema descriptions, and no usage guidance, the description is too sparse for an agent to confidently construct a correct call. The output schema and annotations cover some gaps, but parameter semantics and alternative selection remain under-specified.

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 0%, and the description does not explain any of the 9 parameters. It only refers generically to a 'user-supplied option-chain snapshot', leaving required fields like 'symbol' and optional inputs such as 'source_data', 'rate', 'expiry', and 'rights_confirmed' completely unexplained. The description adds minimal semantic value beyond the raw schema names.

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 ('Validate') and identifies a distinct resource ('user-supplied option-chain snapshot'), while also stating the output ('Return corrections and a summary'). This clearly separates it from sibling tools like option_import_snapshot or option_delete_snapshot, even though those alternatives are not named.

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 phrase 'user-supplied option-chain snapshot' implies the tool is for validation of data the user provides, but there is no explicit guidance about when to use this tool versus option_import_snapshot, option_snapshot_schema, or option_chain_snapshot. No prerequisites, exclusions, or alternative conditions are stated.

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