Optionscanner

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered elsewhere. The description adds one genuinely useful behavioral fact – that the chance-of-profit figure requires IV and days – but says nothing about how contracts scale the outputs or how optional inputs degrade the result. Modest added value above 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?

A single sentence, front-loaded with the instrument type, then a tight enumeration of outputs. Because there is no output schema, every listed metric earns its place rather than being redundant. No filler or hedging.

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, the description correctly compensates by naming the returned figures. The conditional requirement for IV and days is also disclosed. What is missing is any routing against the debit_spread sibling and any note on how the contracts parameter changes profit/loss totals, leaving a small gap for an 8-parameter tool.

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

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

Schema description coverage is 100%, so the baseline is 3; the description earns extra by tying iv_pct and days together as the joint precondition for the modeled chance of profit, which the schema documents only individually. It adds no guidance on credit sign conventions or contract scaling, but that pairing is real added meaning beyond the schema.

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 the exact instrument (bull put / bear call credit spread) and enumerates the computed outputs – width, max profit/loss, breakeven, return on risk, credit-to-width, chance of profit. An agent can distinguish this from debit_spread purely from the name and first clause. It stops short of explicitly contrasting itself with the debit_spread sibling, so it is clear but not fully differentiating.

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: it is a calculator for credit spreads, and the clause 'when implied volatility and days are given' hints that the probability output is conditional on supplying those two optional args. There is no statement of when to pick this over debit_spread, no prerequisites, and no exclusions, so the guidance is thin.

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, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds valuable behavioral context by naming the exact computed outputs and by stating that chance of profit depends on implied volatility and days being supplied, which the annotations do not cover.

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 with no wasted words. The resource and output list are presented immediately, making it easy for an agent to parse purpose and scope.

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?

There is no output schema, so the description usefully enumerates the return metrics an agent should expect. Combined with full schema coverage of inputs and rich annotations, the definition is mostly complete, though it does not explain calculation assumptions or edge-case behavior.

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

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

Schema description coverage is 100%, so the schema already documents every parameter, including the optional days and iv_pct fields for chance of profit. The description repeats the IV/days condition but adds no syntax, format, or constraint details beyond the schema.

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 calculation resource (call or put debit spread figures) and enumerates the exact outputs: width, maximum profit and loss, breakeven, reward to risk, debit-to-width, and chance of profit. This clearly distinguishes it from sibling credit_spread by specifying debit spreads.

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 no explicit when-to-use guidance, no alternatives, and no conditions for choosing this over credit_spread, profit_calculator, or probability_of_profit. Usage is only implied by the phrase 'debit spread figures.'

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, non-destructive, and closed-world, so the safety profile is covered. The description adds the conceptual model (options market pricing, 1σ and 2σ bands) which helps interpret results, but doesn't describe output shape, units of the result, or any assumptions. Adequate but not rich.

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 efficient sentence with no waste, front-loading the core output (1σ/2σ ranges) and then the inputs. Slightly dense but well-structured.

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 3-param pure computation with a fully documented schema and read-only annotations, the description covers the essentials. However, with no output schema, it leaves the return format (e.g., dollar ranges, per-σ labels) unstated. Minimum viable for the tool's complexity.

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%: each parameter has a clear description including the iv_pct convention ('30 means 30 percent') and days as calendar days. The description restates the inputs qualitatively but adds no syntax or format detail beyond the schema. 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?

Clearly states a specific computation: 1σ/2σ price ranges from options-implied volatility over a horizon. Names the required inputs (stock price, implied volatility, days) so the purpose is precise. It does not differentiate itself from siblings like profit_calculator or probability_of_profit, though the resource is distinct enough.

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?

Gives no explicit when-to-use guidance, no alternatives, and no exclusions. With nine sibling options-analytics tools, an agent gets no routing help for choosing expected_move over probability_of_profit or profit_calculator.

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 genuinely useful context beyond that: this returns the full text as Markdown and includes the link, which matters because there is no output schema to convey the return shape.

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, both front-loaded: what is returned first, the routing hint second. Every clause earns its place with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter read tool with no output schema, the description supplies the essential missing pieces: content types covered and the Markdown-with-link return format. An agent could call this correctly without further information, though pagination or size limits for very long articles are not addressed.

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?

With a single required parameter and 100% schema description coverage, the schema already defines 'slug' including example values. The description mentions slug as the lookup key but adds no syntax or format detail beyond the schema, so the 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?

States a specific verb (read) and resource (a Learn page), then enumerates the page types it covers (article, glossary term, calculator, research page). It is clearly separable from the sibling learn_search, which is named as the lookup alternative.

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?

Explicitly routes the agent: 'Use learn_search first when the slug is unknown', naming the alternative and the condition that selects it. The agent knows exactly when this tool is the right call versus its closest sibling.

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 read-only, idempotent, closed-world, non-destructive behavior, so the safety profile is covered. The description adds value beyond that by disclosing the return shape — "titles, summaries and links" — which is meaningful since no output schema exists. It does not mention result ordering or relevance 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?

Two sentences, front-loaded with the core action and only a modestly long topic enumeration that earns its place by helping match user phrasing. The return-format sentence is short and useful; nothing is padded.

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, the description compensates by stating what is returned (titles, summaries, links), and it defines the content scope well. The main gap is the absence of any pointer to learn_read for following up on a result, which an agent would need to complete the search-then-read flow.

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 query ("plain words") and limit (1-20, default 5) parameters are fully documented in the schema. The description adds nothing about query syntax, keyword behavior, or how limit interacts with relevance, so the 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?

States a specific verb (Find) and resource (Learn articles, glossary terms, calculators, research pages) and enumerates the topical domain it covers (greeks, IV rank, the wheel, etc.). It does not explicitly distinguish itself from the sibling learn_read, so an agent must infer the search-vs-fetch split from the names alone.

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?

"answers an options question" implies the usage context, which is enough to know this is the entry point for topic lookup. However, there is no explicit guidance on when NOT to use it, and the obvious alternative (learn_read) is never named, so routing between the two is left 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 establish read-only, idempotent, non-destructive behavior, so the description needn't restate safety. It adds real context beyond them by disclosing the return contents (legs, max profit and loss, breakevens, chance of profit, open links) and that results are computed off an example stock price. It does not explain how the days/iv inputs shift those example values.

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 dense sentence that front-loads the strategy enumeration before the return-content clause; nothing is wasted. It is slightly overloaded in one parenthetical, but every element 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 no output schema, the description correctly carries the burden of describing the return fields, and read-only annotations cover the safety profile. The remaining gap is how the three numeric inputs shape the reported examples and whether the list is static or price-dependent.

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

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

Schema description coverage is 100%, so the days, spot and iv_pct parameters are already fully documented, which sets the baseline at 3. The phrase 'built on an example stock price' faintly ties the payload to the spot input but adds no syntax or meaning for days or iv_pct.

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-plus-resource ('list the eleven standard structures the calculator knows') and enumerates exactly which structures are covered, so an agent knows precisely what comes back. It falls short of 5 because it never explicitly positions itself against siblings like credit_spread or debit_spread, though the enumeration implies the broader browsing role.

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: the mention of 'a link to open each one' suggests this is a discovery step before invoking a specific spread tool, but there is no explicit when-to-use or when-not-to-use statement. Nothing tells the agent whether to prefer this over directly calling debit_spread.

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, so the safety profile is covered. The description usefully discloses the three outputs (dollar budget, contract count, share of equity at risk), which matters since there is no output schema, but it says nothing about rounding of contract counts or handling of zero/negative inputs.

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 leading with the question it answers ('How many contracts fit a risk budget') and then enumerating inputs and outputs. Dense but every clause carries information; the mapping of inputs to outputs is slightly compressed but not wasteful.

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 three-parameter, fully documented, pure-computation tool the definition is nearly sufficient, and it compensates for the absent output schema by naming the returned values. It stops short of complete because computational conventions (rounding contract count down, unit assumptions) are left unspecified.

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% with units already documented for all three required properties, so the schema carries the load. The prose restates the same three inputs without adding format, range, or defaulting detail beyond what the schema 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 names a specific computation (contract count from a risk budget) and enumerates the outputs it returns, so an agent can tell what it produces without opening anything. It does not differentiate itself from near-neighbours like profit_calculator or what_if, 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?

There is no statement of when to reach for this tool versus the other calculator siblings (profit_calculator, probability_of_profit, what_if). Usage is only implied by the inputs listed, with no prerequisites or 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 cover readOnly/idempotent/non-destructive/closed-world, so the bar is lower. The description adds real value by disclosing that the result is model-derived and rests on the lognormal distribution implied by options prices, which tells the agent the output is an assumption-based estimate rather than an observed frequency.

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 leads with the computed quantity and then qualifies it with the model assumptions. Dense but every clause contributes; no filler or restatement of the tool name.

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 pure four-parameter calculator with no output schema, the description conveys the computation, its inputs and its modeling assumption well enough to invoke correctly. The only gap is the shape of the return value (decimal vs percent), which is left implicit.

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

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

Schema description coverage is 100%, so the schema already documents price, level, iv_pct and days. The description reinforces the interpretation of 'level' as a breakeven or short strike and ties IV to the lognormal model, but adds no units, ranges, or formatting beyond what the schema states.

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 computed quantity ('model probability that a stock finishes above or below a price level ... by a date') with the inputs that drive it (implied volatility, lognormal assumption). It is distinguishable from expected_move and profit_calculator by being a probability rather than a price move or P/L, though it never names those siblings 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 'a breakeven or a short strike' hints at the options-trade context, but there is no explicit when-to-use statement and no routing against alternatives like expected_move or profit_calculator. The agent must infer the scenario on its own.

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 (readOnly, idempotent, non-destructive), so the bar is lower. The description adds genuine value by disclosing exactly what is computed — max profit/loss, breakevens, net credit/debit, chance of profit, expected move — and that the return is a link into the Optionscanner calculator.

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?

Front-loaded with the core capability and output list, then input modes, then example queries, then the return artifact. Three dense sentences with no filler, though the output enumeration and example list make it longer than strictly minimal.

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, the description carries the return-value burden and does so by listing computed metrics and the resulting link. Inputs and outputs are both covered; only explicit sibling routing and the up-to-eight-leg edge behavior remain 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?

Schema coverage is 100%, so baseline is 3. The description goes beyond the schema by clarifying the strategy-vs-legs mechanism: a strategy name builds standard legs from the stock price, whereas legs are passed manually with strikes and prices, reinforcing their mutual exclusivity.

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 and resource ('Price any options trade with up to eight legs') and enumerates the computed outputs. The 'any ... up to eight legs' framing implicitly distinguishes it as the general-purpose pricer versus the single-strategy siblings, but no sibling is named, so differentiation stays inferential.

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?

Offers concrete usage examples ('max loss on a spread', 'breakeven on a straddle') and two input modes (strategy name vs explicit legs). However, it never says when to prefer this over siblings like credit_spread, debit_spread, probability_of_profit or expected_move, leaving the routing decision 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 cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false), so the bar is lower; the description adds genuine value by enumerating what comes back: P/L on a chosen date at a chosen price, P/L at expiration, and the change for one more day, one vol point and a one-dollar move. That effectively substitutes for the missing output schema. It does not cover modeling assumptions or accuracy caveats.

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, front-loaded with the value proposition followed by per-dimension detail and a concrete example. No filler or repetition of the title.

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, the description carries the return-value burden and does so reasonably well, and the 9-parameter schema (including nested legs and the strategy alternative) is fully self-documenting. The only gap is that it never explains the legs-vs-strategy mutual exclusivity in prose, though the schema states 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?

Schema description coverage is 100%, including per-leg fields (qty, days, strike, iv_pct, premium) and the strategy enum, so the baseline is 3. The description only implies the stock_price/days_from_now/iv_change_points scenarios and adds no format or interaction detail beyond the schema.

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+resource: it values an options trade under three scenario dimensions (stock move, time decay, IV change). This is clearly distinguishable in kind from sibling tools like expected_move or probability_of_profit, but the description never names or contrasts those siblings, leaving the differentiation implicit.

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?

"Use it for questions like what happens to my condor if the stock drops ten percent next week" gives a concrete triggering question, so an agent knows the scenario-analysis use case. It stops short of any exclusion or alternative routing (e.g. when to prefer profit_calculator or probability_of_profit instead).

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