Coil Scanner

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

No annotations, but description details output structure (scores, flag, note, regime mode). Does not mention latency, caching, or data freshness, but adequate for a zero-parameter 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?

Single sentence that is front-loaded with the main result, but slightly dense with multiple clauses. No wasted words.

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

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

Describes output items (scores, lanes, regime mode) well. Missing definitions of 'books' and lane types, but sufficient for a tool that requires no input.

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?

No parameters; schema coverage is 100%. Baseline for zero params is 4. Description adds context about output without needing to explain 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 states the tool returns 'today's ranked buy-list candidates per book across two lanes' with specific scores and flags, clearly differentiating it from sibling tools like get_market_leaders or get_crypto_trend.

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 explicit guidance on when to use this tool vs alternatives. The purpose implies it's for buy-list candidates, but no when-not-to-use or context for decision.

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 provides good behavioral context: rules-based verdict, UTC daily closes, long-only signals, and gates. It does not mention data freshness or error handling, but covers key traits for a read-only data 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 a single paragraph that efficiently front-loads the core purpose (Bitcoin and Ethereum trend signal) and then details components. Every sentence adds value without 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?

Given no output schema, the description lists major output components (state, gates, price, day change). It does not detail exact JSON structure, but the coverage is sufficient for an agent to understand what the tool returns.

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?

No parameters exist, and schema coverage is 100% trivially. Baseline of 4 applies as description does not need to add param info; there are no parameters to describe.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it returns Bitcoin and Ethereum trend signals, listing specific outputs (state, gates, price, day change) and distinguishing from raw price data. It associates with a specific resource (crypto trend) and verb (get), making purpose unambiguous.

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

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

The description implies use for crypto trend analysis and states it is not raw price data, but does not explicitly specify when to use vs siblings (e.g., get_market_regime) or provide exclusion criteria. Usage context is implied but not fully guided.

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

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

No annotations are provided, so the description must disclose all behavioral traits. However, it only describes the output format (top 10, per book, opportunity score) and does not mention any side effects, constraints, authentication, rate limits, or data freshness. The phrase 'confirmed uptrends' implies some selection logic but lacks detail.

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 is front-loaded with the key purpose ('Today's market leaders, ranked') and conveys the essential information efficiently. However, it could benefit from a slightly more structured format (e.g., breaking out components like ranking, selection criteria).

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 absence of an output schema and annotations, the description is the sole source of information. It explains the output (top 10, per book, opportunity score, uptrends), but omits details such as what an 'opportunity score' represents, how 'confirmed uptrends' are determined, whether the data is real-time or snapshot, and if any per-user customization applies. It is adequate for a simple read tool but not fully 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 tool has zero parameters, and the schema coverage is 100%. Since there are no parameters to describe, a baseline of 4 is appropriate. The description adds no parameter-specific information, but none is 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 clearly states that the tool returns today's market leaders: the top 10 leadership names per book by opportunity score, with full score read. It distinguishes itself from sibling tools like get_buy_list or get_stock_read by specifying the ranking and filtering (confirmed uptrends).

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

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

The description provides no guidance on when to use this tool over alternatives, nor does it mention any prerequisites or context. It simply describes the output without indicating when it is appropriate to call this tool.

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 conveys the tool's read-only nature and return structure (regime, mode, permission ladder). It does not disclose potential delays or side effects, but for a read operation this is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, efficiently front-loading the core idea. Every sentence adds value without 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?

Given no output schema, the description sufficiently covers return values (verdict, mode, permission ladder per book) and context. It is complete for a tool with no parameters.

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 no parameters, so baseline 4 applies. The description adds no parameter information, but none is 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 clearly states the tool's purpose: providing a top-down market read with regime verdict, mode, and permission ladder. It distinguishes itself from name-level signals and sibling tools like get_stock_read by focusing on overall market 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 explicitly advises to 'check this before acting on any name-level signal', providing clear guidance on when to use. However, it lacks explicit 'when not to use' or alternatives 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?

No annotations are provided, so the description must disclose behavior. It describes what is returned, but does not mention whether it is read-only, permissions, or data freshness. For a simple read tool, it is adequate but lacks extra 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?

The description is extremely concise and front-loaded: one sentence listing all components, plus 'Start here.' No wasted words.

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

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

Given no parameters, no output schema, and zero complexity, the description fully explains what the tool does. It is complete for its intended use as a high-level overview, and sibling tools fill in gaps for specific queries.

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 schema coverage is 100%. The description adds meaning by explaining the output content, beyond the empty schema. Baseline is 4, and it meets that.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it provides a market overview: 'regime verdict per book, today's top-5 ranked buy candidates, the biggest gainers and losers, and the BTC/ETH crypto trend-gate state.' The phrase 'Start here' distinguishes it from sibling tools that are more specific.

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 it's the initial tool to use ('Start here'), providing clear context for when to use it. However, it does not explicitly state when not to use it or name alternatives, though siblings are listed.

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. It clearly states the output contents (sector members with scores/rankings and ETF row) and the behavior for unknown values (returns sector directory). However, it does not disclose data freshness, idempotency, or authorization needs, which are minor gaps for a read 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 three sentences, each adding essential information: output contents, input formats, and error handling. It is front-loaded with the core purpose and contains no redundant words.

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

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

For a simple tool with one parameter and no output schema, the description covers purpose, input, and error behavior well. It could elaborate on the structure of the returned data (e.g., how rankings are presented), but overall it is sufficient for correct 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 only parameter 'sector' has a schema description that is generic, but the tool description adds concrete examples ('Energy', 'Information Technology', XLE, XLK) and explains the effect of unknown values. This significantly enhances understanding beyond the schema alone.

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's purpose: providing a detailed drill-down of a sector with scored and ranked members plus the sector ETF row. It specifies input types (sector name or ETF symbol) and distinguishes from sibling tools like get_stock_read and get_buy_list by focusing on sector-level analysis.

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 obtaining a sector's drill-down, but does not explicitly state when to use this tool over alternatives. No guidance on exclusions or prerequisites is provided, though the example inputs help clarify acceptable values.

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

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

No annotations are provided, so the description carries full burden. It discloses the output fields and the behavior for unknown symbols (returns valid-symbol directory). However, it does not mention any side effects, costs, or permissions needed, though the tool appears to be a read operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences: the first explains the output, the second covers scope and error handling. It is front-loaded and concise without any redundant 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?

Given the tool has only one parameter, no output schema, and no annotations, the description covers all essential aspects: input acceptance, output fields, and error handling. It is complete for a read 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 coverage is 100% with a description for 'symbol' as a ticker. The description adds valuable context by specifying the accepted universe (S&P 500, Nasdaq-100, macro names) and the error behavior, which goes 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 clearly states the tool returns a 'full Coil read' with specific fields like opportunity, board percentile, entry quality/state, hold strength, leadership, and book regime. It distinguishes from sibling tools which are for different purposes (e.g., market leaders, buy list).

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 single stock analysis but does not explicitly state when to use this tool over alternatives or provide exclusion criteria. No guidance on when not to use.

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