PatternsRadar — NSE stock screener

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It names the destructive action but does not disclose permanence, whether the scan must exist, failure behavior, or side effects. The word 'Delete' conveys only the most basic behavioral trait.

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 concise sentence that is front-loaded with the core action and resource. There is no redundant or filler content.

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 minimal one-parameter delete tool, this is adequate but not rich. With no annotations and no output schema, the description is the only behavioral context; it could usefully mention that deletion is permanent or how missing scans are handled.

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's 'by name' merely restates the schema's name parameter without adding new semantic detail.

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') with a clear resource ('a saved scan') and the method ('by name'). It clearly distinguishes this tool from siblings like save_scan, run_scan, and list_saved_scans.

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 versus alternatives is provided. The purpose is obvious because only this sibling performs deletion, so usage is implied rather than stated.

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 present, so the description carries the full burden of behavioral disclosure. It does add one useful behavioral detail: 'most recent last' specifies the ordering of the returned bars. However, it does not mention whether the call is read-only, what happens for an invalid symbol, or any other edge-case 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, tightly written sentence that conveys the core resource, scope, and ordering behavior without any redundancy or fluff. It is front-loaded and 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?

There is no output schema and no annotations, leaving the description as the only source of behavioral and return-value context. The one-line description does not explain the response structure, what fields are included, or how errors/pagination are handled. It is under-specified for an agent trying to use the tool correctly without additional information.

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 each parameter already having a clear description. The tool description adds no semantic detail about the parameters beyond what the schema provides, so the baseline score of 3 applies.

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

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

The description states the resource ('OHLCV bars') and the scope ('for one symbol'), which clearly identifies the tool's function. It does not use a verb like 'retrieve' or 'return', but the tool name and the noun-phrase description make the purpose unambiguous. It is distinct from siblings like get_symbol and market_meta because it specifically targets OHLCV price 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 description implies this tool is used when you need recent historical price bars for a single symbol, but it provides no explicit guidance on when to prefer it over related sibling tools such as get_symbol or market_meta. There is no when-not-to-use or alternative routing.

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

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

With no annotations, the description carries the behavioral burden, and it does convey the informational scope by listing return fields and 'latest session'. However, it doesn't explicitly state read-only behavior, data freshness limits, or behavior for unknown symbols, leaving some assumptions to the agent.

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 entire definition is a single dense sentence with no filler, and it front-loads the one-symbol scope before listing return fields. The wording is slightly clipped/grammatically awkward because it lacks a verb, so it doesn't reach a 5.

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 single-parameter tool, the field list plus the schema's symbol documentation is enough to invoke it correctly. Still, without annotations or an output schema, it doesn't cover error behavior, output structure, or the exact meaning/market context of 'liquidity tier' and 'average delivery percentage', leaving some gap.

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 the parameter is already well documented as an NSE ticker with the RELIANCE example. The description's 'one NSE symbol' reinforces the scope but adds no new semantic detail, so the baseline 3 is appropriate.

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

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

The description identifies the resource (one NSE symbol) and enumerates the returned data fields (ISIN, listing dates, liquidity tier, last close, delivery percentage), making the tool's purpose clear. It lacks a proper verb—'Identity and latest session' is a noun phrase—and does not explicitly differentiate from search_symbols, so it falls just 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 guidance on when to choose get_symbol over alternatives like search_symbols or get_bars. An agent must infer from the word 'one' and the field list that this is for exact-symbol lookups, but no when-to-use or when-not-to-use guidance is given.

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 present, so the description carries the full burden. It discloses key limitations up front—no costs/slippage, universe measured today, and explicitly that results 'describe past matches, never a prediction.' It also lists the output dimensions, which is high-value behavioral context for a financial analysis 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?

Three sentences with no filler: the first states the action and outputs, the second defines the tool's limitations, and the third clarifies the epistemic status of the results. The most important qualifier ('A sketch, not a backtest') appears early and 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 and no output schema, the description still conveys purpose, limitations, and main result categories. It does not discuss parameter interactions or interpretation, but the schema covers the inputs and the description's output list is sufficient to call the tool with reasonable expectations.

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 adds no extra meaning about individual parameters beyond a general reference to 'user-chosen forward horizons,' and the schema already documents each field adequately.

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 opens with a specific verb ('Replay') and resource ('a Sift query'), then enumerates concrete outputs: win rate, payoff, excess return, monthly breakdown, and equity-curve approximation. This makes it clearly distinct from sibling tools like run_scan or get_bars, which concern live matching or raw bar data rather than historical performance 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?

It states that the tool is 'a sketch, not a backtest' and lists the missing components (costs, slippage) and the measurement caveat (universe as of today). This provides clear context for when results are appropriate, but it does not name alternative tools or explicitly contrast with run_scan, so it stops short of full when-to-use/when-not-to-use routing.

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

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

With no annotations provided, the description carries the full burden, and it does establish the core behavioral context: 'List' signals a safe read operation, 'saved' scopes it to persisted scans, and 'authenticated Sift account' conveys the auth requirement. However, it discloses nothing about pagination, ordering, limits, or response shape, which a list operation typically involves.

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 10-word sentence with the verb front-loaded and zero filler. Every word earns its place: 'List' states the action, 'saved' scopes the resource, and 'authenticated Sift account' sets the access context.

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

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

For a zero-parameter, zero-complexity list operation, the description is sufficient for correct invocation: no inputs are needed and the scope plus auth requirement are stated. Since no output schema exists, the return format (a list of saved scans) is implied but not detailed, which is a minor gap given how simple this tool is.

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

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

The input schema is empty with additionalProperties: false and zero parameters, so there are no parameter semantics to document. Per the zero-parameter baseline of 4, the description has nothing it needs to add, and nothing is ambiguous.

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 ('List') and a precisely qualified resource ('scans saved to the authenticated Sift account'), making the operation unmistakable. It is clearly distinct from sibling tools like run_scan, save_scan, and delete_scan by verb and the 'saved' qualifier, but it stops short of explicitly naming these alternatives.

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 when-to-use guidance, exclusions, or alternative routing is provided. Given siblings like run_scan, save_scan, delete_scan, and hitrate, an agent must infer when listing saved scans is the right choice rather than executing, saving, or deleting one. The context is implied at best.

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 discloses the exact data the tool returns (first/last session, row counts, symbol count) and frames it as a freshness/coverage check. While it doesn't explicitly state 'read-only', the content and tool name make side effects implausible. It gives useful behavioral context beyond the schema, which has no parameters.

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, each earning its place: the first defines the tool's content, the second states when to call it. No filler, no repetition of the tool name, and the key terms are front-loaded.

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

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

For a zero-parameter metadata tool with no output schema, the description covers purpose, content, and usage context. It lists the fields the agent can expect (first/last session, row counts, symbol count) and explains the practical use (freshness). Nothing needed to call the tool correctly is missing.

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 schema is trivially complete. The baseline for 0-parameter tools is 4, and the description offers no confusing or missing parameter information. Nothing more 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 defines what market_meta does: it returns coverage metadata about the market database, specifically first and last session, row counts, and symbol count. The second sentence explicitly frames this as an action ('Call this to find out how fresh the data is'), distinguishing it from sibling tools that retrieve bars, symbols, or scans.

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 a concrete use case: call this when you need to know how fresh the data is or what the database covers. It doesn't explicitly compare to alternatives like get_bars or search_symbols, but the metadata-focus makes the appropriate context clear. No exclusions are needed given the tool's simple informational role.

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 the full burden of behavioral disclosure. It clearly says the tool runs a query and returns matches, which implies a read operation, but it does not mention side effects, resource consumption, rate limits, or authentication requirements.

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

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

Three sentences with an effective front-loaded purpose, a useful example, and a fallback instruction. Every sentence earns its place, and the description is compact without being under-specified.

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 high schema coverage, the presence of an output schema, and the example query, the description is largely complete. It could be improved by noting that this runs an ad-hoc scan versus saving one, but that is a nice-to-have rather than a correctness gap.

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 all four parameters. The description adds value beyond the schema by showing an example Sift expression for the required source parameter, which clarifies the expected query syntax beyond a generic parameter description.

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 opens with a specific verb and resource: "Run a Sift screener query against NSE equities and return the matches." This makes the tool's role immediately clear and implicitly distinguishes it from siblings like save_scan, list_saved_scans, and get_bars.

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 a concrete Sift query example and explicitly tells the agent to call sift_reference first if unsure of the syntax. It does not, however, state when not to use this tool or contrast it directly with save_scan/list_saved_scans.

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

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

With no annotations, the description carries the burden of disclosing side effects, and it does disclose the key mutating behavior: saving under an existing name replaces the scan rather than creating a duplicate. It does not discuss permissions or irreversibility, but the core impact on account state is clear.

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 action is front-loaded, and the critical overwrite behavior is stated compactly in the second sentence.

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 only three parameters and no output schema, the description covers the essential purpose and the non-obvious replace behavior. It does not describe return values, but no output schema exists and the invocation semantics are clear.

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 of 3 applies. The description adds no parameter-level detail beyond the schema, and the overwrite behavior is already reflected in the schema's description of the name parameter.

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

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

The description states a specific verb and resource: saving a Sift query to the account. It also clarifies the upsert behavior, which distinguishes it from siblings like run_scan, delete_scan, and list_saved_scans. No ambiguity remains about what the tool does.

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

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

The description implies the tool is used to persist queries and explains what happens when saving under an existing name. However, it does not explicitly state when to use this over siblings such as run_scan or list_saved_scans, nor does it mention 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'Find' and describes the search input, without mentioning partial matching behavior, result limits, ordering, case sensitivity, or output format. The read-only nature is implied but not explicitly detailed.

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, concise, front-loaded sentence with no filler. It is efficient, though it could afford to include more behavioral or usage detail without becoming verbose.

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 two-parameter search tool with full schema coverage, the basic call is documented. However, there is no output schema and the description does not explain the return format or how results are ordered, which leaves the agent with partial information about what to expect.

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

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

The input schema already documents both parameters with 100% coverage, so the baseline is 3. The description repeats 'ticker or company name' but adds no new meaning beyond the schema and does not clarify limit semantics or defaults.

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 ('Find'), a resource ('NSE symbols'), and the search criteria ('by ticker or company name'). It is clear what the tool does, though it does not explicitly differentiate it from the closely related sibling get_symbol.

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 guidance on when to use search_symbols versus alternatives such as get_symbol. There are no exclusions, prerequisites, or conditions provided, leaving the agent to infer usage from the tool name and context.

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 of behavioral disclosure. It communicates that the tool returns comprehensive reference content about the query language, which is the essential behavior for a documentation tool. However, it does not describe the output format, length, or whether the tool is purely informational, though those are largely inferable from its purpose.

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, information-dense sentence that front-loads the tool's scope and ends with a clear usage directive. There is no filler or redundancy, and every phrase earns its place.

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

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

For a zero-parameter reference tool with no output schema, the description fully covers what the tool is, what content it provides, and when it should be consumed. There are no missing operational details that an agent would need to invoke it 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?

The tool has zero parameters, so the schema already fully describes the input surface. The baseline for zero-parameter tools is 4, and the description adds appropriate context by explaining what the reference contains instead of needing to document 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 clearly states this is a reference for the Sift query language, enumerating the exact content types it covers (fields, indicators, windows, operators, patterns). It also includes a directive ('Read this before writing a query') that tells the agent what the tool is for, distinguishing it from action-oriented siblings like run_scan and delete_scan.

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 explicit usage context: read this before writing a query. This is a clear instruction on when to invoke the tool. It does not explicitly exclude other tools or list alternatives, but given the tool's nature as a reference, the timing guidance is sufficient.

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