Mansa African Markets

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

No annotations are provided, so the description carries full burden. It describes a read operation ('Look up') but does not disclose auth needs, rate limits, side effects, or return format. Basic transparency is present but limited.

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, front-loaded with the main action, and no unnecessary words. Every part is informative.

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 does not explain return values or behavior when both parameters are used. It is adequate for a simple lookup but lacks details on error handling or result format.

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 parameter descriptions. The description adds context by explaining the role of country filter (includes NIBSS, SWIFT, USSD) and gives an example for code, which adds 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 clearly states it looks up African banks and mobile-money institutions, specifying lookup by country (with code types like NIBSS, SWIFT, USSD) or by a single bank code with an example. This distinguishes it from sibling tools that focus on exchanges, rates, and indices.

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 via country or code but does not explicitly state when to use this tool versus siblings or when not to use it. No alternatives or exclusions are mentioned.

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 lists output fields (index value, change, trading hours, currency, status) which adds some transparency. However, it does not disclose any behavioral traits like side effects, permissions, or error handling.

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

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

One sentence front-loaded with action and resource, no redundant words. Every part serves a purpose.

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 get-one resource with no output schema, the description partially compensates by listing fields. It omits error handling or prerequisites, but given the low complexity, it is mostly 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?

Schema coverage is 100% with enum descriptions already defining the parameter. The description adds 'by ID' but does not provide additional meaning beyond what the schema offers.

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 specific verb 'Get' and resource 'detailed data for one specific African exchange by ID', listing fields (index value, change, trading hours, currency, status). This distinguishes it from siblings like get_african_exchanges (plural) or get_african_indices.

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 when-to-use or when-not-to-use guidance is provided. The description implies use for a single exchange by ID, but does not mention alternatives or exclude cases where multiple exchanges are needed.

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 correctly implies a read-only operation for today's movers. It is clear about what the tool does and is not misleading. However, it does not discuss potential errors, rate limits, or data freshness beyond 'today', which is a minor gap.

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, succinct sentence (12 words) that conveys the core purpose without redundancy. It is front-loaded and easy to parse.

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 and no annotations, the description is adequate for basic understanding but lacks details about the output format (e.g., what fields are returned, pagination, error handling). It does not clarify defaults like 'type' defaults to 'both', leaving some ambiguity for the agent.

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 baseline is 3. The description adds the 'today' context, which is not in the schema, but otherwise does not enhance understanding of the parameters beyond their schema definitions. The enum values for 'type' and 'exchange' are already well-described in 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 action (get), the resource (top gainers and losers), and the scope (on a specific African exchange today). It distinguishes from siblings like get_ngx_top_gainers/losers which are Nigeria-specific, and from get_pan_african_movers which likely covers multiple countries.

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 description does not mention prerequisites, conditions for use, or when not to use it. Siblings like get_pan_african_movers or exchange-specific movers are not compared, leaving the agent to infer usage from the name alone.

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. The description indicates a simple read operation with no side effects, but does not disclose data freshness, update frequency, or authentication requirements. Since there are no annotations to contradict, the description adequately covers the expected behavior for a data retrieval tool.

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

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

The description is a single sentence that packs all key information: verb, resource, specific exchanges, and data fields. No extraneous 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 output schema, the description lists the fields (index levels, daily change, stocks count, status), which is helpful. However, it could mention if the data is real-time or delayed, and whether the list is static or dynamic. Still, for a simple list tool, it is fairly 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?

There are no parameters, so the description does not need to add param-level detail. The schema coverage is 100% (empty schema), and the description already explains what the tool returns, which is sufficient.

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 verb 'Get', the resource 'list of all African stock exchanges', and enumerates specific exchanges and data fields (index levels, daily change, etc.), distinguishing it from siblings like get_african_exchange (singular) and get_african_exchange_stocks.

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. Given zero parameters, usage is straightforward, but the description doesn't mention that this returns all exchanges without filters, which could contrast with sibling tools like get_african_exchange (which likely returns one exchange).

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 carry the burden. It mentions the data fields and filtering/sorting capabilities but does not disclose behavioral traits like rate limits, data freshness, pagination, or limits on the number of results. For a read-only data retrieval tool, this is adequate but not comprehensive.

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, short and front-loaded. Every sentence adds value, but the structure could more clearly separate the supported operations (filtering, sorting) from the data fields. Still, it is concise without missing critical 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 5 parameters, no output schema, and no annotations, the description covers the basic purpose and capabilities. It could mention the response structure (e.g., list of stocks) or default behaviors (e.g., limit default 50) to fully compensate for missing annotations and output schema.

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 adds minimal extra value beyond the input schema; it restates that filtering and sorting are supported but does not explain syntax or behavior of parameters like 'limit' or 'order'. The inferred meanings are already clear from 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 verb 'Get', the resource 'stocks on a specific African exchange', and lists the data fields returned (prices, change percent, volume, etc.). It distinguishes from siblings like 'get_african_banks' (different resource) and 'get_ngx_all_stocks' (Nigeria-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 does not provide guidance on when to use this tool versus alternatives such as 'get_african_exchange_movers' or 'get_ngx_all_stocks'. There is no mention of when not to use it or any context-specific recommendations.

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 must convey behavioral traits. It indicates the tool is read-only ('current rates') and provides timestamps and sources, but lacks details on authentication requirements, rate limits, or how 'current' is defined (e.g., update 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?

The description is a single, efficient sentence that conveys the essential information without unnecessary words. It is well front-loaded with the main action and coverage.

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 a simple purpose, the description is fairly complete. It could be improved by specifying the data structure (e.g., currency codes, rate format) or the number of currencies, but it is adequate for the tool's simplicity.

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 has no parameters, so schema description coverage is 100%. With 0 parameters, the baseline is 4, and the description adds no redundant parameter details. However, it could briefly state that no parameters are 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 provides current USD rates for ~40 African currencies, with as-of timestamp and source. It uses a specific verb ('get') and resource ('African FX rates'), distinguishing it from sibling tools like 'get_african_policy_rates' or 'get_african_indices'.

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 current FX rates but does not explicitly state when to use this tool versus alternatives (e.g., historical rates from 'get_macro_history' or specific exchange tools). No when-not-to-use or exclusion criteria are provided.

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 bears full burden. It adequately discloses that the tool returns all major indices with values, daily change, and YTD performance. As a read-only query with no parameters, additional behavioral traits are not essential, though rate limits or authorization are not mentioned.

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, clear sentence that front-loads the purpose and immediately lists examples. Every word is useful; no wasted space.

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 low complexity (no parameters, no output schema), the description is fully complete: it explains what indices are returned and the data fields provided, making it easy for an agent to use without additional context.

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 has zero parameters and 100% coverage, so the baseline is 4. The description adds value by listing example indices and data fields, though no parameter guidance 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 retrieves major African market indices, listing specific examples (NGX ASI, GSE-CI, NASI, etc.) and the data included (index values, daily change, YTD performance), distinguishing it from sibling tools like get_african_banks or get_african_exchange.

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 notes this retrieves indices 'in one call,' implying it is a consolidated endpoint. While it does not provide explicit when-not-to-use or alternatives, the context of sibling tools suggests it is the primary tool for African indices, and the description is clear enough for correct selection.

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 full burden. It discloses that data is current, includes a live source for Nigeria, and provides source institution and URL. However, it does not mention any potential latency, rate limits, or whether the data is cached or real-time, leaving some behavioral aspects unclear.

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, well-structured sentence that conveys all essential information without any wasted words. It is front-loaded with the core action and resource, making it easy to parse.

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 output schema, the description provides key details: it returns policy rates and inflation for 18 economies, includes source information, and specifies Nigeria is live from CBN. However, it could be more complete by describing the output format (e.g., list of objects) or stating whether all 18 economies are always included.

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% (empty properties). According to guidelines, zero parameters warrants a baseline of 4. No further parameter documentation 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 'Get current central bank policy rates and latest inflation for 18 African economies', specifying the resource and scope. It distinguishes itself from sibling tools like get_african_fx_rates by focusing on policy rates and inflation, and even highlights a live source for Nigeria.

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 fetching policy rates and inflation data but provides no explicit guidance on when to use this tool versus alternative tools like get_african_indices or get_country_macro_indicators. No when-not-to-use or alternatives are mentioned.

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 provided, so description must bear full burden. It indicates the data is current and from latest auctions, but does not disclose update frequency, data freshness, required permissions, or any limitations. Adequate but could be more explicit.

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 extraneous words. Efficiently communicates tool purpose and coverage.

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?

Without an output schema, the description helpfully mentions 'T-bill/bond auction per tenor with stop rates and yields', giving users an idea of return structure. However, it does not specify return format, units, or cross-reference other African data tools. Mostly 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?

Parameter 'country' is fully described in schema as ISO-2 code with examples. The description adds '13 countries covered' which provides context but does not enhance parameter semantics beyond schema. Baseline of 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 it provides the current government yield curve for an African country, specifying T-bill/bond auctions per tenor with stop rates and yields. This distinguishes it from sibling tools focused on banks, exchange rates, indices, etc.

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 siblings, such as get_african_policy_rates or get_african_fx_rates. The mention of '13 countries covered' hints at scope but does not provide usage criteria or 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?

With no annotations, the description carries the full burden. It reveals that for Nigeria, the tool returns live CBN data including specific rates. However, it does not disclose behavior for other countries, error handling, or whether authentication is needed. The read-only nature is implied but not confirmed.

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 very concise: two sentences with no redundancy. The first sentence establishes the core function, and the second provides a concrete example, making it efficient and 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?

Given the tool's low complexity (one parameter, no output schema), the description is fairly complete. It specifies the input and example output for Nigeria. However, it lacks details on the output format for other countries and potential error states, which would be useful for full completeness.

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 sole parameter 'country' is well-documented in the schema with an ISO-2 code example. The description adds that the country is African and gives example codes, but does not add significant meaning beyond the schema, so 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 clearly states 'Get all macro indicators for one African country' and specifies the ISO-2 code input. It distinguishes from sibling tools by focusing on macro indicators like interest rates and inflation, and provides a specific example for Nigeria.

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 fetching African country macro indicators, and lists siblings that cover other financial data (e.g., stocks, exchange rates). However, it does not explicitly state when to use this tool versus alternatives, or provide usage 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 bears full responsibility for disclosing behavioral traits. It mentions monthly granularity and Nigeria's data start date, but omits details like result limits, missing data handling, or idempotency.

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 are concise and front-load the purpose. The second sentence provides a concrete example. However, it could be more structured with bullet points for clarity.

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 and no annotations, the description should explain the return format and behavior. It lacks details on pagination, time range validity, or how missing data is handled, leaving significant gaps.

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 has 100% description coverage, so the baseline is 3. The description adds example indicator names but does not enhance parameter meaning beyond what the schema already 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 clearly states the tool provides monthly history for an African macro indicator, with examples for Nigeria. This distinguishes it from siblings that focus on current rates or specific exchanges, but could be more precise.

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 like get_african_policy_rates or get_country_macro_indicators. The description implies historical data but does not set usage boundaries.

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 discloses handling of Sun–Thu markets and holidays, and the return values. It does not mention rate limits, auth, or side effects, but for a read-only status check it is fairly transparent.

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 purpose, no fluff. Every sentence adds value.

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?

The description provides sufficient detail for the tool's functionality despite missing output schema. It lists return fields and edge cases (weekends, holidays). Minor gaps: no error handling or invalid exchange 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?

The single parameter has 100% schema coverage with clear description. The tool description adds context (Sun–Thu markets) but does not enhance the parameter 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 clearly states the tool checks if an African exchange is open and lists the returned fields (reason, local time, session, next open/close). It distinguishes from sibling tools that are exchange-specific, like get_ngx_market_status, by being general.

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 checking any African exchange's current status, but does not explicitly say when to use this versus exchange-specific siblings like get_ngx_market_status. However, the context is clear enough.

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 states the tool 'gets' data, implying a read operation, but does not disclose behavioral traits beyond purpose. For a simple query, this is adequate but could mention read-only nature or data freshness.

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 18 words, front-loaded with the core action and resource. Every word is necessary and there is 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?

Given the low complexity (zero parameters, no output schema), the description adequately explains the tool's purpose and scope. However, it does not describe the returned data structure, which could be helpful for an AI agent using the output.

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 no parameters, and schema coverage is 100%. Baseline is 3, and the description adds no further parameter information since none exist. This 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 explicitly states the tool retrieves all 45 equities on Nigeria's NASD OTC Securities Exchange, with clear context of the market type. This is a specific verb+resource combination that distinguishes it from sibling tools targeting other exchanges or functions.

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 the full list of NASD stocks, but does not provide explicit guidance on when not to use or alternatives among siblings. The context is clear enough for a simple 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?

No annotations are provided. The description does not explicitly state that this is a read-only operation, nor does it mention behavioral traits like data freshness, caching, or rate limits. The context ('current prices') suggests live data but lacks clarity. The description carries the full burden for transparency and falls short.

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, efficient sentence that conveys the essential information without wasted words. It is front-loaded with the core action ('Get the full list').

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, no annotations, and no output schema, the description is mostly complete. It specifies the scope (all equities), count (148+), and key data fields. However, it does not mention data source, update frequency, or whether the list is sorted, which could be helpful.

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 are required, and the schema has 100% coverage (empty). The description adds meaning by listing the specific return fields (current prices, daily change percent, volume, market cap, and sector), which is valuable for the agent 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 that this tool returns the full list of all 148+ equities on the NGX with specific data fields (current prices, daily change percent, volume, market cap, and sector). It distinguishes itself from sibling tools like get_ngx_top_gainers, get_ngx_top_losers, and get_ngx_stock_price by explicitly indicating it returns the complete universe rather than a subset.

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 fetching the entire equities list but does not explicitly state when to use this tool over alternatives (e.g., get_ngx_top_gainers for movers, get_ngx_stock_price for a single stock). There is no 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?

No annotations are provided, so the description carries the full burden. It discloses the tool returns the 'latest 200' disclosures and lists content categories, but it does not mention authentication needs, rate limits, or data freshness.

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 that is front-loaded with the primary action and includes specific details. 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 zero-parameter retrieval tool without an output schema, the description is mostly complete, specifying source, count, and categories. It could mention pagination or refresh frequency, but this is adequate.

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 (schema coverage 100% trivially), so the baseline is 4. The description adds value by explaining what the tool returns, which goes beyond the empty 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 retrieves corporate disclosures and regulatory announcements from NGX-listed companies, listing specific examples like earnings, dividends, board changes, and filings. This distinguishes it from sibling tools that focus on stock prices, market overview, or gainers/losers.

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 does not explicitly state when to use this tool versus alternatives like get_ngx_all_stocks or get_ngx_stock_price. While it implies use for disclosures, there is no guidance on exclusions or prerequisites.

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 explains the read-only nature (gets overview) and lists returned fields. It doesn't discuss performance or update frequency, but given zero parameters and no destructive impact, the current detail is sufficient.

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: first defines the action and outputs, second provides usage guidance. Front-loaded, no unnecessary words, and every sentence adds value.

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 the return fields but does not specify the exact structure (e.g., object vs array). However, for a simple overview tool with zero params, this is largely adequate and consistent with sibling 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?

No parameters exist, so baseline 4. The description adds no param semantics because none are needed; the schema coverage is 100% with zero 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 the tool's purpose: get a real-time overview of the Nigerian Stock Exchange (NGX). It lists specific data points (ASI, market cap, volume, etc.) and distinguishes from sibling tools like get_ngx_all_stocks or get_ngx_stock_price by focusing on a high-level overview.

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 says 'Use this when the user asks about the Nigerian stock market at a high level.' This provides clear usage context. However, it does not mention when not to use it, though sibling tool names suggest alternatives for more detailed queries.

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 discloses the return values (OPEN, CLOSED, ENDOFDAY), which is transparent. No annotations are provided, but the behavior is simple and fully described. It does not mention any side effects or prerequisites, but none are needed.

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 efficiently conveys the purpose and output. No unnecessary 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 tool with no parameters and no output schema, the description is complete. It tells what the tool does and what it returns, which is sufficient for an agent to use 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?

There are no parameters, so the baseline is 4. The description does not need to add parameter information and is clear about the output.

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 checks whether the Nigerian Stock Exchange is open or closed, with specific return values. It is distinct from siblings like get_market_open_status or get_ngx_market_overview by focusing on a simple boolean-like status.

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 does not provide explicit guidance on when to use this tool versus alternatives such as get_market_open_status or get_ngx_market_overview. The usage is implied but lacks exclusions or 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, the description alone must disclose behavioral traits. It mentions returning 'latest price and trading history,' but omits details like data freshness, single-stock-only scope, or whether historical range is adjustable. 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?

Two efficient sentences with front-loaded primary action. No filler. Every word contributes to understanding.

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

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

For a simple one-parameter tool with no output schema and no nested objects, the description covers the core functionality and usage context adequately. No critical gaps.

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 provides 100% coverage with a description for symbol, including case-insensitivity and examples. The tool description adds limited additional meaning, mostly reiterating usage. Baseline 3 is appropriate as schema does the heavy lifting.

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

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

The description clearly states the tool retrieves the latest price and trading history for a specific NGX-listed stock by ticker symbol, with concrete examples (DANGCEM, GTCO, MTNN). This sufficiently distinguishes it from siblings like get_ngx_market_overview or get_ngx_top_gainers.

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 'Use this when the user asks about the price of a particular Nigerian stock,' providing clear usage context. It lacks explicit 'when not to use' or alternative tool references, but the guidance is sufficiently clear for an agent.

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 fully explain behavior. It fails to mention that the tool is read-only, data freshness, or pagination. The description only restates the tool's 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?

Two sentences, no wasted words, front-loaded with the core action. Every sentence adds value.

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 and no annotations, the description is sufficient for a simple list tool but lacks details on return format, data freshness, or any limitations. Adequate but not comprehensive.

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%, but the description adds the default value for 'limit' (10), which is not in the schema. This provides useful context 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 verb 'get', the resource 'top gaining stocks on the NGX today', and specifies ranking by percentage price increase. It distinguishes from sibling tools like get_ngx_top_losers.

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?

Provides explicit guidance: 'Use this when the user asks which Nigerian stocks are up the most today.' While it doesn't mention when not to use or alternatives, the context 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?

No annotations provided; description mentions ranking by percentage decline but lacks details on data freshness, real-time status, or any behavioral traits beyond basic 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?

Two concise sentences with clear action and usage context; no unnecessary 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?

Adequately describes purpose and return ranking, but could specify output format or data structure since no output schema exists.

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 the limit parameter described; description adds no additional meaning beyond what schema already 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 clearly states the tool retrieves top losing Nigerian stocks by percentage decline, distinguishing it from siblings like get_ngx_top_gainers.

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 says 'use when user asks which Nigerian stocks are down most', providing clear context but no exclusions or 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?

No annotations are provided, so the description must convey behavioral traits. It specifies the scope (all African exchanges) and metric (% change), but does not disclose data freshness, aggregation details, or any limitations. This is 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?

The description is a single sentence that is front-loaded with the action and scope. Every word earns its place, with no unnecessary 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?

Given the tool has one optional parameter, no output schema, and no annotations, the description covers the essential aspects: what it does, scope, and metric. It could mention the return format or ordering, but is otherwise sufficient.

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 (limit) is fully described in the schema with a default of 10. The description adds no additional meaning beyond the schema, so 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 clearly states the verb (Get), resource (biggest stock movers across ALL African exchanges combined), and distinguishes from sibling tools like get_african_exchange_movers by emphasizing the pan-African scope.

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 when to use this tool (for a combined view of movers across all exchanges), but does not explicitly state when not to use it or mention alternatives like get_african_exchange_movers for per-exchange data. The usage context is clear but lacks direct exclusions.

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