IT桔子 MCP

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

No annotations are provided, so the description must fully disclose behavior. It only states what is aggregated without mentioning any behavioral traits such as authentication needs, rate limits, or whether the operation is read-only. This is insufficient for a tool without annotations.

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

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

Two sentences efficiently convey the purpose and use case without fluff. The first sentence is front-loaded with the core action. Could be slightly more structured, but overall concise.

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 10 parameters, 0% schema coverage, no annotations, and no output schema description, the description is incomplete. It only addresses three parameters and omits the output structure, which is critical for an agent to correctly invoke the tool.

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

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

Schema description coverage is 0%, so the description should explain parameters. It mentions 'company tags, time periods, and regions' corresponding to tag_ids, date_ranges, and regions, but ignores 7 other parameters (e.g., scope_ids, event_category, tag_match_mode). The description adds minimal meaning beyond the bare 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 uses specific verbs and resources: 'aggregate number of financing events, disclosed amount events, invested companies, and total financing amount by company tags, time periods, and regions'. It clearly distinguishes from sibling tools like search_companies or count_companies, which have different purposes.

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 states the tool is 'suitable for answering financing statistics and year-over-year/quarter-over-quarter comparisons', providing clear context for when to use it. However, it does not mention exclusions or alternatives explicitly.

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

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

The description adds minimal behavioral context beyond the purpose. It mentions 'externally visible' companies, implying a visibility constraint, but does not disclose side effects, permissions, rate limits, or whether the operation is read-only. Since no annotations are provided, the description carries the full burden, and it 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 concise with two sentences. The first sentence packs the purpose and filter types, while the second adds usage guidance. It is front-loaded with the main action. No superfluous content, though it could be slightly more structured.

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

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

Given the tool has 14 parameters, no annotations, and an output schema (not shown), the description provides a reasonable overview of what the tool does and its filter capabilities. It covers the main filter types but does not explain the output format; however, since an output schema exists, that is acceptable. For a counting tool, the description is fairly complete for understanding its purpose.

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?

Despite zero schema description coverage, the description lists many filter criteria (keyword, industry, tags, location, year, unicorn, dark horse, qualifications) that map to the 14 parameters. This provides semantic meaning beyond the raw schema, helping the agent understand which parameters to use. However, it does not cover all parameters exhaustively (e.g., cities, provinces, fund_status_ids).

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 counts the total number of externally visible companies based on various filters (keyword, industry, tags, region, etc.). It explicitly distinguishes from the sibling tool search_companies by advising against iterating through pagination just to count. This is a specific verb+resource with clear differentiation.

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 provides usage guidance: it says to use this tool for answering questions about how many companies (counts) and warns not to use search_companies pagination just for counting. This is a clear when-to-use and when-not-to-use with alternative named.

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

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

Without annotations, the description carries the full burden. It discloses pagination behavior and the fields returned, which are key behavioral traits. However, it does not explicitly state that the tool is read-only or note any side effects, though that is implied.

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 result. It contains no extraneous words or 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 tool has four parameters (one required) and no annotations, the description provides a functional overview but lacks detail on the pagination mechanism and the optional fields parameter. The presence of an output schema somewhat compensates for return value documentation, but parameter semantics remain incomplete.

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

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

With 0% schema description coverage, the description must explain parameters. It clarifies that company_id is used for identification and implies cursor/page_size are for pagination, but it does not describe the fields parameter or the exact roles of cursor and page_size (e.g., cursor-based pagination behavior). This leaves significant gaps.

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 (query), resource (company funding history), and the specific criteria (by company ID, paginated). It also enumerates the returned information (rounds, amounts, currencies, investors, FA, valuation), leaving no ambiguity about the tool's purpose.

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 guidance is given on when to use this tool versus its siblings (e.g., search_company_investment_cases). There is no mention of prerequisites, exclusions, or alternative tools, which would help an agent choose appropriately.

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 states the tool queries a profile (implying read-only) but does not disclose any permissions, side effects, or whether the output is paginated. Minimal behavioral context beyond the action.

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 a clear verb and resource, listing key fields. It is concise but could benefit from a structured format separating parameter details from general behavior. No waste.

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?

An output schema exists, so return values are defined elsewhere. The description covers the main purpose and key fields, but lacks explanation of the optional 'fields' parameter. For a query tool with two parameters, it is 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?

The input schema has 2 parameters (company_id, fields) with 0% schema description coverage. The description mentions the fields included in the profile but does not explain the 'fields' parameter (which allows filtering specific fields). Description adds no meaning beyond the schema for company_id, and ignores the optional 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 clearly states the tool queries a company profile by ID and lists included fields (industry, tags, region, etc.). However, it does not explicitly differentiate from sibling tools like get_company_funding_events or search_companies, though the resource 'profile' is distinct.

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 guidance on when to use this tool versus alternatives (e.g., search_companies, get_company_funding_events). The description only provides a straightforward use case without 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?

No annotations are provided, so the description carries the full burden. It mentions output fields but does not disclose whether the tool is read-only, requires authentication, or how it handles missing IDs. The description offers minimal behavioral 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 a single sentence that front-loads the purpose and key output fields. It is concise and avoids unnecessary words, though it could include more 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?

Given the presence of an output schema and only two parameters, the description provides a reasonable overview. However, it lacks details on error behavior, return structure beyond the three items, and any usage constraints, making it minimally 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?

The description explains the investor_id parameter (by institution ID) but does not clarify the optional fields parameter. With 0% schema description coverage, the description should compensate more fully, but it only partially addresses one of two 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?

Clearly states the tool queries an investor profile by institution ID and lists what it includes (investment cases, latest investment time, active industry summary). Distinguishes from siblings like search_investors (which searches by name) and get_company_profile (which is for companies).

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 when you have an investor ID and need a profile, but it doesn't provide explicit guidance on when to use this versus alternatives or mention any prerequisites or exclusions.

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

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

No annotations provided; description gives basic purpose and what it returns but omits behavioral traits like authorization, idempotency, or side effects. 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?

Single sentence, front-loaded with key categories, no wasted 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?

Output schema exists, lowering burden. Description covers core purpose but lacks details on parameter usage and return structure. Adequate for a simple 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 has 0% description coverage; description does not explain the 'lookup_type' parameter, its possible values, or default behavior. No mapping of listed categories to parameter values.

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?

Description clearly states it queries dictionary options for categories like industries, funding rounds, etc., and maps natural language to IDs. Verb '查询' and resource '字典选项' are specific. However, it doesn't differentiate from siblings like search_tags that might also provide lookups.

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 versus alternatives. Mentions mapping natural language to IDs, implying a conversion step, but no when-not or alternative suggestions.

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. It discloses that the tool aggregates financing events, converts to RMB, sorts, and allows exclusion of certain rounds. However, it lacks details on authorization, rate limits, pagination, or behavior for large datasets, so it's moderately informative.

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, dense sentence that packs key information about purpose and filters. It is concise and front-loaded with the main action, though more structured formatting could improve readability.

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

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

Despite having 13 parameters and no annotations, the description does not explain many parameters (e.g., location vs provinces vs cities, IDs) or the output format. Enrichment is needed for a complex tool with an output schema present.

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 0% as parameter descriptions are empty. The description only generically mentions filter types (tags, industry, region, time, round) but does not clarify parameters like 'scope_ids', 'company_tag_ids', 'exclude_round_ids', or 'company_tag_match_mode'. This adds minimal value over the schema itself.

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 function: ranking companies by total funding amount in RMB with filtering by tags, industry, region, time, and round. It also specifies the use case for top rankings in a given track, distinguishing it from siblings like 'aggregate_funding_by_tags'.

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 mentions when to use this tool ('suitable for answering TOP rankings of total financing amount in a certain track') and explicitly indicates that IPO and post-IPO rounds can be excluded. It provides context but does not directly compare with sibling tools or when to avoid its use.

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, description only says 'returns candidate matches' without elaborating on output format, error handling, or read-only nature. Minimal transparency despite carrying the full burden.

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

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

Two concise sentences with a concrete example; no wasted words. Front-loads main action.

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?

Provides a concrete usage example linking to another tool, but lacks parameter explanations and behavioral details like matching behavior for 'names' field. Given 4 parameters, description is incomplete.

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?

Description does not explain any of the 4 parameters; schema coverage is 0%. Parameters like 'fields', 'exact_only', 'limit_per_name' are left to inference from their names, which may be insufficient for correct usage.

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?

Description clearly states the tool resolves company names to specific ID system (IT桔子 company_id) in batch, and provides an example workflow. However, it doesn't explicitly differentiate from sibling tool 'search_companies' which might have overlapping functionality.

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?

Description gives a usage scenario (batch resolution followed by another tool call), but does not specify when not to use or compare to alternatives like search_companies, leaving the agent to infer.

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 mentions 'publicly visible' and pagination, which imply a read-only search. However, it does not detail authorization needs, rate limits, or real-time vs. cached data. The behavioral disclosure 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?

Two sentences: first covers purpose and filters, second gives usage guidance. No unnecessary words, well front-loaded. Efficient and clear.

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 17 parameters and an output schema exists, the description covers the tool's main function, filters, pagination, and use case differentiation. It doesn't detail every parameter but provides sufficient context for an agent to understand when to use it. Some minor gaps (e.g., pagination mechanism) are left to the 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 description coverage is 0%, so the description must compensate. It lists filter criteria but does not map them to the 17 parameter names (e.g., 'industry' likely maps to scope_ids, but not explicitly). Parameters like fund_status_ids, qualification_type_ids are not explained. This leaves ambiguity.

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 searches for publicly visible companies with pagination, lists many filter dimensions (keyword, industry, tags, region, etc.), and specifies use cases like finding companies by name or supplementing project background. It also distinguishes from the sibling tool count_companies.

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 provides when-to-use and when-not-to-use guidance: it's suitable for list searches and background info, but for total counts, it directs to use count_companies. This helps the agent choose correctly.

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 reveals consolidation behavior ('按组织关系归并'), but does not disclose authentication needs, side effects, or other behavioral traits. With no annotations, more detail would be beneficial.

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 concise with two sentences, though it lacks structural elements like parameter lists or usage notes. It is appropriately 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?

With 12 parameters and no annotations, the description is insufficient for complex tool usage. It explains the overall purpose but lacks details on parameters, output, or preconditions.

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 12 parameters with 0% schema description coverage. The description provides no parameter-level explanation, failing to compensate for the lack of schema documentation.

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 queries external investment cases, consolidating investment entities by organizational relationship. It distinguishes from sibling tools like search_investor_cases by focusing on company outward investments.

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 clear usage context: answering questions about track-specific company investments, with an example. However, it does not explicitly state when not to use it or compare to 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 carries the full burden. It explains only event_type and event_category but omits behavioral details such as default pagination, rate limits, authentication needs, or the read-only nature. It does not describe sorting, ordering, or what happens when parameters are omitted.

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 and reasonably concise, but the first sentence is vague ('等条件' - etc. conditions) and the second focuses only on two parameters. It front-loads purpose but the vague 'etc.' reduces clarity. More specific structure could improve efficiency.

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 14 parameters and no annotations, the description is incomplete. It covers only two parameters and does not address cursor-based pagination, city/province filtering, field selection, or date range format. An output schema exists but is not provided; the description still fails to bridge the gap for many 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?

Schema description coverage is 0%, so the description must compensate. It explicitly explains event_type and event_category with enumerated values, which adds meaningful context. However, 12 out of 14 parameters (including cursor, page_size, cities, provinces, date_start, date_end, etc.) receive no explanation, leaving significant ambiguity.

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 'paging query events by time, industry, tags, rounds, etc.' which specifies the verb (query), resource (events), and filtering conditions. It also explicitly explains two key fields (event_type and event_category) with their possible values, making the tool's purpose distinct from siblings like search_companies.

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 when filtering events by various criteria but does not provide explicit when-to-use or when-not-to-use guidance. It lacks mention of alternative tools like get_company_funding_events for company-specific needs, leaving the agent to infer 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?

No annotations provided, so description bears full burden. It only mentions return fields, missing behavioral traits like pagination, cursor, or parameter constraints.

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 is concise and front-loaded with purpose, but too brief for a tool with 10 parameters; lacks necessary detail.

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

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

Description omits filtering capabilities, parameter roles, and output structure; incomplete given the tool's complexity and schema coverage.

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

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

Schema description coverage is 0% and description fails to explain any of the 10 parameters; no parameter meaning is conveyed.

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?

Description clearly states the tool queries FA service cases and lists return fields, but does not differentiate from sibling tools like search_company_investment_cases or search_investor_cases.

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 guidance on when to use this tool versus alternatives; lacks context or exclusions.

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

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

With no annotations provided, the description carries full burden. It mentions pagination behavior and return fields but does not disclose other behavioral traits like error handling, permissions, or rate limits. It 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?

The description is very concise at one sentence and front-loads the action and key detail (by institution ID with pagination). It is efficient but could be slightly expanded without harm.

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?

An output schema exists so return values are documented elsewhere. However, with 7 parameters and no annotations, the description lacks details on filtering options and behavior for optional parameters. It is adequate for a simple query but incomplete for full 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?

Schema description coverage is 0% with 7 parameters. The description only implicitly references 'investor_id' and pagination (page_size, cursor implied). It does not explain other parameters like fields, round_ids, scope_ids, sub_scope_ids. This is insufficient compensation for the lack of schema documentation.

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 queries investor investment cases by institution ID with pagination, listing specific return fields. It uses a specific verb-resource combination and distinguishes from sibling (search_company_investment_cases) by focusing on investor ID.

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 when an investor ID is available and pagination is needed, but it does not provide explicit when-to-use or when-not-to-use guidance. Given the presence of sibling tools, it lacks explicit 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 full burden. It discloses core behavior (keyword search) and output fields. However, it does not mention pagination (despite cursor/page_size parameters), rate limits, or side effects, leaving moderate gaps.

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 in Chinese. It front-loads the action and return fields, with no wasted words. However, given the complexity (8 parameters), it is somewhat under-informative, but still efficiently structured.

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

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

Given the tool has 8 parameters, zero schema descriptions, no annotations, and an output schema not shown, the description is insufficient. It covers only keyword search and return fields, ignoring other filtering and pagination capabilities, leaving significant gaps 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?

Schema description coverage is 0%, so the description must compensate. It only mentions the keyword parameter implicitly but does not explain is_fa, cursor, fields, prop_ids, page_size, is_state_owned, or is_government_guidance_fund. The agent receives no guidance on how to use these 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 action: search investment institutions by keyword, and lists the return fields (ID, case count, recent investment time, active industries). This clearly distinguishes it from sibling tools like search_companies or search_investor_cases.

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 versus alternatives. It does not mention prerequisites, exclusions, or context for choosing this over siblings such as search_companies or get_investor_profile.

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 only states the function without disclosing behavioral traits like case sensitivity, fuzziness, pagination, or error handling. The mention of returning 'tag_id' is helpful but minimal.

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 with no wasted words. It front-loads the purpose and provides a practical use case. Highly efficient.

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 simplicity (2 params, output schema exists), the description adequately covers the primary function and use case. However, it lacks parameter details and behavioral context that would make it fully self-contained for an AI 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 description coverage is 0%, but the description does not explain the parameters (keyword, limit) beyond implying keyword is the search term. The purpose of 'limit' is not mentioned, and defaults are not clarified. The description adds some meaning but insufficiently compensates for the lack of schema descriptions.

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 'search tags by keyword' and provides a specific use case (mapping user input terms like AI, robotics to tag IDs). It distinguishes the tool from siblings by focusing on tag search, though it doesn't explicitly exclude alternatives. The verb+resource is 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 explicitly says 'suitable for mapping user input track words to tag_id', giving clear context on when to use the tool. However, it doesn't provide when-not-to-use scenarios or mention alternative tools.

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