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

With no annotations, the description carries the full burden. It explains the download action, parameters, and fallback behavior. However, it does not describe return values, error handling, or side effects beyond what is implied. Still, it provides substantial 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 well-structured with a strategy block and critical rules, ensuring important information is front-loaded. It is slightly verbose but every section adds value, earning a high score.

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 complexity (6 parameters, sibling tools), the description covers usage strategy, parameter rules, and post-call action. It lacks explicit return value details but references output schema and next steps, making it 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?

Despite 0% schema description coverage, the text description's Args section explains each parameter: stock_code (5-digit HK stock code), release_date (YYYY-MM-DD), title_keyword (Title substring), category (optional filter), news_id (HKEXnews NEWS_ID), local_key (Exact local bundle key). This adds 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 clearly states it downloads an HKEXnews announcement PDF (or HTML fallback) to local storage. It uses specific verbs ('Download') and resources ('announcement PDF'), and the context distinguishes it from sibling tools like list_hkexnews_announcements and parse_hkexnews_announcement.

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 explicit when-to-use guidance: 'Invoke ONLY as a fallback when keyword_search / get_announcement_pages returns file not found'. It also includes critical rules like preferring local_key and specifying out-of-scope reports, giving clear 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 provided, the description carries the full burden. It mentions that `page_count` defaults to 3 and max 5, and that `start_page` is 1-based. However, it does not disclose behaviors like what happens on invalid parameters, error handling, or the structure of the returned page content. The instruction 'Do not pre-check file existence' hints at potential failure but lacks depth.

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 well-structured with a main sentence, followed by a clear strategy section, critical rules, and an args list. It is concise (few lines) and front-loaded, with every sentence providing useful information.

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

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

Given the presence of an output schema (as indicated by context signals), the description does not need to detail return values. However, it lacks information on edge cases (e.g., page out of range) and the implication of 'Do not pre-check file existence' suggests potential failure scenarios that are not elaborated. Overall, it is mostly complete for the tool's moderate complexity.

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

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

Schema description coverage is 0%, so the description must add meaning. It explains each parameter: `local_key` as 'Bundle key', `start_page` as '1-based start page', and `page_count` with its default and max. This adds value beyond the schema's property titles, though it assumes knowledge of what a 'bundle key' is.

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 starts with a clear, specific verb+resource: 'Retrieve full page content for a range of pages from a parsed announcement.' This distinguishes the tool from siblings like `keyword_search` or `download_hkexnews_announcement` 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 includes a dedicated <strategy> section that explicitly states when to use this tool ('Directly invoke after keyword_search provides a start_page') and what not to do ('Do not pre-check file existence'). The <critical_rules> further clarifies that `page_count` has a default and max, and prefers using `keyword_search` for facts.

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 carries full burden. Discloses search behavior, relevance sorting, and that missing files trigger download/parse. Does not explicitly state read-only nature, but it's clearly a query 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?

Well-structured with sections (strategy, critical rules, args). Front-loaded with purpose. Slight redundancy: '1-5 keywords' appears in both rules and param description. Still efficient overall.

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, so return values aren't needed. Covers when to use, parameters, and behavior. Could mention that search is within a specific parsed announcement identified by local_key, but context is clear.

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

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

Schema description coverage is 0%, but description adds full meaning: local_key as bundle key, keywords as 1-5 items (not sentences), match_mode default ANY, max_results default 5 max 50. Critical rules further clarify keyword 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?

Clearly states it searches a parsed announcement by keywords and returns results sorted by relevance. Distinguishes from sibling tools by focusing on search within an already-parsed announcement, as opposed to downloading, listing, or parsing tools.

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 strategic guidance: directly invoke, do not pre-check file existence, prefer Chinese/English terms. Also gives critical rules on keyword count (1-5) and synonym expansion, and defaults for parameters.

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 carries full burden. Discloses exclusion of periodic report PDFs (t1=40000), inclusion of performance announcements, and limit max 50. Does not mention auth, rate limits, or error handling, but for a list operation the disclosure is fairly 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?

Highly concise with structured sections (intro, strategy, critical rules, args). Every sentence adds value. 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 6 parameters, no annotations, and an output schema exists, the description provides sufficient context: explains when to use, what is excluded/included, and parameter details. Complete for an AI agent to use 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?

Schema coverage is 0%, so description must compensate. Provides detailed parameter descriptions with examples (e.g., '00700', 'Inside Information'), format YYYY-MM-DD, defaults, and max limit. Adds significant meaning beyond 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?

Clearly states 'List available HKEXnews announcements for a company' with specific verb and resource, and crucially excludes full periodic report PDFs, distinguishing it from general listing tools.

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?

Contains explicit strategy section: use for discovering metadata before download; skip if user provides specific date/title and instead use keyword_search or download_hkexnews_announcement. Provides clear 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 provided, so the description carries full burden. It discloses caching behavior, re-download option, and strategic use. However, it does not explicitly state that it is a read-only operation, though 'diagnostic tool' implies safety.

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?

Well-structured with clear sections for purpose, strategy, critical rules, and args. Every sentence adds value, no fluff. Front-loaded with core 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 2-param diagnostic tool with an output schema, the description covers usage context, prerequisites, and behavior. It tells the agent exactly when and how to use it, which is complete for effective 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 adds full meaning: stock_code is a 5-digit HK stock code with examples, refresh is a boolean defaulting to false that forces re-download of mappings. Both parameters are adequately explained 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 stockId mapping for a Hong Kong stock code, using specific verb 'look up' and resource 'HKEXnews stockId mapping'. It is distinctly a diagnostic tool, differentiating it from siblings like download or list announcements.

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 'Invoke ONLY when download/list returns Stock code not found' and provides a strategy to retry after success. Also gives a critical rule to prefer refresh=false first, offering clear when-to-use and 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 must cover behavioral traits. It mentions the output format (page-split JSON) but does not disclose side effects, idempotency, or behavior on invalid keys. For a parse operation, it is likely safe, but the description could add more context about what happens if the local_key is invalid or the file is corrupted.

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 brief and well-structured: a purpose sentence followed by a usage <strategy> block. Every sentence adds value, and the strategy section is front-loaded. No redundant or irrelevant information.

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

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

Given the tool has one parameter and an output schema exists, the description provides essential information: purpose, usage timing, and parameter meaning. It covers the main use case but could be more thorough on error handling or output structure details, though the output schema likely handles the latter.

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 tool description carries the burden. It explains local_key as 'Bundle key returned by list/download' and gives an example format. This adds significant meaning beyond the schema's minimal title, clarifying the source and structure. However, it doesn't specify constraints like length or character set.

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 parses a downloaded announcement PDF/HTML into page-split JSON. The verb 'parse' and resource 'downloaded announcement' are specific, and the output format is given. It distinguishes from siblings like download_hkexnews_announcement (downloads) and get_announcement_pages (retrieves pages).

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 includes a <strategy> section that explicitly states when to use: 'Call immediately after a successful download_hkexnews_announcement, or when a retrieval tool says the PDF exists but JSON is missing.' This provides clear context and a specific alternative trigger, setting expectation for the proper invocation order.

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