Al Jazeera 360

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

Annotations declare readOnlyHint=true, and the description is consistent with that. The description doesn't add much behavioral depth beyond what annotations provide—it doesn't mention pagination, filters, or the structure of the returned content. It adds useful context about the available sections and the meaning of 'section_id', but for a read-only browse operation, the transparency 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 concise and well-structured. It opens with a clear purpose sentence, provides the bilingual context, and then lists all valid sections in a bulleted list. The parameter explanation follows. While the list is long, it is necessary for usability. It avoids fluff and stays focused.

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 that the tool has a single parameter with a well-defined list of values, the description is nearly complete. It doesn't describe the return structure, but the presence of an output schema (not shown but indicated) likely covers that. It doesn't mention potential edge cases like invalid section IDs, but the list serves as a guide. For a simple browse operation, this is 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?

Schema coverage is 0% (the schema only provides the parameter name 'section_id' with no description). The description compensates by explaining that section_id is the section identifier and listing valid values (e.g., 'AJA', 'Documentaries'). This gives the agent concrete guidance on what to pass, which is essential given the lack of schema-level 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 states a clear verb ('Browse') and resource ('content in a specific section/channel'), and provides a comprehensive list of valid sections with bilingual labels. This clearly distinguishes it from siblings like 'list_sections' (which likely lists sections) and 'search_videos' (which searches across all content).

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

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

The description implies this tool is for browsing a specific section, as opposed to searching or listing sections, but it does not explicitly state when not to use it or name alternatives. The inclusion of the full section list helps the agent know what values to pass, but it doesn't explicitly say 'use this instead of search_videos when you have a section known.'

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 readOnlyHint annotation already declares the tool as safe and read-only. The description adds useful default behavior for section_id ('AJA') and count (10) beyond the raw schema, but it does not disclose ordering, pagination, or empty-result behavior. With annotations covering the main safety profile, this is adequate but not particularly 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 short and front-loaded with the core purpose, followed by a clean Args block. The Arabic sentence repeats the English purpose, which adds some redundancy for an AI agent but remains harmless. Overall, it is concise and well-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?

This is a simple two-parameter, read-only retrieval tool with an output schema present, so the description does not need to explain return values. The description covers the operation, section scope, and count meaning. It lacks minor behavioral details like ordering or pagination, but for this tool the overall context is 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 schema has no property descriptions, so the Args block is the primary source of semantic meaning. It clearly explains that section_id selects the section and count controls the number of episodes, and it restates defaults. The explanation is complete for both parameters, though it does not go into deeper constraints such as max count or accepted section formats.

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

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

The description uses a specific verb and resource: 'Get the latest episodes from a specific section on Al Jazeera 360.' It clearly states the operation and scope possibility. However, it does not explicitly differentiate itself from sibling tools like get_season_episodes or get_trending_content, so it does not fully earn a 5.

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

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

The description makes it clear that this tool is for retrieving latest episodes by section, and the Args block adds useful context about section_id and count. It does not mention alternatives or when not to use this tool, so the agent is left to infer how it differs from related episode and browsing tools.

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?

Annotations already declare readOnlyHint=true, and the description adds useful behavioral context: season_id comes from get_series_details and max_episodes caps the result count with a default of 20. The phrase 'all episodes' is slightly at odds with that cap, but the cap is disclosed in the Args section, so this is not a serious 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 English text is front-loaded with purpose and prerequisite, followed by a clean Args block. The Arabic duplicate is redundant for an agent, but the overall structure is scannable and not padded with filler.

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 read-only, two-parameter tool with an output schema, the description supplies the purpose, prerequisite call, and parameter semantics needed to invoke it correctly. The only minor gap is not explicitly reconciling 'all episodes' with the default max_episodes cap, though that cap is documented in Args.

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 fully compensates by explaining both parameters: season_id is the ID obtained from get_series_details, and max_episodes is the maximum number of episodes to return with its default. This adds real meaning beyond the bare integer types 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 opens with a precise operation: 'Get all episodes in a specific season.' It names the resource (season episodes), the key identifier (season_id), and clearly separates this from series-level tools like get_series_details and get_latest_episodes.

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 instructs the agent to call get_series_details first to obtain season IDs, giving a clear prerequisite and usage order. It does not list exclusions or alternative tools, so it stops short of a full 5.

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?

Annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description adds the 'including all seasons' detail, which is useful but minimal. It doesn't describe the return format or any additional behavior, though the output schema exists to cover that. This is acceptable 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 extremely concise—two short sentences plus the args line. It front-loads the purpose and includes the example efficiently. Every word earns its place with no fluff or repetition.

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 single-parameter read-only tool, the description is largely complete. The output schema handles return values, and the example clarifies the parameter. It could mention what 'detailed information' encompasses, but given the low complexity, it's 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 schema only specifies series_id as an integer with no description (0% coverage), so the description's example ('e.g., 2355 for الدحيح') adds concrete value by clarifying the expected value. It also explicitly calls it 'numeric ID,' reinforcing the type. This compensates well for the schema's lack of description.

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

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

The description clearly states the tool retrieves detailed series information, including all seasons, and provides an example ID. It identifies the resource (series) and the verb (get), but it doesn't distinguish from sibling tools like get_series_seo_map or get_series_seo_map, which might also target series details. Without that differentiation, it's clear but not fully 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?

The description provides no guidance on when to use this tool versus alternatives like get_season_episodes or get_series_seo_map. It doesn't mention any conditions, prerequisites, or exclusions, 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?

Annotations only provide readOnlyHint=true, so the description carries most of the behavioral burden and does add real context: source precedence, the fallback-language rule, the 'if neither exists, list available languages' outcome, and team-endpoint download links. It does not mention pagination or size limits, but for a read-only tool this is a solid disclosure.

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 English portion is front-loaded and efficient, but the Arabic sentence is a near-verbatim restatement of the opening, adding length without new information, and the Args block partially duplicates the schema. Structure is clean but not lean.

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 an output schema present, return-format explanation is not required, and the description covers the source logic, all five parameters, and failure behavior. It is nearly complete; only the absence of any sibling-routing guidance keeps it from full marks.

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, and it largely does: every one of the five parameters is documented with meaning and defaults (language default 'ar' with fallback, format options text|plain|srt|vtt, start_minute default 0, end_minute defaulting to episode end). It supplies enum values the schema lacks entirely.

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 names a specific verb+resource ('Get the full text of an episode') and precisely defines the two content sources (platform subtitle file vs. indexed transcript), including the fallback order. An agent can distinguish this from index-searching siblings like search_video_index without opening any schema.

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

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

It clearly describes internal behavior (source precedence, range filtering, language fallback) and what happens when nothing exists, but never states when to pick this tool over a sibling such as search_video_index or get_video_analysis. Usage is implied rather than routed.

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?

Annotations already declare readOnlyHint=trueways, so the read-only safety profile is covered. The description adds useful context about the response scope (featured shows, most-watched videos, latest episodes, editorial picks), but it does not disclose behaviors like sorting, pagination, or regional/language defaults. 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 short, starts with the core action, and uses a compact enumerated list of result categories. The English/Arabic duplication adds some redundancy for an automated agent but does not inflate the description beyond a few lines.

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?

This is a simple zero-parameter read-only tool with an output schema present, so the description does not need to explain return types. It states the content categories and the read-only annotation covers safety. It is complete for invocation, though a brief usage-routing sentence would make it stronger.

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 schema has zero parameters and 100% schema description coverage, so there are no parameter details for the description to clarify. The baseline of 4 applies because the agent has nothing to resolve about arguments.

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

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

The description uses a specific verb ('Get') and names a concrete resource ('trending and most-watched content on Al Jazeera 360'), then enumerates the returned categories: featured shows, most-watched videos, latest episodes, and editorial picks. It is clear and action-oriented, but it does not explicitly contrast with sibling tools like get_trending_topics or get_latest_episodes.

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 alternatives. Sibling tools such as get_trending_topics, browse_section, and get_latest_episodes exist, but the description provides no conditions, exclusions, or routing hints. Usage must be inferred entirely from the content-list description.

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?

Annotations only supply readOnlyHint=true, so the description usefully adds that transcript lines are omitted by default and that include_transcript returns a large payload — a real behavioural warning. It also discloses the dual list/read mode that annotations do not cover. Missing only things like auth or rate-limit 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 English body is well front-loaded, but the Arabic restatement duplicates the same content for no functional gain and the trailing Args block re-states what the schema already encodes. Roughly a third of the text is redundant.

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 need not be detailed, yet the description still lists the returned sections (summary, chapters, guests, topics, ad breaks, name fixes, on-screen text). With both parameters explained and the routing to get_transcript given, nothing an agent needs to call it correctly is missing.

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

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

Schema description coverage is 0%, so the description carries the full burden and does it: video_id is 'omit to list analysed episodes' (mapping null default to list behaviour) and include_transcript is described as 'Also return every transcript/translation line (large; default false)', adding size and default context beyond the bare schema type.

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?

States a specific verb and resource ('Read the saved analysis of an episode') and enumerates the fields returned, plus the second mode (list all analysed episodes when no video_id). It explicitly names get_transcript as the sibling that does the text part, so the agent can distinguish behaviour without opening either schema.

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 routes the agent: transcript lines are excluded unless include_transcript is true, and 'use get_transcript for the text, or the download links.' It also states the condition that switches to list mode (omit video_id). Both when-to-use and the alternative are 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?

Annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description adds the specific fields returned, which is useful context. However, it doesn't disclose any additional behavioral traits like whether the video must be available in the user's region, whether it returns metadata for unpublished videos, or any rate limits. With annotations covering the safety profile, a 3 is appropriate.

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 and front-loaded with the core purpose. The bilingual repetition (English and Arabic) is somewhat redundant for an AI agent but not harmful. The Args section is clear and minimal. It earns a 4 because the bilingual content adds length without much additional value for an AI agent, but the structure is otherwise 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?

The tool has an output schema, so return values are already documented structurally. The description adds the key fields (title, description, duration, quality, categories, episode info, watch URL) which helps the agent know what to expect. With one simple parameter, readOnlyHint annotation, and output schema present, the description is nearly complete. The only gap is not specifying where the video_id comes from or any prerequisites, but this is minor for such 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 description coverage is 0%, so the description must compensate. It does: it explains that video_id is 'The numeric ID of the video' and provides an example (953659). This adds meaning beyond the bare schema type 'integer'. The description also lists what the returned details include, which helps the agent understand the parameter's role. However, it doesn't specify the ID's source (e.g., from search results or URLs), which would be slightly more helpful.

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: getting detailed information about a specific video on Al Jazeera 360, and lists the specific fields returned (title, description, duration, quality, categories, episode info, watch URL). This distinguishes it from siblings like get_series_details and get_latest_episodes, which target different resources.

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 context: use this when you need details about a specific video by its numeric ID. It doesn't explicitly state when not to use it or name alternatives, but the clear resource focus (video vs series vs episodes) provides adequate guidance. The bilingual text reinforces the intended use case.

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?

Annotations already declare readOnlyHint=true, so the safety profile is known. The description adds behavioral detail beyond annotations: it states that the tool 'Returns section IDs with their Arabic names', which informs the agent about the output format. It also implies 'all available' sections, indicating no filtering or pagination, which is useful context. No contradictions with 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?

The description is concise in each language, with two short sentences. It front-loads the purpose and immediately explains the return value and relationship to browse_section. The bilingual duplication adds length but is intentional for an Arabic platform; still, it slightly reduces conciseness for English-only agents. Otherwise, every sentence earns its place.

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

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

The tool is simple (no parameters) and has an output schema, so the return structure is defined externally. The description fully covers the purpose, the output semantics (section IDs and Arabic names), and the intended downstream usage (browse_section). Nothing an agent needs to call this tool correctly is missing, and the relationship to siblings 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?

The tool has zero parameters, and the schema already reflects that with an empty properties object (100% schema coverage). Per the rubric, a zero-parameter tool receives a baseline of 4 because there is nothing to explain beyond what the schema provides. The description correctly focuses on the output and usage rather than 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 action: 'List all available sections and channels on Al Jazeera 360.' It identifies the specific resource (sections and channels) and the platform, and explicitly ties its output to the sibling tool 'browse_section', making its purpose distinct from other listing tools. The bilingual text reinforces the meaning without ambiguity.

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 says the output is 'for use with browse_section', which clearly indicates when to use it (as a prerequisite to browsing a specific section). It does not explicitly state when not to use it or mention alternatives, but the context is strong enough that an agent can infer its role among the siblings. A minor omission is lack of explicit exclusions, hence a 4.

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 readOnlyHint=true already signaling a non-mutating operation, the description adds useful environment-specific behavior: it opens a player in interactive views and returns a watch link elsewhere. It does not fully explain output details or failure cases, but the output schema likely covers those, so the added context is meaningful without contradiction.

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 compact and front-loads the core purpose, then explains behavior, usage, and the argument. The bilingual repetition doubles length but is appropriate for an Arabic/English product; no unnecessary fluff is present.

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

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

For a single-parameter tool with an output schema, the description covers what the tool does, how it behaves in different environments, when to use it, and where the argument value comes from. Nothing an agent needs to invoke it correctly is missing.

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

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

Schema coverage is 0%, so the description must compensate, and it does: video_id is described as 'The numeric ID of the video' and its provenance is given. This adds real meaning beyond the bare integer type, though it remains somewhat terse and gives no format or range details.

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

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

The description uses a specific verb and resource ('Play a video from Al Jazeera 360') and clearly distinguishes environments: interactive MCP apps open the official player, elsewhere it returns the watch link. This makes the tool's purpose unmistakable and separates it from sibling tools like search_videos or get_video_details.

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

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

It explicitly states when to use the tool: 'Use when the user asks to watch or play something.' It also tells the agent where the video_id comes from ('from search_videos, browse_section, etc.'). It does not enumerate alternatives or exclusions, but for a playback tool the guidance is sufficiently 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?

Annotations already declare readOnlyHint=true, so the description doesn't need to cover safety. It adds that the tool runs checks via an 'interactive view' and shows results, and notes the report parameter is internal. This is useful but not rich; it doesn't detail the exact check steps or output format, though the output schema likely covers that.

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 front-loaded with the purpose and usage, but includes a full bilingual repetition (English and Arabic) that adds length without new information. Still, it's concise and well-structured, with the Args section clearly separated.

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 diagnostic tool with no required parameters and an output schema present, the description covers purpose, usage, and the only parameter. It doesn't discuss prerequisites or limitations, but given the tool's simplicity, 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?

With 0% schema description coverage, the description must compensate. It does: it explains the 'report' parameter is internal, filled by the interactive view, and instructs the agent to leave it empty. This adds meaning beyond the schema's bare title and default.

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

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

The description states a specific action ('Check whether this AI app can play Al Jazeera 360 videos inside the chat') and includes key details like DRM, official player embedding, and fullscreen. It clearly distinguishes from sibling tools like play_video by framing itself as a diagnostic check rather than a playback action.

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

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

It explicitly says 'Use when the user says a video does not play in the chat' and instructs to call it with no arguments, noting the interactive view runs checks. This provides clear contextual guidance without ambiguity, even if alternatives aren't 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?

readOnlyHint=true already establishes that this is a safe read, and the description adds genuinely useful behavior beyond that: results are grouped by episode, speech matches carry the exact second (exact_sec derived from word timings), and the index only covers episodes that were analysed or transcribed. It does not mention ranking, pagination, or empty-result behavior, which leaves a modest 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 core purpose, return shape, and coverage prerequisites are front-loaded in the first three sentences, and the per-argument block is easy to scan. The Arabic restatement of the opening sentence is duplicated content for most agents and adds length without adding routing 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 three params, an existing output schema, and a read-only annotation, the definition covers what is searched, which corpora are indexed, what the matches look like, and every argument. The only substantive omission is not distinguishing this tool from search_videos, which matters in a fourteen-tool sibling set.

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% and the description fully compensates: query is described as a name, topic, or phrase in Arabic or English; kind enumerates all ten accepted values with glosses (people = guests + mentions, transcript_en = English translation); limit's default of 40 is restated. This is exactly the information the empty schema lacks.

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?

States a specific verb and resource with scope: searching *inside* analysed episodes for appearances, topics, speech and on-screen content. This distinguishes it in substance from the sibling search_videos, but it never names or contrasts that sibling explicitly, so the boundary is implied rather than declared.

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 line 'Covers episodes saved with save_video_analysis or transcribed with listen_to_video / transcribe_audio' effectively tells the agent when this tool will return results, which is real contextual guidance. However, it offers no when-not condition and never routes the agent to an alternative such as search_videos, so the choice among siblings is left to inference.

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?

Annotations already declare readOnlyHint=true, lowering the bar for safety disclosure. The description adds useful behavioral context (platform scope, Arabic/English support, optional content-type filtering) but omits result ordering, pagination behavior, or failure modes. Consistent with the calibration example, annotations carry the safety profile and the description adds moderate value without contradiction.

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 purpose is front-loaded and the Examples and Args sections are well organized, but the entire English opening is duplicated verbatim in Arabic, roughly doubling length with no additional information for an agent-consuming definition. The bilingual content belongs in the annotation title, not repeated in full.

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 3-parameter tool with an output schema present, the description covers query semantics, language support, filter values, and result caps — enough for correct invocation. Gaps are minor: no pagination or ordering disclosure and no guidance on alternative discovery tools, leaving a slightly incomplete picture for an agent facing the sibling set.

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, and it largely does: the Args section gives content_type real meaning ('VOD' for single videos, 'SERIES' for series only, None for all) that the bare string-or-null schema lacks, and query examples clarify the search term semantics. Only max_results adds little beyond the schema's own default.

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 opening sentence states a specific verb and resource: 'Search for videos, documentaries, and programs on Al Jazeera 360.' The bilingual search capability and content-type filtering are clearly stated, and concrete examples ('فلسطين', 'غزة', 'الدحيح') make the scope unmistakable. No sibling tool is a search tool, so this is implicitly distinguished from browse_section, get_trending_content, and get_latest_episodes.

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?

Usage is implied through examples and the stated bilingual/filter capabilities, but the description never says when to use this tool versus alternatives such as browse_section or get_trending_content for discovery without a keyword. There is no when-not-to-use guidance or explicit alternative routing, so an agent must infer the selection rule.

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 only readOnlyHint=true provided, the description adds real context: the action renders UI interactively in the conversation and is meant for explicit display intent, which is consistent with a non-destructive read. It does not cover auth requirements, limits, or any state side effects, so it stops short of full disclosure.

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 English usage rule is front-loaded and the parameter block is tightly organized. The Arabic paragraph largely restates the English sentence, which is defensible for a bilingual tool but is still redundancy that slightly dilutes conciseness.

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 need no explanation. Given a single required param, six parameters total, and readOnlyHint already declared, the description covers purpose, trigger conditions, and per-view parameter usage completely enough to call the tool 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 description coverage is 0% and there are no enums in the schema, yet the Args block documents all six parameters and even enumerates the view values (home|section|latest|search|series|season|video|play). It maps each id/query param to the views that consume it and gives a concrete example for section_id ('AJA', 'AJD'), fully compensating for the schema gap.

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

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

The description states a specific verb and resource: opening an interactive Al Jazeera 360 view (rows, programme/episode/player pages) inside the conversation. It explicitly separates itself from the data-only siblings with 'For everything else, use the other tools, which return data only.' An agent can distinguish it without opening any schema.

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

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

It gives an explicit when-to-use trigger ('ONLY when the user explicitly asks to see/display/play here') with concrete Arabic and English phrasings. The alternative is named generically ('the other tools'), but it does not differentiate against plausibly overlapping siblings like play_video or watch_video, leaving some selection ambiguity.

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?

readOnlyHint=true already signals a safe read, but the description adds genuinely new behavior: frames sampled at ~15s intervals, 12 frames per returned image, and that findings can be persisted via save_video_analysis. It does not mention token/context cost or any cap on how many frames can be pulled overall.

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?

Front-loaded with the core purpose and output format, and the workflow tip and parameter notes are tight. The Arabic paragraph largely restates the English content, adding redundancy without new 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?

For a 4-param tool with no output schema and only a readOnlyHint annotation, the description covers purpose, frame semantics, parameter behavior and a follow-up workflow. Minor gaps remain around whether a long range can exceed the frame budget or how partial results are signaled.

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 carries the full load and does it well: video_id provenance (from search_videos, get_season_episodes), start/end minute semantics with defaults, and max_frames range 4-36 with default 24 and the 12-per-image batching rule.

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?

States a specific verb and resource ('Look at an Al Jazeera 360 episode') and immediately specifies the output ('timestamped frames ... as images'), which cleanly separates it from siblings like get_transcript, get_video_details and play_video.

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?

Gives concrete use cases (describe an episode, find who appears, build chapters/metadata) and a workflow hint ('for long episodes, look at the whole range first, then zoom into a range'), plus the follow-up tool save_video_analysis. It stops short of explicitly stating when to prefer get_transcript or play_video instead.

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