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

With no annotations provided, the description carries the full burden. It implies a read-only 'check' but does not disclose what constitutes a 'good opportunity', what output is returned, whether any side effects exist, or how the result is computed. This is minimal beyond the annotation-less state.

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 short—one sentence—which makes it front-loaded and easy to parse. However, it sacrifices substance for brevity; while it states the core purpose, it omits important contextual and usage details. It is not bloated, but it is under-specified.

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

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

For a tool with 4 parameters, a likely complex matching algorithm, and no output schema, this description is incomplete. It doesn't explain what the result looks like, how the check is performed, or how region/language affect the outcome. The agent is left without enough context to predict behavior or interpret results.

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 only 50%: steamUrl and youtubeChannelUrl have descriptions, but region and language do not. The tool description adds no parameter meaning whatsoever, failing to explain the role of region/language or how they influence the opportunity check. It does nothing to compensate for the undocumented 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 a specific action: checking whether a Steam game is a good fit for a YouTube channel. It uses a clear verb and identifies both resources (game, channel). However, it does not distinguish itself from sibling tools like check_small_youtuber_game_fit, which likely has 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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention any exclusions, prerequisites, or contextual cues that would help an agent choose this tool over the many similar sibling check 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?

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It says 'Evaluate' which implies a read-only analysis, but it does not explicitly state that the tool makes no modifications, what data it relies on, or what the returned result looks like. No limitations, prerequisites, or side effects are mentioned.

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

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

The description is a single sentence that is direct and front-loaded. It contains no filler or redundant information, and every word contributes to the core purpose. This is an model of 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?

With no output schema and no annotations, the description needs to explain the output and provide enough context for confident use. It does not describe what the evaluation result looks like, how to interpret scores, or when to prefer this over siblings. The tool may be simple, but the description leaves too many practical questions unanswered.

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 0% description coverage, so the description must compensate. It implies 'query' is the gaming niche to evaluate, but gives no format, example, or further detail. The 'period' parameter is not mentioned at all, and its meaning is left entirely to the schema enum. The description's mention of evaluation criteria adds some context but does not adequately explain either 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 a specific verb ('Evaluate') and resource ('a gaming niche'), and lists four concrete evaluation dimensions (demand, creator pressure, opportunity, small-channel fit). This makes the purpose understandable, but it does not explicitly distinguish this tool from closely named siblings like 'check_small_youtuber_game_fit' or 'check_game_for_youtube', so it misses the top score.

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

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

There is no guidance on when to use this tool versus the many overlapping alternatives. The description only defines what the tool does, not in which scenarios it should be preferred. With numerous sibling tools, this lack of contextual direction is a significant gap.

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, and the description only restates the core function. It fails to disclose what criteria define 'realistic', what output format is returned, or any data sources/safety implications.

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, direct sentence with no filler. It is optimally concise and front-loads the main 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?

Without an output schema, annotations, or parameter documentation, this one-sentence description is insufficient to understand the tool's behavior, return value, or how to interpret results. It is adequate only as a basic label.

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 0% description coverage, and the description does not explain any of the three parameters. It only loosely hints that 'game or gaming topic' corresponds to 'query' and 'smaller YouTube channel' maps to 'channelSize', leaving 'period' completely unexplained.

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 ('Check') with a clear resource ('game or gaming topic') and a specific context ('realistic for a smaller YouTube channel'), distinguishing it from siblings like check_game_for_youtube by emphasizing the 'smaller' channel focus.

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 provided on when to choose this tool over the many sibling tools (e.g., check_game_for_youtube, check_gaming_niche). The description does not mention alternatives, exclusions, or typical use cases.

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 for behavioral disclosure. It merely restates the title without explaining what 'worth covering' means, what data is analyzed, or the nature of the result. No side effects, prerequisites, or decision process are mentioned.

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

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

The description is a single sentence with no wasted words, earning a high conciseness score. However, its brevity sacrifices necessary details, though structure itself is clean and front-loaded with the main verb.

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

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

For a tool with two parameters, no annotations, and no output schema, this description is severely incomplete. It does not explain what inputs are expected, what the output looks like, or how the tool determines worthiness. Users would be left guessing how to invoke it correctly.

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

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

The input schema has two parameters (query, period) with no descriptions, and the tool description does not mention either parameter. 'query' is ambiguous (likely a game name but not stated), and 'period' is an enum but its effect on the check is unexplained. Schema description coverage is 0%, so the description needed to compensate but did not.

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

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

The description clearly states the tool checks whether a Steam update, patch, DLC, comeback, or event is worth covering on YouTube. This specific scope differentiates it from general-purpose tools like check_game_for_youtube, though it does not explicitly name alternatives.

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

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

The description implies usage when a user has a specific Steam update or event in mind and wants to assess its YouTube potential. However, it gives no explicit guidance on when not to use it or how it differs from sibling tools like find_youtube_gaming_opportunities.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does not explain what the tool actually returns (e.g., a boolean, list), how the check is performed, potential edge cases, or any side effects. This is a significant gap for a tool that performs a comparison-based check, leaving the agent uncertain about the tool's output and behavior.

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

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

The description is a single, concise sentence that is front-loaded with the main verb 'Check'. It contains no superfluous words or redundant information. However, it is perhaps too brief, lacking important behavioral details, but that is a completeness issue rather than a conciseness issue, so it earns a 4 for structure.

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 only one parameter, no output schema, and no annotations, making the description the primary source of context. The description explains the basic purpose but fails to convey what the tool actually returns or how collisions are detected. Without output schema or annotations, the description should be more complete about the tool's behavior and results, but it is insufficiently detailed.

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 fully describes the 'query' parameter with a description and example, so schema coverage is 100%. The description does not add any additional semantic meaning beyond what the schema already provides; it merely repeats the concept of a channel name or handle. The baseline of 3 is appropriate because the schema does the heavy lifting, and the tool description adds little value.

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 'Check' and the resource 'channel name or handle', and it distinguishes from sibling tools by focusing specifically on channel name/handle collisions rather than titles or niches. However, it does not clarify what 'returned YouTube channel results' means or the exact nature of a collision, so it is specific but not fully precise.

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

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

The description implies usage when you need to verify if a channel name/handle collides with existing YouTube results, but it does not explicitly say when to use this tool over alternatives like check_youtube_title. There is no mention of when not to use it or what distinguishes it from similar checks, so the guidance is only implied.

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 must disclose how saturation is measured, what data is used, and what the response includes. It only states 'check whether... crowded or has room' without operational detail, using metaphorical terms like 'shelf' and 'sharper angle' that are not defined.

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 short sentence with no filler, front-loading the verb. However, it is under-specified rather than concise—it sacrifices essential context for brevity, but it does not waste words.

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

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

No output schema and no annotations. The description gives no information about return format, scoring, or how to interpret 'shelf saturation' or 'sharper angle'. For a potentially nuanced competitive analysis tool, this is inadequate guidance.

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 the description does not mention or clarify either parameter. 'query' could mean a game name, YouTube search term, or something else; 'period' is unclear as to what timeframe it applies to. The description entirely fails 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 uses a specific verb ('check') and resource ('YouTube shelf saturation' for gaming topics). It clearly distinguishes from siblings like check_gaming_niche and check_steam_update_opportunity by focusing on crowdness of the topic shelf rather than niche viability or update timing.

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?

Implied usage is when evaluating a gaming topic for competitive saturation. No explicit 'when to use vs alternatives' or exclusions, and no reference to sibling tools. The context is clear but does not guide the agent toward or away from 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 provided, the description carries the full burden of behavioral disclosure. It states the comparison dimensions but does not disclose the output format (e.g., score, list, metrics), how the data is sourced, or any limitations. The agent cannot predict what a response will look like.

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, densely packed sentence with no redundancy. Every word contributes to explaining the tool's function and scope, making it concise and front-loaded.

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

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

Despite the simple parameter set, there is no output schema and no annotations, so the description must explain what the agent will receive. It fails to specify the result type, scoring mechanism, or how to interpret 'demand' and 'competition'. This is a significant gap for a tool that is meant to guide title decisions.

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 already covers both parameters fully (100% coverage), so the baseline is 3. The description adds value by clarifying that the query should be a 'gaming video title' and connecting it to the comparison aspects (demand, competition, overlap), which helps the agent understand the query's domain and intent beyond the schema's generic wording.

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 ('compare') and clearly identifies the resource ('gaming video title or keyword') and what it is compared against ('recent YouTube videos, demand, competition, and title overlap'). This distinguishes it from sibling tools like check_youtube_channel_name, which targets channel names rather than titles.

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 context is implied: it is for evaluating a gaming video title or keyword against demand/competition. However, there is no explicit guidance on when to use this tool versus alternatives like check_game_for_youtube or check_youtube_channel_name. No exclusions or alternative tools are mentioned.

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

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

With no annotations, the description carries the full burden. It discloses the API key requirement and that the feed is 'ranked' by PeepTrend, adding value. But it omits behavioral details like whether it is read-only, how region/language define 'market', or error behavior without a valid key. This is moderate transparency.

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

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

The entire description is one concise sentence that front-loads the main purpose. Every word earns its place; no filler 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?

Given three parameters, no output schema, and no annotations, the description is too thin. It does not explain what the feed contains, how the parameters alter results, or how it differs from sibling tools like get_opportunity_detail. This leaves a significant gap for an agent to correctly select and 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 must compensate. It only vaguely references 'market' without explaining region/language. It does not mention the 'mode' parameter or its enum values (qualified, steam-only, watchlist). This leaves all three parameters semantically unexplained.

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 'Return' and identifies a distinct resource: 'PeepTrend's ranked Steam and YouTube opportunity feed for a market.' This clearly differentiates it from sibling tools like check_gaming_niche or get_opportunity_detail, which focus on individual checks or 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?

The description implies usage for retrieving a market feed and states a prerequisite (PeepTrend API key). However, it does not explicitly say when to use this tool over alternatives, nor does it mention any exclusions. It provides clear context but lacks explicit guidance on 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 has the full burden of behavioral disclosure. It only mentions the subscription requirement, but does not state whether this is a read-only operation, whether it has side effects, or what the 'regenerate' parameter does. This is a significant gap for a tool that likely triggers content generation.

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 concise sentences, front-loaded with the core purpose and a key prerequisite. Every word earns its place; no fluff 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?

The tool has four parameters, no output schema, and no annotations, so the description must carry substantial context. It only provides a high-level purpose and a prerequisite, missing return value details, parameter explanations, and usage scenarios. This is inadequate for a tool of this 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%, and the description provides no explanation of the four parameters (slug, region, language, regenerate). It only implies 'slug' relates to an opportunity but gives no details on semantics or defaults. This fails to compensate 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 the tool's function: generating PeepTrend content ideas for an opportunity. The verb 'Generate' and resource 'content ideas' are specific, and the mention of PeepTrend and opportunity scope distinguishes it from sibling tools like check_* tools and find_youtube_gaming_opportunities.

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

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

The description gives clear context: use this tool when you have an opportunity and need content ideas. It also states a prerequisite (active PeepTrend subscription). However, it does not explicitly compare with alternatives or state exclusions, which keeps it slightly below a 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?

With no annotations provided, the description carries the full burden. It discloses that this is a report retrieval operation and lists the report contents, plus the API key requirement. However, it does not explicitly state read-only behavior, error scenarios, or rate limits, which would improve transparency.

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 concise sentences, front-loaded with the verb and object. It includes essential details without any extraneous words, making it easily skimmable.

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

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

The description covers the tool's main purpose and report contents, which is useful given the lack of an output schema. However, it lacks parameter semantics and deeper behavioral details (e.g., required permissions, response format), making it not fully complete for a tool with three parameters and no annotations.

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 the description provides no explanation of the 'slug', 'region', or 'language' parameters. The agent is left to infer that 'slug' identifies the opportunity and 'region'/'language' are filters, but with no guidance on formats or allowed values, this is a significant 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 clearly states the specific action ('Open a full opportunity report') and resource, with explicit contents (score breakdown, Steam/YouTube evidence, crowding estimate, creator brief). It distinguishes itself from sibling discovery tools like find_youtube_gaming_opportunities by focusing on retrieving details for a specific opportunity.

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 retrieving detailed reports on a specific opportunity, which is clear context for when to use it. It also notes the prerequisite of a PeepTrend API key. However, it does not explicitly mention alternatives or when not to use this tool.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the tool reports two connection states (anonymous or API key), but it does not describe the return format, side effects, or error behavior. For a simple status check, this is minimally adequate 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 a single, well-structured sentence that is front-loaded with the action ('Show') and immediately provides the key distinction. There is no redundant or filler content.

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

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

This is a very simple tool with no parameters and no output schema. The description covers the core function, but since there is no output schema, it could be more complete by specifying the return format (e.g., string or boolean). However, given the low complexity, it is nearly 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?

The tool takes no parameters, and the input schema is empty (100% coverage). Per the rubric, a zero-parameter tool receives a baseline of 4. The description appropriately adds no parameter details because there are none.

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 with a specific verb ('Show') and resource ('connection status'), and it distinguishes itself from sibling tools that all focus on YouTube gaming opportunities. The added detail about anonymous versus API key connection states makes the purpose unmistakable.

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 is the tool to check connection status, but it does not explicitly mention when to use it or alternatives. Since no other sibling tool covers connection status, the context is enough to infer usage, but explicit guidance is missing.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the subscription requirement but does not disclose side effects, whether the operation is idempotent, what 'clear' means for the note, or the response behavior. This is a significant gap for a mutation tool.

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

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

The description is two sentences with no wasted words. It front-loads the primary actions and provides the key prerequisite. 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?

Given the tool has three parameters, no annotations, and no output schema, the description is too sparse. It omits explanation of core parameters (gameId, note), what 'clear' means, and what the user should expect after the call. The description covers the action but not the operational 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%, so the description must compensate but largely fails. It implicitly maps the status enum to verbs, but does not explain 'gameId' or 'note' at all. This adds little value beyond the raw schema.

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

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

The description clearly states the tool's purpose with specific verbs (save, plan, dismiss, publish, clear) and identifies the resource (PeepTrend opportunity workflow status). It distinguishes from sibling tools that perform checks or read details, making it clear this is the mutation tool for workflow status.

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

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

The description implies usage by listing the possible status actions and notes the prerequisite of an active PeepTrend subscription. It is clear when to use this tool versus siblings, but it does not explicitly name alternatives or exclusion scenarios, so it lacks a perfect 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?

With no annotations provided, the description carries the full burden. It adds useful context like the subscription requirement and feedback categories, but it does not disclose the actual behavioral effect (e.g., that it sends data to PeepTrend, is a write operation, or whether it is reversible) or any response/return behavior.

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

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

The description is only two sentences long. It is front-loaded with the action and includes all necessary high-level information without any filler 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?

The tool is simple and the description covers purpose and prerequisite, but it lacks parameter-level guidance and does not explain the outcome of sending feedback (no output schema). It is adequate for a basic tool but has clear gaps in completeness.

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

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

Schema description coverage is 0%, so the description must compensate. It loosely maps to the 'type' parameter by listing the categories, but it never mentions 'gameId' or 'message', leaving two out of three parameters unexplained and failing to connect the feedback categories to the enum 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?

The description uses a specific verb 'Tell PeepTrend' and resource 'opportunity', and enumerates the feedback categories (useful, wrong, saturated, etc.), making its purpose unambiguous and distinct from sibling tools like check_gaming_niche or save_opportunity_workflow.

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 clearly implies a context (providing feedback on opportunities) and includes a prerequisite ('Requires an active PeepTrend subscription'), but it does not explicitly state when not to use the tool or mention alternatives among siblings.

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