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

With no annotations, the description carries the transparency burden. It does disclose the return fields and supports example query patterns, but it does not mention error handling, exact-name matching behavior, data freshness, or limitations beyond 'tradeable items.' The read-only nature is only implied by 'Returns.'

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 opening sentence is dense and front-loaded, but the eight example bullets include repetitive variants (30/90/180-day changes) and could be trimmed significantly. While examples are helpful, the description is longer than necessary.

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 lookup tool with no output schema and no annotations, the description is fairly complete: it lists the output categories and provides a wide range of example queries. It lacks explicit output structure and error-condition details, but overall it gives adequate context for an agent to understand when and how to use 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?

The schema covers 100% of parameters with clear descriptions, so the baseline is 3. The description adds example queries, but it introduces ambiguity by showing 'Compare the price of a dragon scimitar and a rune scimitar' while itemName is a single string parameter, leaving multi-item handling unclear.

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 specific verb 'Returns' and details the resource: current price, price trends, category, image, and examine for tradeable Grand Exchange items. This clearly states what the tool does and distinguishes it from the sibling get_item_price_history, which focuses on historical price series.

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 examples provide clear usage contexts, such as single item queries, price comparisons, percentage changes over 30/90/180 days, and retrieving description/icon/id. However, it does not explicitly state when to prefer get_item_price_history or mention exclusions, relying on implied context rather than direct alternative 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?

With no annotations, the description must convey behavioral traits. It discloses that the tool is a read-only query returning daily prices over a 180-day window, but doesn't mention data freshness, error handling, or any access constraints.

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

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

The description is concise but includes several examples that reinforce usage. The redundant 'Usefull for...' sentence and minor typo prevent a 5, but the structure is clear 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?

The examples include comparing two items and asking for a specific future date (1 April 2025), which could mislead the agent into thinking the tool accepts multiple items or arbitrary date queries. The description doesn't clarify that only a single item is accepted or that data is limited to the previous 180 days relative to now.

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 documents both parameters (itemName and gameMode) with descriptions, so the description doesn't need to add parameter semantics. The examples illustrate query phrasing but don't add new information about the parameters themselves.

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 'Returns the prices each day of a given item for the previous 180 days', which is a specific verb, resource, and time scope. It clearly differentiates from sibling tools like get_item_details or player-focused 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?

The description says it's 'useful for seeing price trends' and includes query examples covering single and comparative requests. It doesn't explicitly name alternatives or exclusions, but the context of siblings makes the intended use 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?

With no annotations available, the description carries the full burden of behavioral disclosure. It honestly describes the core function (returning a count), but provides no additional context such as whether the count is live/cached, whether it covers all worlds, or any potential limitations. This is acceptable for a simple read-only tool, but leaves some ambiguity about 'currently online'.

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, front-loaded sentence that directly states the tool's purpose without any filler or repetition. Every word contributes to clarity, making it highly 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?

For a tool with no parameters and no output schema, the description is fully complete. It clearly specifies what is returned (the number of players) and the domain (RuneScape and OSRS). No additional context is necessary for an agent to understand and correctly invoke this 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?

The tool has zero parameters and the schema is empty, so there is no parameter information to elaborate. The baseline for zero-parameter tools is 4, and the description adds sufficient context by explaining what the output represents.

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 ('Returns') and resource ('number of players currently online in RuneScape and Old School RuneScape'). It effectively distinguishes itself from sibling tools like get_item_details or get_player_hiscore, which focus on different data types.

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 explicit guidance on when to use this tool versus alternatives. It only states what it does, without suggesting scenarios (e.g., 'use this to check live player counts') or exclusions. The usage is not even clearly implied beyond the basic function.

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

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

No annotations are provided, so the description bears the full burden of behavioral disclosure. It states what is returned but omits details like how game mode and type affect the result, whether the tool handles multiple players in a single call (as 'Multi comparison' suggests), and any potential errors or rate limits. The ambiguity around 'activity' and comparison behavior leaves significant gaps.

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

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

The description is concise, with a clear one-sentence summary followed by a list of relevant examples. The examples are useful and not overly verbose, though some could be trimmed. The structure is front-loaded and easy to parse, earning a high score for efficient use of space.

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

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

The tool has three parameters and no output schema or annotations, so the description must compensate. It leaves key questions unanswered: whether multiple players can be compared in one call, what constitutes an 'activity', whether output format is consistent across types, and how gameMode 'rs' differs from 'osrs' in practice. The examples hint at multi-player support but the schema only accepts a single playerName, creating confusion. This incomplete picture makes it hard for an agent to fully use 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?

With 100% schema description coverage, the schema already documents parameter meanings. The description adds some value through examples that illustrate playerName and gameMode usage, but it does not elaborate on parameter syntax or constraints beyond the schema. The added examples show type variations (ironman) but do not explain all type options; thus it meets the baseline without exceeding it.

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 returns a player's rank, level, and experience/score, with a specific verb ('returns') and resource (player hiscore). However, it does not explicitly differentiate from sibling tools like get_top_rankings, which also deals with hiscores, so it loses a point for missing sibling distinction.

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 examples provide implied usage scenarios (single lookups, comparisons, specific modes like ironman), but there is no explicit guidance on when to use this tool versus alternatives, no when-not-to-use conditions, and no mention of prerequisites such as requiring a valid game mode. The context is inferred from examples rather than stated.

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

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

With no annotations, the description carries the burden of disclosing behavior. It explains the return value and an important inclusion detail (FunOrb/version accounts), but it does not clarify whether the count is real-time, cached, cumulative, or restricted to active accounts, nor the output format.

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, front-loaded with the primary purpose, and the second sentence adds a valuable inclusion qualifier. Every word earns its place; there is no fluff.

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, no-output-schema tool. The description covers the core purpose and a key edge case. It is slightly incomplete in not addressing the distinction from get_player_count or the response type, but for such a low-complexity tool, it is mostly 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 tool has zero parameters, so parameter documentation is not needed. The baseline of 4 applies because no parameter semantics are required and the description avoids redundant parameter 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 clearly states the verb 'Returns' and the resource: the current amount of accounts created that can access RuneScape, including FunOrb or a particular version. This is specific and understandable, though it does not explicitly differentiate from sibling tools like get_player_count.

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 about when to use this tool instead of alternatives such as get_player_count. The description only states what the tool returns, leaving the usage context entirely 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?

No annotations are provided, so the description carries the burden. It discloses the maximum result count (50) and that it targets a single skill/activity per call, but it doesn't specify sort order, response format, or behavior for ties/multi-skill requests, leaving some ambiguity.

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 sentence is concise and front-loaded, followed by a compact list of illustrative examples. No wasted words; every sentence adds value.

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

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

For a simple tool with full schema coverage, the description provides helpful examples of valid skill/activity names and demonstrates the size limit. It doesn't specify return structure or ordering, but the tool's simplicity and schema mitigate this gap.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds no parameter-specific meaning beyond the schema, though examples demonstrate usage context for 'name' and 'size'.

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 ('Returns up to the top 50 players') and the resource ('in a given skill or activity'). It distinguishes from sibling tools (items, prices, player stats) and examples reinforce the purpose.

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

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

Examples illustrate when to use the tool, such as single rankings, multi comparisons, and max-size queries. It lacks explicit when-not-to-use or alternative tool names, but the sibling list makes the context obvious.

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