Stonkwatch

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 but fails to indicate if the operation is read-only, idempotent, or requires authentication. It mentions 'community' as a data source but omits return format, rate limits, or error handling 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 single-sentence description is efficiently front-loaded with the action verb 'Get' and contains zero redundant or filler words. Every word earns its place in defining the tool's scope and function.

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 low complexity (two simple parameters) and complete schema coverage, the description adequately covers the core function but remains incomplete regarding output format and behavioral characteristics. Without an output schema, the lack of return value description creates a minor 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 description coverage is 100%, with both ticker and timeframe well-documented in the input schema itself. The description references 'ASX stock ticker' which aligns with the schema but does not add syntax details, validation rules, or examples beyond the structured field 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 retrieves community sentiment analysis for a specific resource (ASX stock ticker), providing both the action and domain scope. However, it does not explicitly differentiate this tool from siblings like get_stock_price or list_trending in the text itself.

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 offers no guidance on when to use this tool versus alternatives, nor does it mention prerequisites such as valid ASX ticker formats or API limitations. Users must infer applicability solely from the tool name.

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 specifies temporal context ('current') and indicates the tool returns both price and change data, which is helpful given the lack of output schema. However, it lacks details on data freshness, rate limits, or error handling for invalid symbols.

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 with nine words. Every word earns its place—no fluff, no redundancy, immediate clarity on function and scope.

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 operation with 100% schema coverage, the description is nearly complete. It would benefit from clarifying whether 'current' means real-time or delayed data, and the timeframe for 'change' (e.g., daily), but suffices for tool selection.

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 100% description coverage for the single 'symbol' parameter. The description does not add parameter-specific semantics, but none are needed given the schema's clarity with examples (BHP, CBA, WDS). Baseline 3 is appropriate.

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 clearly identifies the resource ('current price and change') and scope ('ASX-listed stock'). The ASX qualifier effectively distinguishes this from sibling tools like get_sentiment (sentiment analysis) and list_trending (trending stocks).

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 ASX scope implies geographic/ exchange limitations, but there are no explicit when-to-use guidelines or comparisons to alternatives (e.g., when to use get_sentiment vs. this tool). Usage is implied but not 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 provided, the description carries the full burden. It discloses the ranking methodology (discussion activity) and geographic scope (ASX), but omits safety profile (read-only status), rate limits, cache duration, or what constitutes 'currently' (real-time vs delayed).

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

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

Single sentence with zero waste. Every element earns its place: 'List' (action), 'currently trending' (temporal relevance), 'ASX stocks' (resource), 'by discussion activity' (differentiator). Front-loaded and appropriately sized for the tool's complexity.

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 list operation with one optional parameter and no nested structures, the description adequately covers the tool's purpose and differentiation. Given the lack of output schema, it appropriately focuses on the filtering/ranking logic rather than return values.

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 for the single 'limit' parameter, the baseline score applies. The description does not mention the parameter, but the schema fully documents it ('Number of results (default 10, max 25)'), so no additional semantic clarification is needed from the 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 provides a specific verb ('List'), clear resource ('ASX stocks'), and precise scope ('by discussion activity'). It effectively distinguishes this tool from siblings get_stock_price (price data) and get_sentiment (sentiment analysis) by specifying discussion volume as the ranking metric.

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?

While it doesn't explicitly name sibling alternatives, the phrase 'by discussion activity' provides clear contextual guidance on when to use this tool (for social buzz/forum activity trends) versus price-based or sentiment-based tools. However, it lacks explicit 'when-not-to-use' guidance.

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