artemis-mcp

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 does not disclose any behavioral aspects such as side effects, read-only nature, or permission requirements. The description focuses solely on output 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 brief and well-organized, using a short introductory sentence and bullet-like notes. It avoids unnecessary verbosity while conveying the core purpose and important usage tips.

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 complexity (7 parameters, no output schema), the description lacks essential context such as what the generated formula looks like, how parameters interact, or what the return value is. This leaves ambiguity for the agent.

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 description explains some parameters (date format, order, metric types) but leaves others like 'show_dates' and 'hide_weekends' unexplained. Coverage is partial; the description adds some value but does not fully clarify all seven 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 ('Generate') and the resource ('ART formula for Artemis Sheets'), and provides examples of use cases (prices, fees, revenue). It does not explicitly contrast with sibling tools, but the purpose is unambiguous.

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 practical notes (date format, order, metrics) but does not explicitly state when to prefer this tool over alternatives like get_artemis_data. The context is implied but not explicit.

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 are absent, so the description must carry transparency. It states it creates properly formatted formulas and shows example output strings (e.g., =ARTINFO(...)). It does not explicitly mention side effects, return type, or whether it is purely a string generator, but the examples imply the output format. This is adequate but not exhaustive.

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

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

The description is well-structured with a clear opening statement followed by bulleted usage instructions. It is not overly verbose, but the multiple examples and conditional sections add length. It is effectively organized and front-loaded with the core purpose.

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

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

For a simple formula generator with no output schema, the description covers its purpose and parameter usage thoroughly. It does not mention error handling or alternative tool selection, but those are less critical for this tool's scope. Overall, it provides sufficient context for correct invocation.

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

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

The input schema provides no descriptions for top_n, parameter1, or parameter2 (0% coverage). The description fully explains each parameter with usage scenarios, examples, and default values, completely 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 clearly states the tool generates ARTINFO formulas for Artemis Sheets, with specific verb 'generate' and resource 'ARTINFO formula'. It distinguishes from sibling tools by explicitly naming ARTINFO (versus ART) and providing examples.

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

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

Provides explicit conditional usage instructions for both market rankings (top_n) and asset information (parameter1/parameter2), with examples. However, it does not directly compare with sibling generate_art_formula or mention alternative tools, so it stops short of full 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?

The description says 'Get', implying a read-only operation, but does not disclose authentication requirements, rate limits, error behavior, or any side effects. With no annotations provided, the description carries the full burden and provides only minimal 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 purpose is front-loaded, but the description repeats the phrase 'for the given symbols and metrics' and includes the parameter list in the prose, making it somewhat redundant. It is not poorly structured, but it could be more concise.

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 omits crucial context such as the output format, error handling, authentication requirements, or any example calls. Since there is no output schema or annotations to fill these gaps, the tool definition feels incomplete for an agent to use reliably.

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 description repeats the parameter names without adding meaningful semantics: 'symbols' and 'metrics' are undefined, with no examples or allowed values. It does add important guidance that dates must use YYYY-MM-DD, but this only covers two of the four parameters and does not compensate for the otherwise tautological explanations.

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 ('Get Crypto data') and the resource ('from the Artemis API'), and names the key parameters (symbols, metrics, dates). It is distinguishable from siblings like 'get_artemis_supported_metrics_for_symbol' or 'validate_artemis_api_key', though it does not specify exactly what kind of data is returned.

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 versus the sibling tools. There is no mention of prerequisites such as validating the API key first or checking supported metrics, leaving the agent without direction on selection.

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 word 'Get' implies a read-only operation, but the description does not explicitly state side effects, authentication requirements, rate limits, or error behavior. Since no annotations are provided, the description carries the full burden, and it only partially addresses behavioral context.

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

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

The description is concise and directly to the point. It avoids unnecessary fluff and clearly communicates the core function and the key constraint on the symbol parameter in two short sentences.

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 mentions that the tool returns metrics with descriptions and sources, giving an agent a reasonable idea of the output. However, with no output schema, details about response structure, pagination, or possible empty results are not covered, though the tool's simplicity keeps this from being a major 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?

The schema only defines 'symbol' as a required string with no description. The tool description adds that it accepts only one symbol at a time, which is useful, but it does not clarify the expected format (e.g., ticker symbol, name) or provide examples, leaving some ambiguity.

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: to get the list of metrics supported by Artemis for a given symbol, including their descriptions and sources. It uses a specific verb ('get') and identifies the resource ('metrics'), making the intent unambiguous.

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 some usage guidance by explicitly noting that the symbol parameter accepts only one symbol at a time. However, it does not mention when to prefer this tool over sibling tools like get_artemis_data or how it relates to them, so guidance is partial.

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 description is extremely minimal and does not disclose what validation entails, what the output looks like, whether it has side effects, or any permissions required. No annotations exist to supplement this 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 description is a single, concise sentence. It is well-structured for its brevity, though it could benefit from a bit more detail.

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 does not mention how the API key is passed, what the success/failure output looks like, or any prerequisites. It is incomplete for an agent to use effectively without further information.

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 declares zero parameters, but the description implies an API key input without explaining how it is supplied (e.g., environment variable, hidden config). This ambiguity reduces clarity about the actual invocation.

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: to validate the Artemis API Key. It distinguishes itself from siblings by focusing on validation rather than data retrieval or formula generation.

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 or under what circumstances validation is needed. The description lacks context that would help an agent decide between this and other tools.

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