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

The description provides no behavioral details beyond the annotation's idempotentHint. It doesn't describe side effects, state changes, or required permissions, leaving the agent uninformed.

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 (4 words), which is efficient, but it sacrifices necessary detail. It is front-loaded but incomplete.

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 one parameter and an output schema, the description lacks completeness. It does not mention what the output represents or any contextual information about the optimization lifecycle.

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 tool description does not explain the 'model' parameter or its nested 'optimizationId'. The schema itself provides an example, but the description fails to compensate.

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 'Abort an optimization' clearly states the verb (abort) and resource (optimization), distinguishing it from siblings like 'delete_optimization', 'create_optimization', etc.

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 on when to use this tool versus alternatives. Does not mention prerequisites (e.g., optimization must be running) or differences from delete_optimization.

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 provide idempotentHint but don't cover the interactive browser launch or login requirement. The description adds critical behavioral context beyond annotations, though it could elaborate on success/failure outcomes.

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 purpose, and every sentence adds necessary information. No wasted 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?

Given the tool's simplicity and the presence of an output schema, the description covers purpose, side effect, and prerequisite. It lacks details on post-auth behavior but is still fairly 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?

Input schema coverage is 0%, and the description does not explain the parameter 'model' or its nested 'brokerage' field. It only generically mentions 'brokerage or data provider', adding no semantic value beyond the schema's 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 clearly states the tool authorizes an external connection with a live brokerage or data provider, and it distinguishes itself by mentioning the browser-opening behavior, which no sibling tool does.

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 provides clear context for use, including the prerequisite of being logged into QuantConnect on the browser. However, it does not explicitly state when not to use it or mention alternatives, though no direct alternatives exist among siblings.

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 lack readOnlyHint or destructiveHint, so the description must define behavior. It does not disclose that broadcasting a command may be destructive (e.g., running orders), nor mention authentication requirements or side effects. The tool's impact on live algorithms is unspecified.

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 and front-loaded, but it is under-informative for the tool's complexity. Conciseness is good, but it does not earn its place by adding value; it could be more detailed without becoming verbose.

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 having an output schema, the description omits critical context: what happens after broadcasting (e.g., success/failure indication), error states, rate limits, or the effect of excludeProjectId. For a tool affecting all live algorithms, this is insufficient.

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 explain parameters. It mentions none of the three main parameters (organizationId, excludeProjectId, command). The description does not help an agent understand what to provide or how fields like excludeProjectId or command work.

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 (broadcast), resource (live command), and scope (all live algorithms in an organization). It implicitly distinguishes from sibling create_live_command which sends a command to a single algorithm, but does not explicitly compare.

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 on when to use this tool versus alternatives like create_live_command. No preconditions or exclusions mentioned. The description is purely declarative without contextual usage advice.

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 states 'run a backtest' which may imply a mutation, but annotations declare readOnlyHint=true, creating a contradiction. The description does not clarify the actual side effects or scope of the initialization check, leaving 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 description is a single sentence, concise for the core purpose. However, it could be improved by clarifying the parameters and side effects without adding much length.

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 of the input (nested objects) and lack of parameter guidance in the description, the tool is incomplete for an agent. The description does not explain prerequisites or the structure of the required model parameter, despite an output schema existing.

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 0% description coverage, meaning no parameter info in the schema's top-level description. The tool description fails to mention the required 'model' parameter (with language and files), leaving the agent without guidance on what to provide.

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 action (run a backtest briefly), its purpose (initialize algorithm and get errors), and the result (errors if any). It distinguishes from siblings like check_syntax and create_backtest by focusing specifically on initialization errors from a short run.

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 when to use (to check initialization errors without a full backtest) but lacks explicit guidance on when not to use or how it differs from alternatives like check_syntax or create_backtest.

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 indicate readOnlyHint=true, so the read-only nature is known. The description adds no further behavioral details (e.g., return format, error reporting), missing an opportunity to add value.

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 concise (one sentence), but it is under-specified. It sacrifices completeness for brevity, earning a middle score.

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 having an output schema, the description omits key context: what happens on syntax errors, whether it returns errors or just a boolean, and how to interpret results. The tool is simple but still incomplete.

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% (top-level parameter has no description). The description fails to explain parameters like 'language' or 'files', which are critical for tool use.

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 syntax of code, which distinguishes it from siblings like compilation or execution tools. However, 'a code' is somewhat vague and could be more 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?

No guidance on when to use this tool versus alternatives (e.g., compiling or running code to check errors). The description does not mention exclusions or context.

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 annotation 'readOnlyHint: true' already indicates a read operation, and the description 'Show' aligns with that. However, the description adds no additional behavioral context beyond what the annotations provide, such as the fact that completions are returned or that language and sentence are required. With the annotation present, a score of 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 a single sentence with no unnecessary words. It is concise, but could be structured to include more detail without losing brevity.

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 of the nested input schema and the existence of an output schema (not shown), the description is too minimal. It does not explain the return format, behavior when no completions are found, or any constraints like response size limits. More context would help the agent 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?

The input schema has 0% description coverage at the top level, and the description does not explain the nested parameters (language, sentence, responseSizeLimit). The description simply says 'for a specific text input', which vaguely references the 'sentence' parameter but fails to mention the language or optional size limit. Since the description does not compensate for the low schema coverage, the score is low.

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 'Show the code completion for a specific text input' clearly indicates the tool's purpose. It specifies a verb ('Show') and a resource ('code completion'), and adds context ('for a specific text input') that hints at the input parameter. While it distinguishes from siblings like 'check_syntax' or 'update_code_to_pep8', it could be more precise about what 'code completion' entails.

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 its siblings, such as 'check_syntax' or 'create_compile'. There are no explicit when-to-use or when-not-to-use instructions, 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 indicate 'destructiveHint: false', which the description doesn't contradict (it describes a creation operation, not destruction). However, the description adds minimal behavioral context beyond annotations—it mentions getting a backtest ID as output, but doesn't cover aspects like rate limits, authentication needs, or what happens if the backtest fails.

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, efficient sentence that front-loads the key action and outcome. There's no wasted verbiage, making it easy to parse quickly.

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 there's an output schema (which likely covers the backtest ID), the description doesn't need to detail return values. However, for a creation tool with 0% schema coverage and no behavioral annotations beyond destructiveness, the description is too sparse—it doesn't explain prerequisites, error conditions, or how it relates to sibling tools, leaving gaps in understanding.

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%, meaning parameters are undocumented in the schema. The description provides no information about parameters, not even hinting at required fields like 'projectId' or 'compileId'. With 1 parameter (a nested object), the baseline is 4 for zero parameters, but here the description 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 clearly states the action ('create a new backtest request') and the outcome ('get the backtest Id'), which distinguishes it from sibling tools like 'list_backtests' or 'read_backtest'. However, it doesn't specify what a 'backtest' is in this context, which could help differentiate from similar tools like 'create_optimization'.

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 like 'create_optimization' or 'create_live_algorithm', nor are prerequisites mentioned (e.g., needing a compiled project). The description only states what it does, not when it's appropriate.

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 mentions 'asynchronously' but lacks details on asynchronous behavior, error handling, or required closure via read_compile. Annotations only provide destructiveHint=false, leaving behavioral 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?

Single sentence, no redundant words. Efficient but could include more context without becoming verbose.

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 one-parameter schema and existence of read_compile as a sibling, the description minimally explains creation but misses connecting to the asynchronous lifecycle.

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 schema describes projectId. The description adds no extra meaning beyond the schema, failing to compensate for low coverage.

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 'create' and resource 'compile job request' for a project, distinguishing it from siblings like create_backtest and create_optimization.

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 on when to use this tool vs alternatives, nor prerequisites like whether the project must exist.

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 provide idempotentHint=true and destructiveHint=false, indicating safe, repeatable operations. The description adds minimal context about adding a file but doesn't elaborate on permissions, file type restrictions, or error conditions. It doesn't contradict annotations, but offers little behavioral insight beyond them.

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, clear sentence with no wasted words. It's front-loaded and efficiently conveys the core action, making it easy to scan and understand quickly.

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's complexity (file creation with multiple parameters) and the presence of an output schema (which handles return values), the description is minimally adequate. However, it lacks details on usage context, parameter meanings, and behavioral nuances, leaving gaps for an AI agent to infer correct usage.

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 doesn't compensate by explaining parameters. It mentions 'a given project' (hinting at projectId) but ignores name, content, and codeSourceId. With no parameter details in the description and low schema coverage, the baseline score of 3 reflects adequate but incomplete parameter semantics.

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 'Add a file to a given project' clearly states the action (add/upload) and resource (file to project), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'update_file_contents' or 'upload_object', which might have 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?

The description provides no guidance on when to use this tool versus alternatives like 'update_file_contents' or 'upload_object'. It mentions the target (a given project) but offers no context about prerequisites, constraints, or when other tools might be more appropriate.

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 provides no behavioral details beyond the name. Annotations indicate non-destructive, but the description does not clarify that creating a live algorithm requires a complex request object with many fields, or that it initiates a live deployment.

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 short but fails to provide useful information. It does not earn its place as it adds no value beyond the tool name.

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 of the input schema (over 50 nested definitions) and the absence of parameter descriptions, the description is completely inadequate. It should at least mention key required subfields like projectId, compileId, nodeId, and brokerage.

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 adds no information about the single required 'model' parameter. It does not explain that this parameter is a complex object with many nested required fields, leaving the agent with no guidance.

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 'Create a live algorithm' is a tautology, restating the tool name without adding any specificity. It fails to differentiate from sibling tools like create_backtest or create_compile.

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 on when to use this tool versus alternatives. The description does not mention prerequisites or context, such as needing a project, compile, and node before creating a live algorithm.

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 provide only a title, no readOnlyHint or destructiveHint. The description does not disclose side effects, permission requirements, or the impact on the live algorithm. As a mutation tool, the description should warn about potential risks.

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 front-loaded but could include more specific information without becoming verbose.

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 nested input schema and siblings with similar purposes, the description is too minimal. It lacks context on prerequisites (e.g., algorithm must be live) and does not help distinguish from broadcast_live_command.

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 top-level parameter 'model' has no description in the schema (0% coverage), and the tool description does not elaborate on required fields (projectId, command). Although nested definitions provide descriptions, the tool description adds minimal value beyond 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 'Send a command to a live trading algorithm' clearly states the action (send) and the resource (command to a live algorithm). It distinguishes from sibling tools like broadcast_live_command which likely targets multiple algorithms, but lacks explicit differentiation.

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 on when to use this tool versus alternatives such as broadcast_live_command or stop_live_algorithm. No prerequisites or exclusions 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?

The description does not disclose behavioral traits beyond the annotation (destructiveHint=false). It does not mention idempotency, side effects, or rate limits. For a creation tool, more context is needed, such as whether it replaces an existing optimization or creates a new one.

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, which is concise, but it lacks structure and is under-specified 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?

Given the complexity of the input schema with many required nested fields and the existence of sibling tools, the description is insufficient. It does not provide context about what an optimization is, how to configure it, or what the output will be.

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 adds no meaning beyond the schema. The top-level parameter 'model' has no description (0% coverage), and the description does not explain the required nested fields or any constraints.

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 the verb 'create' and resource 'optimization', making the basic action clear. However, it does not distinguish from sibling tools like 'update_optimization' or 'delete_optimization', and the phrase 'specified parameters' is vague.

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. There is no mention of prerequisites, context, or exclusions.

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 indicate 'destructiveHint: false' and 'idempotentHint: false', which the description doesn't contradict—it describes a creation action without implying destruction. However, the description adds little beyond annotations: it doesn't clarify what 'default organization' means, whether creation requires authentication, or if there are rate limits. With annotations covering basic safety, this earns a baseline score for minimal added 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 a single, clear sentence with no wasted words—it directly states the tool's purpose and context. It's front-loaded and efficiently conveys the essential information without unnecessary elaboration, making it easy for an agent to parse quickly.

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's complexity (creation action with nested parameters) and the presence of an output schema (which reduces the need to describe return values), the description is minimally adequate. However, it lacks details on parameter usage, organizational defaults, or error conditions, leaving gaps that could hinder correct tool invocation despite the structured data support.

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 0% description coverage, but the description provides no parameter details beyond implying an organizational context. It doesn't explain the required 'model' parameter, its nested fields (name, language, organizationId), or their purposes. Since schema coverage is low, the description fails to compensate, resulting in a baseline score due to inadequate parameter clarification.

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 ('Create a new project') and specifies the context ('in your default organization'), which distinguishes it from other project-related tools like 'create_project_collaborator' or 'update_project'. However, it doesn't explicitly differentiate from 'create_file' or 'create_live_algorithm', which are also creation tools but for 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 provides minimal guidance by mentioning 'default organization', but offers no explicit advice on when to use this tool versus alternatives like 'update_project' or 'create_project_collaborator'. There's no mention of prerequisites, such as needing an existing organization or specific permissions, which are common in project creation contexts.

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 indicate destructiveHint=false and idempotentHint=true, which describe core behavioral traits. The description adds nothing beyond that, but does not contradict annotations. It does not disclose edge cases like duplicate collaborator handling, but the annotations carry the burden here.

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, focused sentence with no wasted words. It is front-loaded and easy to parse, effectively conveying the core action.

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 (one parameter but a nested object with four required fields) and the presence of an output schema, the description is minimally adequate. However, it lacks information on error cases, permissions, and behavior when adding an existing collaborator. For a CRUD tool with many siblings, more context would be beneficial.

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% because the tool description does not mention any parameters. The input schema includes a nested object with four required fields, each with its own description. However, the tool description fails to explain the structure or required fields, leaving the agent to rely entirely on 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 'Add a collaborator to a project' clearly states the verb (add), the resource (collaborator), and the scope (to a project). It distinguishes from sibling tools like delete_project_collaborator, update_project_collaborator, and read_project_collaborators, which handle other CRUD operations.

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 update_project_collaborator for modifying permissions or delete_project_collaborator for removal. It also lacks prerequisites, such as whether the caller needs specific permissions or if the project must exist.

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 provide idempotentHint=true, which is a behavioral trait. However, the description adds no additional behavioral context, such as what happens upon deletion (cascading effects, irreversibility) or confirmation. It merely says 'Delete', which is obvious from the name.

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, concise and to the point. No unnecessary words or 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 simple delete operation, the description covers the basic purpose. The schema and annotations fill in details. However, it does not mention the output or potential side effects, though these are less critical for delete tools.

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 details the required parameters (projectId and backtestId) with descriptions and examples. The tool description adds no extra meaning beyond the schema, so the baseline score of 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 'Delete a backtest from a project' clearly states the verb (Delete), the resource (backtest), and the context (from a project). It effectively distinguishes from sibling tools like delete_project or delete_file.

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 explicit guidance on when to use, when not to use, or alternatives. The tool name implies usage for deleting a backtest, but there is no elaboration on prerequisites or conditions.

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 annotation idempotentHint: true is the primary behavioral clue, but the description does not add any extra context beyond stating it deletes a file. No mention of irreversibility or authorization needs.

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, no redundancy. Efficiently communicates the core action.

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 of the tool (delete operation with multiple parameters) and lack of output schema details, the description is too minimal. It should mention consequences (irreversible) or constraints (e.g., file must exist in project).

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?

Although the input schema has descriptions for nested properties, the top-level model parameter lacks description (0% coverage). The tool description does not compensate by explaining the parameter structure.

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 'Delete a file in a project.' uses a specific verb ('Delete') and resource ('file in a project'), clearly distinguishing it from sibling tools like read_file or update_file_contents.

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 on when to use this tool versus alternatives (e.g., patch_file or update_file_contents). Lacks context on prerequisites or when deletion is appropriate.

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 provide idempotentHint: true, but the description does not elaborate on behavioral traits like error handling or side effects. For a destructive operation, details on what happens if the file doesn't exist or permissions are missing are absent.

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, clear sentence with no redundant words. It is front-loaded with the verb and resource, making it efficient, though it could be slightly expanded to include parameter 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?

For a delete tool with nested parameters and a sibling list tool, the description is incomplete. It lacks return value details (output schema exists but is not referenced), prerequisites, or error conditions, making it less helpful for an agent to use 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 full descriptions for the nested properties (organizationId, key), but the top-level 'model' parameter lacks a description. The tool description echoes the schema's concept without adding new information, so it meets the baseline for adequate schema coverage.

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 deletes an Object Store file, specifying the scope ('of a specific organization and key'). This distinguishes it from sibling delete tools like delete_file or delete_optimization.

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, nor does it mention prerequisites or idempotency. The agent is left to infer usage from context.

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 provide idempotentHint: true, indicating idempotent behavior, but the description adds no additional context. With annotations present, the description's lack of behavioral details is acceptable, but it does not go beyond what annotations already convey.

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 at three words, conveying the essential purpose with no wasted words. It is appropriately sized for a simple deletion tool.

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 delete operation with an output schema and idempotent annotation, the description is minimal but adequate. However, it lacks information about permanence, error handling, or authentication requirements, leaving 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?

The schema has 0% description coverage for the top-level parameter 'model', though the nested optimizationId has a description. The tool description does not explain how to specify the optimization ID, adding no value beyond the schema's implicit structure.

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 'Delete an optimization.' clearly states the action and resource, distinguishing it from sibling tools like update_optimization or delete_backtest. It is specific enough for an agent to understand the tool's core function.

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, such as aborting an optimization or updating it. There is no mention of prerequisites (e.g., optimization must exist) or when not to use it.

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 adds no behavioral context beyond the idempotentHint annotation. It does not mention whether the deletion is permanent, what associated resources are affected, or permission requirements.

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, clear sentence with no unnecessary words. It is perfectly 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?

Given the availability of an output schema and the minimal description, the tool lacks important context such as effect on associated data, required permissions, and how it relates to sibling tools.

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 already provides a clear description for the only parameter (projectId). The tool description adds no additional semantic value, resulting in a baseline score of 3.

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 'Delete a project.' clearly states the verb (delete) and resource (project). It is succinct and easily understood, but does not differentiate from other delete siblings (e.g., delete_backtest) or mention scope.

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, such as delete_project_collaborator or other delete operations. There is no mention of prerequisites or consequences.

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 adds no behavioral context beyond the idempotentHint annotation. It does not disclose permanence, permission requirements, or effects on the project.

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, front-loaded with purpose. Very concise, though slightly 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?

Despite having sibling tools and an output schema, the description lacks prerequisites, result details, or important behavioral notes. Incomplete for a mutation 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 description does not elaborate on parameters; schema provides decent descriptions for projectId and collaboratorId but top-level coverage is 0%. The description fails to compensate.

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 (Remove) and the resource (collaborator from a project). It distinguishes from siblings like create_project_collaborator and update_project_collaborator.

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 on when to use this tool vs alternatives such as update_project_collaborator or read_project_collaborators. No conditions or exclusions 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?

Annotations already declare readOnlyHint=true, indicating a safe read operation. The description adds minimal behavioral context beyond stating it shows suggestions, but does not contradict annotations. It could better specify the nature of suggestions or limitations.

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 with no extraneous words. It is appropriately sized for a simple tool, though it could be slightly more structured without losing 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?

Given the tool's moderate complexity and the existence of an output schema, the description is adequate but vague. It explains the tool's purpose but fails to cover what 'context and suggestions' entail, leaving some gaps in understanding.

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 does not mention any parameters, but the input schema provides detailed descriptions for all nested properties (language, error). With high schema coverage, the baseline is 3; the description adds no extra meaning beyond 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 clearly states the tool shows additional context and suggestions for error messages, which is distinct from sibling tools like check_syntax or complete_code. The verb 'Show' and the resource 'error messages' are specific and 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 no guidance on when to use this tool versus alternatives. It lacks explicit context for usage, exclusions, or mention of when not to use it, leaving the agent without comparative direction.

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 indicate readOnlyHint=true, so the safe read nature is covered. The description adds no further behavioral traits (e.g., speed, permissions, estimate accuracy).

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 is concise but lacks detail. Could be more informative without losing brevity.

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 of the input schema (nested object with many fields), the description is insufficient. It does not explain what parameters to provide or the nature of the estimate.

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 does not mention the complex 'model' parameter or its nested fields. Schema description coverage is 0% for the top-level parameter, and the description fails to compensate.

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 estimates execution time for an optimization, using a specific verb and resource. It distinguishes from sibling tools like create_optimization which actually runs optimizations.

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 on when to use this tool versus alternatives (e.g., create_optimization for actual execution). The description only explains functionality without context for decision-making.

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 merely states the action without disclosing behavioral traits beyond what the annotations provide. The idempotentHint=true annotation suggests idempotency, but the description does not confirm this or discuss side effects, permissions, or data loss. For a liquidation action, more transparency on impact is expected.

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 (5 words) with no wasted language. However, it is so brief that it sacrifices completeness. Conciseness alone doesn't warrant a perfect score.

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's apparent destructiveness and the presence of an output schema, the description is insufficient. It lacks details about return values, prerequisites, the difference from similar tools, and the exact effect on the live algorithm.

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 does not mention the lone parameter 'projectId' or provide any additional meaning beyond the input schema. Although the schema itself has a description for projectId, the tool description adds no value for parameter understanding.

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 ('Liquidate and stop') and the resource ('a live algorithm'). However, it does not distinguish this tool from the sibling 'stop_live_algorithm', which could have overlapping or different behavior. The distinction is unclear.

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 like 'stop_live_algorithm' or 'broadcast_live_command'. The description lacks context on prerequisites, typical scenarios, or exclusions.

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, indicating a safe read operation. The description adds no behavioral context beyond this, such as pagination, rate limits, or authentication needs. It doesn't contradict annotations, but provides minimal extra value given the annotation coverage.

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, clear sentence with no wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly without unnecessary elaboration.

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 annotations (readOnlyHint) and an output schema (which handles return values), the description is minimally adequate. However, it lacks context on usage, parameters, and behavioral details, making it incomplete for optimal agent understanding despite the structured support.

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 schema provides no parameter descriptions. The tool description mentions no parameters at all, failing to compensate for the coverage gap. However, there is only 1 parameter (a nested object with 'projectId' and 'includeStatistics'), and the baseline is 3 when schema coverage is low but the description doesn't add meaningful param 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 action ('List') and resource ('all the backtests for the project'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'read_backtest' (which likely reads a single backtest) or 'list_optimizations' (which lists a different resource type), missing explicit 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?

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid project ID), exclusions, or compare to similar tools like 'read_backtest' for single backtests or 'list_optimizations' for other listings, leaving usage context unclear.

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 a title, so the description carries the burden of behavioral disclosure. It implies a read-only operation by using 'List', but doesn't specify aspects like pagination, sorting, or rate limits. No contradictions exist with annotations, but additional context is needed for full 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 a single, clear sentence with no wasted words, making it easy to parse. It efficiently conveys the core purpose without unnecessary elaboration, fitting the tool's straightforward nature.

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 an output schema, the description doesn't need to detail return values. However, with 0% schema coverage and no annotations beyond a title, the description is too minimal—it lacks parameter guidance and behavioral context, making it incomplete for effective use despite the output schema.

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%, with one parameter 'model' that includes a 'status' field with an enum. The description mentions 'past and current' deployments, hinting at status filtering, but fails to explain the parameter's purpose or how to use the status options, leaving significant gaps in understanding.

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') and resource ('past and current live trading deployments'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'list_backtests' or 'list_optimizations' beyond the resource type, missing explicit 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?

No guidance is provided on when to use this tool versus alternatives such as 'read_live_algorithm' for detailed views or other list tools. The description lacks context on prerequisites or typical use cases, offering minimal usage direction.

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 indicate readOnlyHint=true, so the description's 'List' is consistent but adds no additional behavioral context (e.g., pagination, limits, performance impact). The bar is lowered due to annotations, but no extra value beyond stating the obvious.

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?

One-sentence description is efficient and front-loaded with the key action. Could benefit from a slightly more structured format (e.g., bullet points for key details) but remains 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?

With an output schema present, the description does not need to detail return values. However, it lacks context about the 'directory' scope, constraints on organizationId, and how listing behaves with nested folders. Given the number of sibling file-related tools, more context would improve selection accuracy.

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% (top-level parameter 'model' lacks description). The tool description does not explain parameters; it only mentions 'specific directory' which loosely maps to the 'path' parameter. The nested schema has descriptions, but the tool description adds no value beyond what the schema already provides.

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) and resource (Object Store files) with a specific scope (under a directory in an organization). This distinguishes it from sibling tools like read_object_properties or upload_object.

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 on when to use this tool versus alternatives like read_object_store_file_download_url or read_object_properties. No exclusions or context about directory listing depth or permissions.

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 indicates no destructive behavior. The description adds the project scope but no additional behavioral traits like pagination, sorting, or performance hints. It is adequate but minimal given the annotation.

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 with no unnecessary words. It is front-loaded and 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?

Given the simplicity of the tool (list by project ID) and the presence of an output schema, the description is mostly complete. It lacks only minimal behavioral details, but the overall context is sufficient for a straightforward list operation.

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 0% description coverage for the projectId parameter. The description mentions 'for a project' but does not elaborate on the parameter structure or constraints, failing to compensate for the schema's lack of clarity.

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 'List all the optimizations for a project.' clearly states the action (list) and resource (optimizations), and it distinguishes from sibling tools like create_optimization, update_optimization, delete_optimization, and read_optimization.

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 listing optimizations by project, but does not explicitly state when to use this tool over alternatives, nor does it provide exclusions or prerequisites.

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 indicate readOnlyHint=true, which the description aligns with by implying a read operation ('List'). The description adds minimal behavioral context beyond annotations—it specifies 'details of all projects' but doesn't cover pagination, sorting, or response format. With annotations handling safety, this earns a baseline score for slight added value.

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, clear sentence with no wasted words. It's front-loaded with the core action and resource, making it efficient and easy to parse for an AI agent.

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's simplicity (0 parameters, read-only per annotations, and an output schema exists), the description is reasonably complete. It states what the tool does, though it could benefit from slight elaboration on usage context. The output schema likely covers return values, reducing the need for more detail.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here, earning a high score as it avoids redundancy and the tool is simple.

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 ('List') and resource ('projects'), specifying it retrieves 'details of all projects'. However, it doesn't differentiate from sibling tools like 'read_project' (which likely fetches a single project) or 'list_backtests'/'list_optimizations' (which list other resource types), missing explicit 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 description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to prefer 'list_projects' over 'read_project' for individual details, or how it relates to other list tools like 'list_backtests', leaving the agent with no usage context.

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 provide idempotentHint=true, indicating safe retries, but no readOnlyHint or destructiveHint. The description adds context: it's a lock operation for editing, implying a state change that might restrict access. However, it doesn't disclose behavioral traits like side effects (e.g., blocking collaborators), auth needs, or rate limits. No contradiction with annotations exists, but the description carries some burden due to limited 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 a single, clear sentence that efficiently conveys the core purpose without unnecessary details. It's front-loaded with the main action and context, making it easy to parse. No wasted words or redundant 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 the tool's complexity (state-changing lock operation), annotations are minimal (only idempotentHint), schema coverage is 0%, and an output schema exists (not provided here). The description is too brief: it doesn't cover prerequisites, effects, error conditions, or return values. For a tool that likely involves permissions and collaboration dynamics, this is inadequate.

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%, with parameters 'projectId' and 'codeSourceId' undocumented in the schema. The description adds no parameter information beyond implying 'project' context. It fails to explain what 'projectId' or 'codeSourceId' mean or how they're used, leaving significant gaps in understanding the inputs.

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 ('Lock') and resource ('a project that has collaborators'), with a specific purpose ('so you can edit it'). It distinguishes from generic lock operations by specifying the collaborator context, though it doesn't explicitly differentiate from sibling tools like 'update_project' or 'create_project_collaborator' which might have overlapping contexts.

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 minimal guidance: it implies usage when a project has collaborators and needs editing. However, it lacks explicit when-to-use criteria, prerequisites (e.g., permissions), or alternatives (e.g., vs. 'update_project' or other project management tools). No exclusions or comparisons to sibling 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?

The description adds no behavioral details beyond what annotations already provide (readOnlyHint, openWorldHint). It does not contradict annotations but offers no additional 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 a single concise sentence that front-loads the action and resource, with no unnecessary 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?

For a simple zero-parameter tool with an output schema, the description is sufficient to inform the agent that it reads account status.

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?

There are no parameters, and schema coverage is 100%. The description does not need to add parameter meaning; baseline of 4 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 clearly states the verb 'Read' and the resource 'organization account status', making the tool's purpose unambiguous and distinct from siblings like read_backtest or read_project.

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 by the name and description; no explicit when-not or alternatives are provided, but the simplicity and uniqueness of the tool make it clear when to use it.

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 provide readOnlyHint=true, indicating a safe read operation. The description adds minimal behavioral context beyond this—it specifies 'results' but doesn't detail what those results include (e.g., performance metrics, logs) or any constraints (e.g., authentication needs, rate limits). Since annotations cover the safety aspect, the description gets a baseline score but lacks enrichment.

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 wasted words. It's front-loaded with the core action and resource, making it easy to parse. Every part of the sentence contributes to understanding the tool's purpose efficiently.

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's moderate complexity (reading specific backtest results), the description is minimal but functional. Annotations cover read-only safety, and an output schema exists (implied by context signals), so the description doesn't need to explain return values. However, it lacks details on result scope or error conditions, leaving gaps 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 input schema has 0% description coverage (no parameter descriptions in the schema itself), but the description provides no parameter information. However, the schema defines a nested object with 'projectId' and 'backtestId', which are self-explanatory to some degree. The description doesn't add meaning beyond the schema's structure, but since the schema is clear, it meets the baseline.

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 'Read the results of a backtest' clearly states the verb ('Read') and resource ('results of a backtest'), making the purpose evident. It distinguishes from siblings like 'list_backtests' (which lists multiple) and 'read_backtest_chart' (which reads specific chart data). However, it doesn't explicitly differentiate from all similar siblings (e.g., 'read_backtest_insights', 'read_backtest_orders'), so it's not a perfect 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a backtest ID), contrast with siblings like 'list_backtests' for discovery, or specify use cases (e.g., retrieving summary results vs. detailed data). Without any usage context, the agent must infer from tool names 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 indicate readOnlyHint=true, so the agent knows it's a safe read operation. The description adds minimal context beyond this, specifying it reads a 'chart' but not detailing behavioral traits like data format, permissions, or rate limits. It doesn't contradict annotations, as 'read' aligns with readOnlyHint.

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, efficient sentence with no wasted words. It's front-loaded and appropriately sized for the tool's purpose, though it could benefit from more detail. Every word earns its place by stating the core action.

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 annotations (readOnlyHint) and an output schema (implied by context signals), the description is minimally complete but lacks depth. It doesn't explain the chart's nature, return format, or error conditions, leaving gaps despite structured data support. For a tool with 1 parameter (though nested with 6 sub-parameters), more context is needed.

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 schema provides no parameter descriptions. The description adds no parameter information beyond implying a chart is read from a backtest. It doesn't explain what parameters like 'model', 'projectId', or 'name' mean, failing to compensate for the low coverage.

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 'Read a chart from a backtest' clearly states the action (read) and resource (chart from a backtest), but it's vague about what 'chart' entails (e.g., visual data, metrics) and doesn't differentiate from siblings like 'read_backtest' or 'read_backtest_insights'. It avoids tautology by not just restating the name.

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. It doesn't mention prerequisites (e.g., needing a backtest ID), exclusions, or compare to sibling tools like 'read_backtest' for general data or 'read_live_chart' for live algorithms. Usage is implied only by the name and 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 declare readOnlyHint=true, indicating a safe read operation. The description adds no additional behavioral context, such as pagination constraints or ordering, which are present in the schema but not inferred.

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