QuantConnect MCP Server

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools have distinct purposes with clear resource-action pairs (e.g., create_backtest vs. read_backtest vs. delete_backtest). However, some overlap exists in object store operations (read_object_properties, read_object_store_file_download_url, read_object_store_file_job_id) and live algorithm monitoring tools (read_live_insights, read_live_orders, read_live_portfolio) that could cause minor confusion about which to use for specific queries.
Naming Consistency5/5
Tool names follow a highly consistent verb_noun pattern throughout (e.g., create_backtest, list_backtests, read_backtest, delete_backtest). All tools use snake_case with clear action verbs (create, read, update, delete, list, etc.) and specific nouns, making them predictable and easy to parse.
Tool Count2/5
With 63 tools, the count is excessive for typical MCP server purposes, making it overwhelming for agents to navigate. While the domain (QuantConnect platform) is broad, many tools could be consolidated (e.g., multiple object store read operations) or omitted to reduce cognitive load and improve usability.
Completeness5/5
The tool set provides comprehensive coverage for the QuantConnect domain, including full CRUD operations for projects, backtests, optimizations, files, and live algorithms. It also includes specialized tools for syntax checking, code completion, error enhancement, and platform-specific features like object store management and node selection, leaving no obvious gaps for core workflows.
Average 3.1/5 across 63 of 63 tools scored. Lowest: 1.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide destructiveHint=false, but the description adds no behavioral context beyond the basic 'create' action. For a tool that likely deploys trading algorithms with real financial implications, the description should mention authentication requirements, rate limits, what 'live' means operationally, or any side effects. With minimal annotations, the description carries most of the burden and fails to provide necessary behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - just three words. While technically efficient, this represents under-specification rather than optimal conciseness. For such a complex tool with significant financial implications, this brevity is inadequate. However, it is front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's high complexity (financial algorithm deployment), rich input schema with 0% description coverage, no output schema information provided in context signals, and minimal annotations, the description is completely inadequate. It fails to explain what the tool actually does, what inputs are required, what the output represents, or any operational considerations for live trading algorithms.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the complex CreateLiveAlgorithmRequest structure (with 5 required properties and extensive nested brokerage/data provider configurations) is completely undocumented in the schema. The description provides zero parameter information - it doesn't mention any of the required inputs like projectId, compileId, nodeId, or brokerage settings. This leaves the agent with no semantic understanding of what parameters are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
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 that restates the tool name without adding specificity. It mentions the verb 'create' and resource 'live algorithm' but provides no details about what a live algorithm entails, what it does, or how it differs from other creation tools like create_backtest or create_optimization.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (like needing a compiled project), when this would be appropriate versus creating a backtest, or any contextual constraints. The agent receives zero usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description doesn't contradict the annotations (destructiveHint: false indicates it's non-destructive, which aligns with 'create' operations typically being additive). However, it adds no behavioral context beyond what annotations provide. It doesn't mention whether this starts an asynchronous job, has cost implications (despite 'estimatedCost' in schema), requires specific permissions, or has rate limits. With annotations covering only destructiveness, the description carries significant burden but provides minimal behavioral insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is maximally concise - a single sentence with zero wasted words. It's front-loaded with the core action and doesn't contain any unnecessary elaboration. While this conciseness comes at the expense of completeness, as a standalone text it's efficiently structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by the rich input schema (11+ nested properties) and the existence of an output schema, the description is severely inadequate. It doesn't explain what domain this operates in (algorithmic trading optimization based on sibling tools), what an optimization job entails, or how it relates to other tools like 'estimate_optimization_time' or 'list_optimizations'. The description fails to provide the contextual framing needed to understand when and how to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage (the schema has detailed parameter descriptions but they're in the schema itself, not counted as 'description coverage' for this evaluation), the description 'with the specified parameters' adds almost no semantic value. It doesn't explain what the single 'model' parameter contains, what optimization means in this domain, or how parameters relate to the optimization process. The description fails to compensate for the schema's technical documentation with accessible explanations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Create an optimization with the specified parameters' is a tautology that essentially restates the tool name 'create_optimization' without adding meaningful specificity. It doesn't explain what an 'optimization' is in this context (e.g., algorithmic trading optimization, parameter tuning) or what resource it creates beyond the generic term. While the title annotation 'Create optimization' provides minimal context, the description itself fails to clarify the purpose beyond the obvious.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a compiled project first), when optimization is appropriate, or how it differs from related tools like 'create_backtest' or 'update_optimization' in the sibling list. The agent receives no contextual cues about appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not add behavioral details beyond the annotations, which indicate idempotentHint=true. It fails to disclose critical traits like whether deletion is permanent, requires specific permissions, or has side effects. However, it does not contradict the annotations, so it meets the lower bar set by their presence but adds minimal value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence, 'Delete an optimization.' It is front-loaded and wastes no words, making it easy to parse quickly, though this brevity contributes to its lack of helpful detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a deletion operation with no annotations on safety or behavior, and with schema coverage at 0% and an output schema present, the description is incomplete. It does not address key aspects like what deletion entails, error conditions, or return values, leaving significant gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the schema lacks descriptions for parameters. The description does not compensate by explaining the 'optimizationId' parameter's semantics, such as format, source, or validation rules. With one parameter and no schema guidance, this leaves the agent guessing about proper usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Delete an optimization' is a tautology that merely restates the tool name 'delete_optimization' without adding specificity. It does not clarify what an 'optimization' is in this context or distinguish it from similar tools like 'delete_backtest' or 'delete_object' among the siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 does not mention prerequisites, such as whether the optimization must be in a specific state, or exclusions, such as not using it for active optimizations. This leaves the agent without context for proper tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true, indicating this is a safe read operation. The description doesn't contradict this but adds minimal behavioral context beyond annotations—it doesn't disclose rate limits, authentication needs, or what data is returned. Since annotations cover the safety profile, the bar is lower, but the description could still add more operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single three-word sentence—with zero wasted words. It's front-loaded and efficiently states the core action, though this brevity comes at the cost of completeness. No structural issues are present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one parameter with 0% schema coverage, an output schema exists (which helps), but the description is inadequate. It doesn't explain what an 'optimization' is in this context, how to use the tool, or what to expect in return. For a read operation with a required ID parameter, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 doesn't mention parameters at all, failing to compensate for the schema gap. It doesn't explain what 'optimizationId' represents, its format, or where to obtain it, leaving the agent with minimal guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Read an optimization' is a tautology that restates the tool name without adding meaningful context. It doesn't specify what 'optimization' refers to in this domain or what aspects are being read. While it includes a verb ('Read') and resource ('optimization'), it lacks the specificity needed to distinguish it from sibling tools like 'list_optimizations' or 'update_optimization'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 an optimization ID), differentiate from 'list_optimizations' (which likely lists multiple optimizations), or specify use cases. The agent must infer usage solely from the tool name and schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description adds no behavioral context beyond what annotations provide - no information about pagination behavior (implied by start/end parameters), rate limits, authentication requirements, or what format the insights are returned in. With annotations covering the safety profile, this meets the minimum baseline.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence with no wasted words. However, this conciseness comes at the cost of being under-specified. While structurally simple, it lacks the necessary detail for a tool with complex parameter requirements.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this tool has an output schema (which handles return values) and annotations covering read-only safety, the description should focus on usage context and parameter guidance. However, it fails to explain the paginated nature of insights retrieval, the relationship between parameters, or when to use this versus other backtest reading tools. For a tool with 4 nested parameters and sibling alternatives, this is insufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% (the single parameter 'model' has no description in the schema), and the tool description provides absolutely no information about parameters. The description doesn't mention that insights are fetched using a range (start/end), require project and backtest IDs, or have a 100-item limit. This leaves all parameter semantics undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Read out the insights of a backtest' clearly states the verb ('read out') and resource ('insights of a backtest'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'read_backtest' or 'read_live_insights', leaving ambiguity about what specifically distinguishes this tool from other read operations in the system.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. There are multiple sibling tools for reading different aspects of backtests (e.g., 'read_backtest', 'read_backtest_chart', 'read_backtest_orders'), but the description doesn't explain when this specific insights-reading tool is appropriate versus those other options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 adds useful context about the 5-minute update cadence, which helps understand data freshness. However, it doesn't mention authentication requirements, rate limits, error conditions, or what happens when the algorithm isn't live - leaving significant 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately brief with two sentences. The first sentence states the core purpose, and the second adds important behavioral context about update frequency. There's no wasted language, though it could be more front-loaded with critical information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 helps), but schema description coverage is 0% and annotations are minimal, the description is insufficient. It doesn't explain what parameters are needed, what the tool returns, or important constraints like the 250-line limit mentioned in the schema. For a tool with 5 undocumented parameters, this is inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the parameters are documented in the schema. The description provides no information about any parameters - it doesn't mention projectId, algorithmId, startLine, endLine, or format. This leaves all 5 parameters completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'logs of a live algorithm', making the purpose understandable. However, it doesn't distinguish this tool from potential sibling tools like 'read_backtest' or 'read_compile' that also read logs or data, so it doesn't fully differentiate from alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 mentions 'snapshot updates about every 5 minutes' which gives some context about data freshness, but doesn't specify when to choose this over other read_* tools or what prerequisites might be needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations include idempotentHint=true, indicating safe retries, which the description doesn't mention. The description adds no behavioral traits beyond this, such as effects on ongoing processes or error conditions. It doesn't contradict annotations but provides minimal 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence, 'Abort an optimization.', which is front-loaded and wastes no words. It's appropriately sized for a simple action, though this brevity contributes to gaps in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 0% schema coverage, no output schema details provided, and annotations only covering idempotency, the description is incomplete. It doesn't explain what aborting entails (e.g., stopping a process vs. deletion), potential side effects, or return values, leaving significant gaps for agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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, failing to compensate for this gap. With 1 required parameter (optimizationId), the description should clarify its purpose and format, but it adds no semantic information beyond what's inferred from the tool name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Abort an optimization' clearly states the action (abort) and target (optimization), but it's vague about what 'optimization' entails and doesn't differentiate from sibling tools like 'delete_optimization' or 'stop_live_algorithm'. It's functional but lacks specificity about the resource being affected.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'delete_optimization' or 'stop_live_algorithm', nor does it mention prerequisites (e.g., an optimization must be running). The description is standalone with no context for selection among similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true, indicating this is a safe read operation. The description adds minimal behavioral context beyond this - it implies analysis without modification but doesn't describe what the check entails (e.g., whether it returns errors, warnings, success status). No contradiction with annotations exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just 6 words with no wasted language. It's front-loaded with the core purpose. However, this conciseness comes at the cost of completeness rather than being optimally informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 0% schema description coverage, no output schema details provided in context, and annotations only covering read-only status, the description is inadequate. It doesn't explain what the tool returns, how to interpret results, or provide necessary parameter context. The existence of an output schema doesn't compensate for the description's minimalism.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for the single parameter 'model', the description provides no parameter information. It doesn't explain that 'model' requires language specification and file content, nor does it clarify the structure expected. The description fails to compensate for the schema's lack of parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check the syntax of a code' states the basic purpose (verb+resource) but is vague about scope and lacks specificity. It doesn't distinguish this tool from potential syntax-checking siblings (though none are explicitly listed among siblings) and uses generic terms like 'a code' rather than specifying it analyzes programming language syntax.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. The description doesn't mention prerequisites, appropriate contexts, or exclusions. While there are no obvious syntax-checking siblings, the tool exists among many code-related tools (e.g., complete_code, enhance_error_message) without differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only provide a title, so the description carries full burden for behavioral disclosure. While 'Send a command' implies a write operation, it doesn't specify required permissions, potential side effects (e.g., executing trades), rate limits, or what constitutes a valid 'live trading algorithm'. No output behavior is described despite having an output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized and front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that sends commands to live trading algorithms (potentially high-impact), the description is insufficient. With 0% schema coverage, no behavioral context, and no usage guidelines, it leaves critical gaps despite having an output schema. The description doesn't address what makes a command valid or the implications of execution.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but provides no parameter information. It doesn't explain what 'model' contains, the required 'projectId' and 'command' fields, or the command structure shown in examples. The single-sentence description adds no meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Send a command') and target ('to a live trading algorithm'), providing specific verb+resource. However, it doesn't differentiate from sibling tools like 'broadcast_live_command' or 'liquidate_live_algorithm', which appear related to live trading operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives like 'broadcast_live_command' or other live algorithm management tools. The description lacks context about prerequisites, appropriate scenarios, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true, indicating this is a safe read operation. The description adds no behavioral details beyond this, such as rate limits, authentication needs, or what happens if parameters are invalid. Since annotations cover the safety aspect, the bar is lower, but the description could have added useful context like pagination behavior (implied by start/end parameters) or data format. No contradiction with annotations exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, straightforward sentence with no wasted words, making it easy to parse. It's front-loaded with the core action. However, it's arguably too concise, as it omits necessary details about parameters and usage, which reduces its overall helpfulness despite the efficient structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 doesn't need to cover safety or return values. However, it's a read operation with 4 nested parameters (start, end, projectId, backtestId) that are undocumented in the description, and it lacks usage context among siblings. This makes it minimally adequate but incomplete for effective tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% (parameters are nested under 'model' without descriptions in the top-level schema), so the description must compensate. However, it mentions no parameters at all, failing to explain what 'model' contains or the meaning of start, end, projectId, and backtestId. This leaves critical input semantics undocumented, making it harder for an agent to invoke the tool correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Read out the orders of a backtest' clearly states the verb ('read out') and resource ('orders of a backtest'), making the purpose understandable. However, it doesn't distinguish this tool from sibling tools like 'read_backtest', 'read_backtest_chart', or 'read_backtest_insights', which all involve reading backtest data but different aspects. The description is vague about what 'orders' specifically refer to in this context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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), compare it to similar tools like 'read_live_orders' or 'read_backtest', or specify use cases. Without this context, an agent might struggle to select this tool appropriately among the many read-related siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only provide a title ('Read live chart'), which doesn't convey behavioral traits like read-only status, destructive potential, or authentication needs. The description adds minimal value beyond this, stating it 'Reads' a chart but not disclosing rate limits, error conditions, or what 'live' entails (e.g., real-time data vs. historical). With annotations lacking critical hints, the description fails to compensate adequately for a tool that likely interacts with live systems.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words: 'Read a chart from a live algorithm.' It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place by conveying essential information without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (interacting with live algorithms and charts) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations covering safety or behavior and a schema lacking parameter descriptions, the description doesn't provide enough context for safe and effective use. It meets a bare minimum by stating the action but leaves critical gaps in understanding how and when to apply it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, meaning parameter descriptions are absent in the schema itself. The tool description provides no additional parameter information beyond the tool name, which implies parameters like 'model' but doesn't explain their semantics or relationships. Since the schema lacks descriptions, the description should compensate but doesn't, resulting in a baseline score due to the schema's failure to document parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Read a chart from a live algorithm' clearly states the verb ('Read') and resource ('chart from a live algorithm'), making the basic purpose understandable. However, it doesn't distinguish this tool from sibling tools like 'read_backtest_chart' or 'read_live_algorithm', leaving ambiguity about when to use this specific chart-reading tool versus others. The purpose is clear but lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 sibling tools like 'read_backtest_chart' for non-live charts or 'read_live_algorithm' for general live algorithm data, nor does it specify prerequisites such as requiring a live algorithm to be running. Without any usage context or exclusions, the agent must infer when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true, indicating this is a safe read operation. The description doesn't contradict this but adds minimal behavioral context beyond the annotations. It mentions 'search for content' which aligns with read-only behavior but doesn't elaborate on search limitations, result formats, or any rate limits that might be relevant.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence 'Search for content in QuantConnect.' It's front-loaded and wastes no words, though this brevity comes at the cost of completeness. Every word serves a purpose in stating the basic function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 1 parameter with 0% schema coverage, no output schema details provided in context, and annotations only covering read-only status, the description is inadequate. It doesn't explain what 'content' means, how results are returned, or provide any parameter guidance. For a search tool with complex nested parameters, this leaves too many gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 the single parameter 'model' or its nested structure (SearchRequest with language and criteria). With no parameter details in the description to compensate for the schema gap, this leaves the agent guessing about required inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Search for content in QuantConnect' states a clear verb ('Search') and target ('content in QuantConnect'), but it's vague about what type of content and doesn't differentiate from siblings like 'read_file' or 'list_projects'. It provides basic purpose but lacks specificity about the search scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. With siblings like 'read_file' for specific content access or 'list_projects' for listing resources, there's no indication of when search is appropriate versus direct retrieval methods. No usage context or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only provide a title, so the description carries the full burden of behavioral disclosure. It states the action ('broadcast') but lacks details on permissions needed, whether it's destructive (e.g., could affect trading), rate limits, or response behavior. This is inadequate for a tool that likely impacts live trading operations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words, front-loading the key action and target. It's appropriately sized for the tool's complexity, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (broadcasting commands to live algorithms, likely with financial implications), the description is insufficient. Annotations are minimal, schema coverage is 0%, and while an output schema exists, the description doesn't address critical aspects like safety, permissions, or behavioral traits, leaving significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'organization' but doesn't explain parameters beyond what the schema provides. Schema description coverage is 0%, so parameters like 'command' and 'excludeProjectId' are undocumented in both schema and description. However, the description implies the 'organization' context, adding minimal value over the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Broadcast a live command') and target ('to all live algorithms in an organization'), which is specific and actionable. However, it doesn't differentiate from sibling tools like 'create_live_command' or 'stop_live_algorithm', which could handle similar contexts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'create_live_command' (for single algorithms) or 'liquidate_live_algorithm' (for stopping). There's no mention of prerequisites, such as requiring live algorithms to be running, or exclusions, leaving usage context implied but unspecified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations include 'readOnlyHint: true', indicating this is a safe read operation. The description doesn't contradict this, as 'Show' aligns with reading. However, it adds minimal behavioral context beyond annotations—no details on rate limits, authentication needs, or what 'show' entails (e.g., real-time suggestions, batch processing). With annotations covering safety, the description provides some value but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
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's front-loaded with the core action. However, it could be more structured by including key details, but as-is, it's efficiently concise without being overly brief.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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, the description doesn't need to explain safety or return values. However, with 0% schema coverage and no behavioral details, it's incomplete for a tool that likely involves AI or complex processing. It meets a minimal standard but leaves gaps in understanding how to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 mentions 'a specific text input', which hints at the 'sentence' parameter but doesn't explain the 'model' object, 'language', or 'responseSizeLimit'. It adds marginal meaning but doesn't fully compensate for the schema gap, leaving key parameters unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
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 states the tool's purpose (verb: 'Show', resource: 'code completion') but is somewhat vague. It doesn't specify what kind of code completion (e.g., AI-based, IDE-like) or how it differs from sibling tools like 'check_syntax' or 'update_code_to_pep8', leaving room for ambiguity about its exact function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, context (e.g., for programming assistance), or exclusions, and doesn't reference sibling tools. This lack of usage context makes it harder for an agent to decide when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states 'Delete a file' which implies a destructive operation, but annotations already provide idempotentHint=true. The description doesn't add meaningful behavioral context beyond what annotations provide - no information about permissions needed, whether deletion is permanent, confirmation requirements, or error conditions. However, it doesn't contradict the annotations either.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence with no wasted words. It's front-loaded with the core action and resource. While it lacks detail, what's present is efficiently structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive operation tool with 0% schema description coverage and complex nested parameters, the description is inadequate. While there's an output schema (which reduces the need to describe return values), the description doesn't provide enough context about the deletion operation, parameters, or usage scenarios to be complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides zero information about parameters. With 0% schema description coverage and 1 parameter (a nested object with 3 sub-properties), the description fails to compensate for the lack of schema documentation. It doesn't mention projectId, filename, or codeSourceId at all.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete') and resource ('a file in a project'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from sibling tools like 'delete_object' or 'delete_backtest', which also perform deletion operations on different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. There are multiple deletion tools in the sibling list (delete_backtest, delete_object, delete_optimization, delete_project, delete_project_collaborator), but the description doesn't explain when file deletion is appropriate versus deleting other resources.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide idempotentHint=true, indicating repeated calls have the same effect. The description adds no behavioral context beyond 'Delete a project' - it doesn't mention permissions needed, whether deletion is permanent/reversible, confirmation requirements, or side effects. With annotations covering idempotency, the description adds minimal value but doesn't contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at three words with zero wasted language. It's front-loaded with the core action and resource. Every word earns its place, though this conciseness comes at the cost of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive operation with 0% schema description coverage, one parameter, and an output schema (implied but not shown), the description is inadequate. It doesn't explain what happens upon deletion, return values, error conditions, or permissions required. The annotations help with idempotency but don't compensate for the lack of behavioral context in the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, with one parameter (projectId) documented only in the schema with basic description. The tool description adds no parameter information beyond what's implied by 'Delete a project' (needs a project identifier). Since schema coverage is low, the description should compensate but doesn't, resulting in a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
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), making the basic purpose understandable. However, it doesn't differentiate from sibling tools like delete_backtest, delete_file, delete_object, or delete_project_collaborator, which all perform deletion operations on different resources. The purpose is clear but lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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., project must exist), when-not-to-use scenarios (e.g., if project is in use), or explicit alternatives among sibling deletion tools. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true, confirming this is a non-destructive read operation. The description adds minimal behavioral context beyond this—it doesn't mention performance characteristics, rate limits, or authentication needs. Since annotations cover the safety profile, the description meets a baseline but lacks enrichment about what the estimation entails or potential limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single, well-structured sentence that front-loads the core purpose without unnecessary details. Every word contributes directly to understanding the tool's function, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (1 parameter with nested objects, 0% schema coverage) and the presence of an output schema, the description is insufficient. It doesn't clarify parameter semantics or behavioral nuances, relying too heavily on the output schema for return values. For a tool with undocumented parameters, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, meaning parameter details are entirely undocumented in the schema. The description only vaguely references 'specified parameters' without explaining what they are, their purposes, or how they affect the estimation. This fails to compensate for the schema gap, leaving parameters semantically unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Estimate the execution time of an optimization with the specified parameters.' It provides a specific verb ('Estimate') and resource ('execution time of an optimization'), making the function unambiguous. However, it doesn't differentiate from sibling tools like 'create_optimization' or 'read_optimization', which would require explicit comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 an existing optimization setup), contrast with sibling tools (e.g., 'create_optimization' for actual execution), or specify scenarios where estimation is appropriate (e.g., planning or resource allocation). Usage is implied but not articulated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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.
Conciseness5/5
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.
Completeness3/5
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.
Parameters2/5
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.
Purpose3/5
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.
Usage Guidelines2/5
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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds the important behavioral detail that 'The snapshot updates about every 10 minutes,' which is valuable operational context not captured in annotations. However, with no annotations provided, the description doesn't address other key behavioral aspects like whether this is a read-only operation, potential rate limits, authentication requirements, or error conditions. The description partially compensates for missing annotations but leaves significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just two sentences that both earn their place. The first sentence states the core purpose, and the second provides important behavioral context about update frequency. There's no wasted language, repetition, or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 handles return values) and the nested parameter object has good descriptions, the description's main gaps are in usage guidance and top-level parameter explanation. For a tool that reads live data, the description provides basic purpose and update frequency but misses important context about when to use it, authentication needs, and how the 'model' parameter works. It's minimally adequate but with clear deficiencies.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides zero information about parameters, while the schema has 0% description coverage for the top-level 'model' parameter. The nested object 'ReadLiveOrdersRequest' has good parameter descriptions (start, end, projectId), but the description doesn't mention any parameters, explain what 'model' contains, or provide context about how to use the tool. With 0% schema coverage at the top level and no parameter information in the description, this is inadequate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'read out' and resource 'orders of a live algorithm', making the purpose specific and understandable. It distinguishes from siblings like 'read_live_algorithm' or 'read_live_portfolio' by focusing specifically on orders. However, it doesn't explicitly differentiate from 'read_backtest_orders' which might be a similar sibling operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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., requires a live algorithm to be running), doesn't specify when this should be used instead of other order-related tools, and offers no exclusion criteria. The only contextual information is the update frequency, which doesn't help with tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations include 'idempotentHint: true,' which the description does not contradict, as 'update' can be idempotent. However, the description adds no behavioral context beyond this, such as permission requirements, side effects, or rate limits. With annotations covering idempotency, the description meets a baseline but fails to enrich understanding of the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence: 'Update collaborator information in a project.' It is front-loaded with the core action and resource, with no unnecessary words or redundancy. This makes it highly efficient and easy to parse, earning full marks for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a mutation tool with 1 parameter (a nested object), 0% schema description coverage, and an output schema present, the description is minimally complete. It states the purpose but lacks details on usage, parameters, or behavioral traits. The output schema may cover return values, but the description does not provide enough context for effective tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, meaning parameter details like 'liveControl' and 'write' are only documented in the schema. The description adds no semantic information about parameters, such as what 'collaborator information' entails or how updates are applied. It does not compensate for the low schema coverage, leaving parameters poorly explained in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose as 'Update collaborator information in a project,' which is clear but vague. It specifies the verb ('update') and resource ('collaborator information in a project'), but does not differentiate from sibling tools like 'create_project_collaborator' or 'delete_project_collaborator' in terms of scope or specific actions. This makes it minimally adequate but lacking in specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 does not mention prerequisites, such as needing an existing collaborator, or contrast with sibling tools like 'create_project_collaborator' for adding new collaborators or 'delete_project_collaborator' for removal. Without any usage context, it leaves the agent to infer appropriate scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true, indicating this is a safe read operation. The description adds no behavioral traits beyond this—it doesn't mention pagination, rate limits, authentication needs, or what 'list all' entails (e.g., if it returns summaries or full details). With annotations covering safety, the description adds minimal value, scoring baseline for adequate but unenriched context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste: 'List all the optimizations for a project.' It's front-loaded with the core action and resource, making it easy to parse quickly. No extraneous words or redundant information are present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, read-only per annotations, and an output schema exists), the description is minimally complete. It states the purpose but lacks details on usage, behavioral nuances, or parameter specifics. With annotations and output schema handling safety and returns, the description is adequate but leaves gaps in guidance and semantics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description implies a 'project' parameter without detailing it. The schema defines one parameter (projectId), but neither the schema nor description explains its format or constraints beyond the example. With low coverage, the description partially compensates by hinting at the parameter's role, but it's insufficient for full clarity, meeting the baseline for minimal viability.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
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 verb ('List') and resource ('optimizations'), but it's vague about scope and doesn't differentiate from siblings like 'read_optimization' (which reads a single optimization) or 'list_backtests' (which lists a different resource). It specifies 'for a project' which provides some context but lacks specificity about what 'optimizations' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 sibling tools like 'read_optimization' (for single optimization details) or 'create_optimization' (for creating new ones), nor does it specify prerequisites, exclusions, or typical use cases. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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.
Conciseness5/5
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.
Completeness2/5
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.
Parameters2/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only provide a title ('Read live algorithm'), which doesn't cover behavioral traits. The description adds that it reads 'details' but doesn't disclose what those details include, whether it requires specific permissions, rate limits, or error conditions. It doesn't contradict annotations, but provides minimal behavioral context beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 with the core action and resource, making it immediately clear what the tool does. Every word earns its place, though more content could enhance utility without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 (which should define return values), the description doesn't need to explain outputs. However, with no annotations covering behavioral traits and 0% schema description coverage for the single parameter, the description is minimal. It states the basic purpose but lacks context on usage, parameter meaning, or detailed behavior, making it adequate but incomplete for optimal agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the single parameter 'projectId' has no description in the schema. The tool description doesn't mention parameters at all, failing to compensate for the schema gap. However, with only one parameter and a straightforward naming convention ('projectId'), the baseline is 3 as the agent can infer meaning from context, though explicit guidance would improve this.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Read details of a live algorithm' clearly states the verb ('read') and resource ('live algorithm'), but it's vague about what 'details' specifically include. It distinguishes from obvious siblings like 'create_live_algorithm' or 'stop_live_algorithm', but doesn't differentiate from similar read operations like 'read_live_chart' or 'read_live_insights' that might provide more specific details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With siblings like 'list_live_algorithms' (for listing) and other 'read_live_*' tools (for specific aspects), there's no indication of when this general 'details' tool is appropriate versus more specialized ones. No prerequisites or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only provide a title ('Read live insights'), so the description carries the burden of behavioral disclosure. It adds valuable context: the snapshot updates about every 10 minutes, which informs the agent about data freshness and potential delays. This goes beyond what annotations provide, though it could be more detailed (e.g., on permissions or error handling).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core purpose in the first sentence. The second sentence adds useful behavioral context without redundancy. However, it could be more structured by explicitly addressing parameters or usage scenarios.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (involves live algorithm insights with parameters) and the presence of an output schema (which handles return values), the description is partially complete. It covers the purpose and a key behavioral trait but lacks parameter explanations and usage guidelines, making it adequate but with clear gaps for effective tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 does not mention any parameters, failing to compensate for this gap. It should explain the 'model' parameter (which includes start, end, and projectId) to help the agent understand what inputs are needed and why.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'Read[s] out the insights of a live algorithm,' which clarifies the verb (read) and resource (insights of a live algorithm). However, it does not differentiate from sibling tools like 'read_backtest_insights' or 'read_live_logs,' leaving ambiguity about when to use this specific tool versus other read operations on live algorithms.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description mentions snapshot updates every 10 minutes, but this is a behavioral trait rather than usage context. There is no mention of prerequisites, alternatives, or exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate 'destructiveHint: false', confirming non-destructive behavior, which the description aligns with by implying a read operation. The description adds value by specifying that it creates a job for downloading and returns a job Id, offering context beyond annotations, but doesn't detail job lifecycle, permissions, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded in a single sentence, efficiently stating the core action without unnecessary details. However, it could be slightly improved by clarifying the two-step process more explicitly, but overall it's well-structured with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (involving job creation and file downloads), annotations cover safety, and an output schema exists, reducing the need for return value details. However, the description lacks parameter explanations and usage context, making it incomplete for effective agent use despite structured data support.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, with parameters 'organizationId' and 'keys' undocumented in the schema. The description provides no parameter semantics, failing to explain what 'organizationId' or 'keys' represent, their formats, or how they relate to the job creation, leaving significant gaps in understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Create a job to download files' and 'read the job Id'), identifying the resource (Object Store files) and the outcome (job Id). However, it doesn't explicitly differentiate from sibling tools like 'read_object_store_file_download_url', which might offer alternative file access methods.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, such as 'read_object_store_file_download_url' for direct URLs or 'list_object_store_files' for browsing. It lacks context about prerequisites, timing, or workflow integration, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds minimal behavioral context beyond annotations. Annotations provide 'idempotentHint: true', indicating safe retry behavior, but the description doesn't elaborate on what 'stop' entails (e.g., whether it halts trading immediately, preserves state, or requires specific permissions). No contradiction with annotations exists, but the description misses opportunities to clarify the tool's operational impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place, though this comes at the cost of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (stopping a live algorithm is a significant operation), the description is inadequate. While an output schema exists (which reduces the need to describe return values), the description lacks crucial context: no parameter guidance, no behavioral details beyond the basic action, and no differentiation from sibling tools. For a mutation tool with only minimal annotations, this leaves substantial gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, with only one parameter ('projectId') documented in the schema without a description. The tool description provides no parameter information whatsoever, failing to compensate for the schema's lack of documentation. This leaves the agent with insufficient understanding of what 'projectId' represents or how to obtain it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Stop') and target resource ('a live algorithm'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'liquidate_live_algorithm' or 'broadcast_live_command', which might have overlapping or related functionality in the live algorithm context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. There are multiple sibling tools related to live algorithms (e.g., 'liquidate_live_algorithm', 'broadcast_live_command', 'create_live_algorithm'), but the description doesn't mention any of them or explain when this specific stop action is appropriate versus other control mechanisms.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide idempotentHint=true, but the description adds minimal behavioral context beyond the basic action. It doesn't disclose permissions needed, whether the update overwrites or merges content, error conditions, or rate limits. However, it doesn't contradict annotations, and with annotations covering idempotency, the bar is lower.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 complexity, earning its place without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 (not provided in context but indicated as true), the description needn't explain return values. However, for a mutation tool with annotations only covering idempotency, the description lacks details on side effects, error handling, or integration with sibling tools, making it minimally adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the input schema itself has detailed descriptions for all parameters (projectId, name, content, codeSourceId). The description adds no parameter semantics beyond what the schema provides, so it meets the baseline of 3 since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Update the contents of a file' clearly states the action (update) and resource (file contents), but it's vague about scope and doesn't differentiate from sibling tools like update_file_name or create_file. It lacks specificity about what kind of file system or context is involved.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 update_file_name or create_file. The description doesn't mention prerequisites (e.g., file must exist), exclusions, or contextual cues for selection among sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide destructiveHint=false, indicating it's non-destructive. The description adds that it's asynchronous, which is valuable context not in annotations. However, it doesn't mention authentication needs, rate limits, or what 'compile job' entails beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 efficiently includes the asynchronous nature and project scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 (which handles return values) and non-destructive annotations, the description covers the basic action and async behavior. However, with 0% schema coverage and no usage guidance, it leaves gaps in parameter understanding and tool selection context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, with one parameter ('model' containing 'projectId') undocumented in schema. The description mentions 'for a project' but doesn't explain what 'projectId' represents or how to obtain it, failing to compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('create a compile job request') and resource ('for a project'), and specifies it's asynchronous. However, it doesn't differentiate from potential siblings like 'create_backtest' or 'create_optimization' which might also involve project processing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With siblings like 'check_syntax' or 'create_backtest', the description doesn't indicate if this should precede or follow those operations, or what specific compile scenarios it addresses.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide idempotentHint=true, indicating safe retry behavior. The description adds that it 'liquidates and stops', implying a destructive operation that terminates the algorithm, which is useful context beyond annotations. However, it doesn't detail effects like data loss, permissions needed, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded and wastes no space, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has annotations (idempotentHint) and an output schema, the description covers the basic action. However, for a destructive operation with 0% schema coverage and no sibling differentiation, it lacks details on parameters, usage context, and behavioral nuances, making it incomplete for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, with one parameter ('projectId') undocumented in the schema. The description provides no information about parameters, failing to compensate for the lack of schema documentation, leaving the agent without guidance on what 'projectId' represents or how to use it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'stop_live_algorithm', 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.
Usage Guidelines2/5
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 'stop_live_algorithm' or 'delete_live_algorithm', nor does it mention prerequisites or context for liquidation. It lacks explicit when-to-use or when-not-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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.
Conciseness5/5
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.
Completeness3/5
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.
Parameters2/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the data updates every 10 minutes, which is useful behavioral context about freshness. However, it doesn't mention permissions, rate limits, or what the output contains (though an output schema exists, reducing this burden).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with two sentences. The first sentence states the purpose, and the second adds valuable behavioral context about update frequency. There is no wasted text, and it's front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 (which handles return values) and no annotations, the description is minimally adequate. It covers the basic purpose and a key behavioral trait (update frequency), but lacks parameter details and usage guidelines, leaving gaps for an agent to infer correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds no information about the single parameter 'projectId' beyond what the schema minimally provides (type and requirement). No examples, constraints, or meaning of the parameter are explained in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Read out') and resource ('portfolio state of a live algorithm'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'read_live_algorithm' or 'read_live_insights', which might provide related but different data about live algorithms.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 mentions the snapshot updates every 10 minutes, which hints at usage timing, but doesn't specify prerequisites, exclusions, or compare to other read tools for live algorithms in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true, suggesting a safe read operation. The description adds behavioral context: it runs a backtest for 'a few seconds' and focuses on initialization errors, which clarifies the scope beyond just reading. However, it doesn't detail side effects (e.g., resource usage), rate limits, or error handling. No contradiction with annotations exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that front-loads the purpose. It's appropriately sized without wasted words, though it could be slightly more structured (e.g., separating purpose from constraints).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (involves backtesting and error detection), annotations cover safety (readOnlyHint), and an output schema exists (so return values needn't be described). However, the description lacks details on parameter usage, error conditions, and how it differs from siblings, making it adequate but with gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries full burden. It mentions 'algorithm' indirectly via 'initialize the algorithm', but doesn't explain the 'model' parameter's structure (e.g., files, language) or how it relates to the algorithm. The description adds minimal semantic value beyond the schema's properties.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Run a backtest for a few seconds to initialize the algorithm and get initialization errors if any.' It specifies the verb ('run a backtest'), resource ('algorithm'), and outcome ('get initialization errors'). However, it doesn't explicitly differentiate from sibling tools like 'check_syntax' or 'create_backtest', which prevents a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 compiled algorithm first), exclusions, or compare it to similar tools like 'check_syntax' or 'create_backtest'. The context is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations include 'idempotentHint: true', indicating safe retries, but the description adds minimal behavioral context. It mentions deletion is for a 'specific organization and key', which clarifies scope, but doesn't address permissions, side effects (e.g., irreversible deletion), or response details. No contradiction with annotations, but the description adds only modest value 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words, front-loading the core action. It could be slightly more structured (e.g., separating purpose from parameters), but it efficiently conveys the essential information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (destructive operation with 1 parameter, 0% schema coverage, annotations, and an output schema), the description is minimally adequate. It covers the basic purpose and parameters but lacks details on usage, behavioral traits, or output implications. The output schema likely handles return values, but the description doesn't fully compensate for other gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by specifying that parameters are for 'organization and key', aligning with the schema's 'organizationId' and 'key'. However, it doesn't explain parameter formats, constraints, or relationships beyond this basic mapping. With low schema coverage, the description adds some meaning but not comprehensive details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete') and the resource ('Object Store file'), specifying it targets a specific organization and key. It distinguishes from sibling tools like 'upload_object' and 'list_object_store_files' by focusing on deletion. However, it doesn't explicitly differentiate from other deletion tools (e.g., 'delete_file'), which slightly reduces specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 the file to exist), exclusions, or comparisons to similar tools like 'delete_file' or 'delete_object' operations in other contexts. Usage is implied but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 context by specifying it reads a 'result', implying it's for completed jobs rather than real-time status. However, it doesn't disclose rate limits, authentication needs, or error behaviors beyond what annotations cover.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with zero waste. It directly states the action and target, making it efficient and easy to parse, though it could benefit from more detail given the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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, the description is minimally complete. However, for a tool with 1 parameter (a nested object) and no schema descriptions, it should explain more about the compile process and result format to aid the agent fully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 implies parameters are needed to identify the compile job. It doesn't detail the 'model' parameter's structure or semantics, but since there's only one parameter (a nested object with projectId and compileId), the baseline is high. The description could compensate more by mentioning these IDs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Read a compile packet job result' states the verb ('Read') and resource ('compile packet job result'), but it's vague about what a 'compile packet job' entails and doesn't differentiate from sibling tools like 'read_backtest' or 'read_optimization'. It's adequate but lacks specificity about the domain context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With siblings like 'create_compile' and 'read_backtest', it's unclear if this is for retrieving results after compilation or for monitoring ongoing jobs. No explicit when/when-not statements or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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.
Conciseness5/5
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.
Completeness3/5
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.
Parameters3/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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.
Behavior3/5
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.
Conciseness5/5
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.
Completeness3/5
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.
Parameters3/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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.
Behavior3/5
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.
Conciseness5/5
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.
Completeness3/5
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.
Parameters3/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide idempotentHint=true and destructiveHint=false, which the description doesn't contradict. The description adds no behavioral context beyond what annotations already cover (like permission requirements, rate limits, or what happens on duplicate adds). With annotations doing the heavy lifting, this is adequate but not insightful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it highly efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has annotations (idempotent, non-destructive), a detailed input schema with full property descriptions, and an output schema (implied by 'Has output schema: true'), the description is minimally complete. However, it lacks context about collaboration roles, permissions, or error conditions that would help an agent use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 any parameters. The single parameter 'model' and its nested properties (projectId, collaboratorUserId, etc.) are undocumented in the description. However, since the schema fully defines all required fields with descriptions, the baseline of 3 is appropriate as the schema carries the burden.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add') and resource ('a collaborator to a project'), making the purpose immediately understandable. However, it doesn't differentiate from the sibling tool 'update_project_collaborator' or 'delete_project_collaborator', which would be necessary for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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' or 'delete_project_collaborator'. There's no mention of prerequisites, constraints, or typical use cases, leaving the agent with minimal contextual direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true, indicating this is a safe read operation. The description adds value by specifying what the tool does ('Show additional context and suggestions'), which aligns with the read-only nature. However, it doesn't disclose important behavioral details like whether this performs AI analysis, what format the enhancements come in, latency expectations, or any rate limits. With annotations covering the safety profile, this earns a baseline 3 for adding some context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 purpose and doesn't include unnecessary elaboration. Every word earns its place by directly describing the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 handles return values), annotations cover read-only safety, and there's only 1 parameter, the description is somewhat complete for basic understanding. However, for a tool that presumably performs AI-enhanced error analysis, the description lacks important context about what 'additional context and suggestions' means, how comprehensive they are, or any limitations. It's minimally adequate but leaves significant questions unanswered about the tool's capabilities.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning parameters are completely undocumented in the schema. The description doesn't mention any parameters at all, failing to compensate for the schema gap. However, there's only 1 parameter (a nested object 'model'), so the baseline is 4 for 0 parameters, but since the description provides zero parameter information, it drops to 3. The description doesn't explain what 'model' should contain or how to structure the error enhancement request.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Show additional context and suggestions for error messages.' It specifies the verb ('Show') and the resource ('additional context and suggestions for error messages'), making it clear this is an enhancement/analysis tool. However, it doesn't explicitly distinguish itself from potential sibling tools like 'check_syntax' or 'check_initialization_errors' that might also handle errors differently.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. There's no mention of prerequisites, when this enhancement is most useful, or what types of errors it works best with. Given the sibling tools include multiple error-related tools ('check_initialization_errors', 'check_syntax'), the lack of differentiation is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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.
Conciseness5/5
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.
Completeness3/5
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.
Parameters3/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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.
Behavior3/5
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 context by specifying the directory-based listing scope ('under a specific directory'), which isn't covered by annotations. However, it doesn't disclose other behavioral traits like pagination, rate limits, error conditions, or output format details, leaving gaps despite the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently conveys the core purpose without redundancy. It's front-loaded with key information ('List the Object Store files') and avoids unnecessary words, 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, read-only per annotations) and the presence of an output schema (which handles return values), the description is minimally adequate. However, it lacks usage guidelines and detailed parameter semantics, making it incomplete for optimal agent decision-making. The annotations help but don't fully compensate for these gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries full burden for parameter meaning. It mentions 'directory in an organization,' which loosely maps to the path and organizationId parameters but lacks specifics like format examples or optionality. Since there's only 1 parameter (a nested object with two fields), the baseline is 3, as the description provides some high-level context without detailed compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('Object Store files'), specifying the scope as 'under a specific directory in an organization.' It distinguishes this tool from other list tools (e.g., list_backtests, list_projects) by focusing on Object Store files. However, it doesn't explicitly differentiate from potential siblings like read_object_store_file_download_url, which is a minor gap.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 organization access), exclusions (e.g., not for reading file contents), or related tools like read_object_store_file_download_url for downloading files. This leaves the agent with minimal context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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.
Conciseness5/5
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.
Completeness3/5
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.
Parameters3/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true, which aligns with the 'Get' action in the description, so there is no contradiction. The description adds minimal behavioral context beyond annotations—it implies this tool retrieves a URL for downloading, but does not specify if the URL is time-limited, requires authentication, or details rate limits. With annotations covering safety, a baseline score is appropriate as the description adds some value but lacks rich behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words, making it highly concise and front-loaded. It efficiently communicates the core function without unnecessary elaboration, earning full marks for structure and brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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, the description does not need to cover safety or return values. However, it lacks details on parameter usage, behavioral traits like URL expiration, and guidance relative to siblings. For a tool with 0% schema coverage and no output description, the description is minimally adequate but leaves gaps in context, scoring at the baseline for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 does not mention any parameters or their semantics, such as 'organizationId' or 'jobId', failing to compensate for the schema gap. However, since there is only one top-level parameter ('model'), which is a nested object, the baseline is adjusted to 3 as the description does not add meaningful parameter information beyond what is implied by the tool name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get the URL') and the resource ('for downloading files from the Object Store'), making the purpose evident. However, it does not explicitly differentiate this tool from its sibling 'read_object_store_file_job_id', which appears related, so it misses the highest score for sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, such as 'read_object_store_file_job_id' or 'list_object_store_files'. There is no mention of prerequisites, context, or exclusions, leaving usage unclear beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide idempotentHint=true, indicating safe retries, but the description adds minimal behavioral context. It specifies that only 'name or note' can be updated, which clarifies the scope of changes, but doesn't address permissions, side effects, or error conditions. No contradiction with annotations exists, but the description doesn't enrich beyond the idempotency hint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('Update the name or note of a backtest'). There is no wasted wording, and it directly communicates the tool's function without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 (which handles return values), annotations (idempotentHint), and a simple purpose, the description is somewhat complete but lacks details on parameter requirements and usage context. For a mutation tool with 0% schema coverage, it should better explain the input structure and when to apply updates.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, but it only mentions 'name or note' without explaining the required 'projectId' and 'backtestId' parameters. It adds some meaning by specifying updatable fields, but leaves key identifiers undocumented. With 0% coverage, this partial compensation results in a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Update') and the resource ('backtest'), specifying what fields can be modified ('name or note'). It distinguishes from siblings like 'create_backtest' or 'delete_backtest' by focusing on modification rather than creation or deletion. However, it doesn't explicitly differentiate from 'update_project' or 'update_optimization' which might have similar naming patterns.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 an existing backtest), exclusions (e.g., not for updating other backtest attributes), or refer to sibling tools like 'read_backtest' for checking current values before update. Usage is implied by the verb 'Update' but lacks explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true, indicating this is a safe read operation. The description adds that it 'updates' code, which could imply mutation, but in context, this likely means transforming code for style compliance without permanent changes. It doesn't contradict annotations, but adds minimal behavioral context beyond them, such as whether it modifies files in-place or returns formatted content.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Update Python code to follow PEP8 style.' It's front-loaded with the core action and resource, with no wasted words. Every part of the sentence contributes essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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, the description doesn't need to cover safety or return values. However, with 0% schema coverage and no usage guidelines, it's incomplete for a code transformation tool. It adequately states the purpose but lacks details on parameters and context, making it minimally viable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries full burden for parameter meaning. It mentions 'Python code' but doesn't explain the 'model' parameter or its 'files' structure. The description adds some context by implying input is code, but fails to detail parameter requirements or usage, resulting in a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Update Python code to follow PEP8 style.' It specifies the verb ('Update') and resource ('Python code') with a clear objective. However, it doesn't differentiate from sibling tools like 'check_syntax' or 'complete_code' that also process code, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, when not to use it, or compare it to siblings like 'check_syntax' for validation or 'update_file_contents' for general updates. This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide idempotentHint=true, indicating safe retry behavior, which the description doesn't repeat. The description adds minimal behavioral context beyond annotations—it implies a mutation operation but doesn't specify permissions, side effects, or error conditions. With annotations covering idempotency, the description adds some value but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 directly states the tool's action, 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.
Completeness3/5
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 (not provided in context) and annotations for idempotency, the description is minimally adequate but incomplete. It doesn't address mutation risks, parameter requirements, or sibling differentiation, leaving gaps in understanding for a file-update operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 'name of a file' but doesn't detail the required 'model' parameter or its nested fields (projectId, name, newName, codeSourceId). The baseline is 3 since the schema lacks descriptions, but the description adds no parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Update the name of a file' clearly states the verb ('update') and resource ('name of a file'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'update_file_contents' or 'update_project', which could involve similar operations on different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. There's no mention of prerequisites, constraints, or comparison with sibling tools like 'update_file_contents' or 'create_file', leaving the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide idempotentHint=true, indicating safe retries, but the description adds minimal behavioral context. It doesn't disclose permissions required, side effects (e.g., whether other optimization properties are affected), or error conditions. With annotations covering idempotency, the description adds little beyond the basic action, but doesn't contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 easy to scan. Every word earns its place, achieving maximum efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 (implying return values are documented elsewhere), annotations cover idempotency, and the schema describes parameters, the description is minimally adequate. However, for a mutation tool, it lacks context on permissions, side effects, or error handling, leaving gaps in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the schema itself includes descriptions for 'optimizationId' and 'name' parameters. The description mentions updating the name, implying the 'name' parameter, but doesn't add meaning beyond what's in the schema (e.g., format constraints or examples). With schema doing the work, baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Update') and the resource ('name of an optimization'), making the purpose understandable. It distinguishes from siblings like 'create_optimization' and 'delete_optimization' by focusing on name updates, though it doesn't explicitly differentiate from other update tools like 'update_backtest' or 'update_project'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 an existing optimization), exclusions, or comparisons to siblings like 'update_backtest' or 'update_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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds minimal behavioral context beyond annotations. Annotations provide 'idempotentHint: true', indicating safe retries, but the description doesn't elaborate on effects like partial updates or permissions. It doesn't contradict annotations, but offers little extra insight into mutation behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action. Every word contributes directly to understanding the tool's purpose without any redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a mutation tool with idempotent annotations and an output schema, the description is minimally adequate. It covers the basic action but lacks details on error conditions, update scope, or relationships with sibling tools, leaving gaps for an AI agent to infer usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description mentions 'name or description', hinting at two parameters. However, it omits the required 'projectId' and doesn't clarify parameter interactions or defaults. It adds some meaning but doesn't fully compensate for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Update') and resource ('a project's name or description'), making the purpose immediately understandable. It specifies what can be modified, though it doesn't explicitly differentiate from sibling tools like 'update_project_nodes' or '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.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, such as needing an existing project ID, or contrast with tools like 'create_project' or 'delete_project'. Usage context is implied but not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide idempotentHint=true, indicating safe retries. The description adds that it uploads 'files' to 'Object Store', implying a write operation, which aligns with the tool name. However, it doesn't disclose rate limits, permissions needed, or what happens on conflict (e.g., overwrite behavior), leaving behavioral gaps despite annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 easy to scan and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 1 parameter with 0% schema coverage, no output schema details provided, and annotations limited to idempotency, the description is minimal. It states the purpose but lacks context on parameters, error handling, or integration with siblings like delete_object. For a write tool, more behavioral context would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the input schema defines 'model' with nested properties (organizationId, key, objectData). The description doesn't explain these parameters at all, offering no semantic value beyond the schema. Baseline 3 is appropriate as the schema carries the full parameter documentation burden.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Upload files to the Object Store' clearly states the action (upload) and target resource (Object Store files). It distinguishes from siblings like 'delete_object' and 'list_object_store_files', but doesn't specify file types or constraints beyond the generic term 'files'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention prerequisites like authentication, file size limits, or when to choose upload_object over other file-related tools like create_file. The description assumes context without providing usage boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide idempotentHint=true, indicating safe retry behavior. The description adds that this is a deletion operation, which implies destructive action, but doesn't elaborate on permissions, side effects, or confirmation requirements. It doesn't contradict annotations, but adds minimal behavioral context beyond 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately understandable. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's destructive nature, annotations cover idempotency, the schema documents parameters well, and an output schema exists (though not shown). The description could better address behavioral aspects like permissions or side effects, but for a simple delete operation with good structured data, it's reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the input schema includes detailed descriptions for 'projectId' and 'backtestId' within the nested object. The description doesn't add any parameter semantics beyond what's in the schema. With schema doing the documentation work, baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete') and resource ('a backtest from a project'), making the purpose unambiguous. It doesn't explicitly differentiate from sibling tools like 'delete_file' or 'delete_optimization', but the specificity of 'backtest' and 'project' context provides inherent distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 the backtest to exist), nor does it reference sibling tools like 'list_backtests' for discovery or 'update_backtest' as an alternative. Usage context is implied but not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states 'Remove' which implies a destructive operation, but annotations only provide idempotentHint=true and a title. The description doesn't add behavioral context beyond the obvious destructive nature - no mention of permissions required, whether removal is reversible, or what happens to the collaborator's access. With minimal annotations, the description carries most of the burden but provides only basic behavioral information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words. It's front-loaded with the core action and target. Every word earns its place - 'Remove' specifies the action, 'a collaborator' specifies what's being removed, and 'from a project' specifies the context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive operation with idempotentHint annotation and an output schema, the description is minimal but adequate. It states what the tool does, but doesn't provide context about permissions, consequences, or error conditions. The presence of an output schema means return values are documented elsewhere, but the description could better prepare the agent for using this mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage (parameter count is 1 but it's a nested object with 2 sub-parameters), yet the description doesn't mention any parameters at all. However, since the tool name and description clearly imply what needs to be specified (a project and a collaborator), and the schema itself documents the two required fields well, the description gets a baseline 4 for a tool with obvious parameter needs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Remove') and target ('a collaborator from a project'), making the purpose immediately understandable. It doesn't differentiate from sibling tools like 'update_project_collaborator' or 'create_project_collaborator', but it's specific enough to understand what the tool does without being tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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' or 'lock_project_with_collaborators'. There's no mention of prerequisites, permissions needed, or consequences of removal. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true, which the description doesn't contradict. The description adds minimal behavioral context beyond annotations—it implies retrieval of details but doesn't specify format, pagination, or error handling. With annotations covering safety, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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, the description is reasonably complete for a simple read operation. It could improve by clarifying scope versus siblings, but the structured data reduces the burden on the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides no parameter information beyond what's implied by 'project'. The schema's 'projectId' parameter is documented with a description, so the baseline is 3 as the schema compensates for the description's lack of detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('project details'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'list_projects' or 'read_project_collaborators', which would require more specificity to earn a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'list_projects' or other read_* tools. It lacks any context about prerequisites, exclusions, or comparative use cases, leaving the agent without direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true, so the agent knows this is a safe read operation. The description adds minimal behavioral context beyond this, as it doesn't specify what 'collaborators' includes (e.g., roles, permissions) or any limitations (e.g., pagination, access controls). However, it doesn't contradict the annotations, and with annotations covering safety, the description's lack of detail is acceptable but not enriching.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words, making it highly concise and front-loaded. It directly states the tool's function without unnecessary elaboration, which is efficient for an AI agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter, read-only operation) and the presence of annotations (readOnlyHint) and an output schema (implied by context signals), the description is reasonably complete. It covers the core action, though it could benefit from more context on usage or output details, but the structured data helps fill gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 add any parameter details beyond what's implied by the tool name. It doesn't explain the 'projectId' parameter's format, constraints, or how to obtain it. Since there's only one parameter and the schema provides basic documentation (title, type, example), the baseline of 3 is appropriate, but the description fails to compensate for the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('List') and resource ('collaborators on a project'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'list_projects' or 'read_project', which also involve reading project-related data, so it doesn't fully distinguish itself from alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 project ID), exclusions, or compare it to sibling tools like 'list_projects' or 'read_project_collaborator' (which might handle individual collaborators). This lack of context leaves the agent guessing about appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description adds minimal behavioral context by specifying what gets read ('available and selected nodes'), but doesn't elaborate on format, pagination, or other behavioral traits. With annotations covering the safety profile, this earns a baseline 3 for adding some value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a simple read operation and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read operation with readOnlyHint annotation and an output schema, the description provides adequate context. It specifies what data is retrieved ('available and selected nodes'), which complements the structured fields. The main gap is lack of usage guidance relative to sibling tools, but overall completeness is reasonable given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the single parameter 'projectId' has no description in the schema. The tool description doesn't mention parameters at all, failing to compensate for the schema gap. However, with only one parameter and an output schema present, the baseline remains at 3 since the description doesn't add parameter meaning but the overall context is manageable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('read') and resource ('available and selected nodes of a project'), making the purpose understandable. However, it doesn't distinguish this tool from similar sibling tools like 'read_project' or 'update_project_nodes', which would require more specific differentiation for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. There are several sibling 'read_' tools (e.g., 'read_project', 'read_project_collaborators') with no indication of when this specific node-reading tool is appropriate versus other project-related read operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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.
Conciseness5/5
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.
Completeness4/5
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.
Parameters4/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true and openWorldHint=true, which already convey that this is a safe, read-only operation with open-world assumptions. The description adds no behavioral details beyond this, such as rate limits, authentication needs, or what 'account status' entails, so it provides minimal 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words, making it highly concise and front-loaded. It efficiently communicates the core purpose without unnecessary elaboration, which is ideal for such a straightforward tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, annotations covering safety (readOnlyHint) and assumptions (openWorldHint), and an output schema exists, the description is reasonably complete. It states what the tool does, though it could benefit from more context on what 'account status' includes or typical use cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema description coverage, the schema fully documents the lack of inputs. The description doesn't need to explain parameters, and it doesn't add any semantic details beyond the schema, which is acceptable for a parameterless tool, warranting a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Read') and resource ('organization account status'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'read_project' or 'read_backtest', which follow similar naming patterns but target different resources, so it lacks 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.
Usage Guidelines2/5
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 context, prerequisites, or exclusions, leaving the agent to infer usage based on the name alone, which is insufficient for optimal tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true, confirming this is a safe read operation. The description adds minimal behavioral context beyond this, stating it returns a list with basic information but not detailing format, pagination, or potential errors. Since annotations cover the safety profile, the description meets the lower bar by providing some additional context without contradicting annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently conveys the core functionality without unnecessary words. It is front-loaded with the main action and resource, making it easy to parse. Every part of the sentence contributes directly to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (0 parameters, read-only operation), the description is reasonably complete. It specifies what is returned, and with an output schema present, detailed return value explanations are unnecessary. However, it could benefit from more context on usage scenarios or data specifics to enhance completeness for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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. A baseline of 4 is applied as the schema fully handles parameters, and the description doesn't need to compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Returns a list of LEAN versions with basic information for each version.' It specifies the verb ('Returns'), resource ('LEAN versions'), and scope ('list with basic information'). However, it doesn't differentiate from sibling tools like 'read_mcp_server_version' or 'read_latest_mcp_server_version', which appear related but target different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 any prerequisites, context for usage, or comparisons to sibling tools such as 'read_mcp_server_version' or 'read_latest_mcp_server_version', which might serve similar purposes for different data. This lack of explicit guidance leaves the agent without clear direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 useful behavioral context by specifying that it 'doesn't work if the key is a directory,' which is not covered by annotations. However, it doesn't provide additional details like rate limits, authentication needs, or error handling, so it only partially enhances transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, with the main purpose stated first and a critical limitation added in a second sentence. There's no wasted text, but it could be slightly more structured for clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (read operation with specific constraints), annotations cover safety, and an output schema exists, the description is reasonably complete. It adds key behavioral context (directory limitation) but could benefit from more usage guidance relative to siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 compensates by clarifying that parameters are for 'a specific organization and key.' It doesn't elaborate on parameter formats or constraints beyond this. Since there's only one parameter (a nested object with two fields), the baseline is reasonable, but more detail could improve utility.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get Object Store properties of a specific organization and key.' It specifies the verb ('Get'), resource ('Object Store properties'), and scope ('specific organization and key'). However, it doesn't explicitly differentiate from sibling tools like 'read_object_store_file_download_url' or 'list_object_store_files', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage guidance with the statement: 'It doesn't work if the key is a directory in the Object Store.' This implies when not to use the tool. However, it doesn't offer explicit alternatives or clarify when to use this tool versus similar siblings, leaving some ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 behavioral context by specifying that it can read a single file or all files, which goes beyond the annotations. However, it doesn't disclose details like rate limits, authentication needs, error handling, or what 'read' entails (e.g., returns file contents vs. metadata). With annotations covering safety, a 3 is appropriate for adding some value without rich behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action ('Read a file from a project') and efficiently adds the conditional behavior. Every word serves a purpose with zero waste, making it appropriately sized and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 files with optional filtering), annotations cover safety, and an output schema exists (implied by context signals), reducing the need to explain return values. The description addresses key usage but could improve by mentioning error cases or limitations. It's mostly complete for a read operation with good structural support.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by explaining the 'name' parameter's role: if omitted, it reads all files. However, it doesn't clarify the 'projectId' or 'codeSourceId' parameters. With one parameter (a nested object) and no schema descriptions, the baseline is low, but the description adds partial meaning for one aspect, warranting a 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Read') and resource ('a file from a project'), specifying the action and target. It distinguishes from siblings like 'read_object_store_file_download_url' or 'read_project' by focusing on project files. However, it doesn't explicitly differentiate from 'read_file_contents' or similar file-reading siblings that might exist in other contexts, though none are present in the provided sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by stating 'or all files in the project if no file name is provided,' which gives context for when to omit the 'name' parameter. However, it lacks explicit guidance on when to use this tool versus alternatives like 'list_object_store_files' or 'read_object_store_file_download_url' for different file sources, and doesn't mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context beyond annotations: it describes the browser automation ('automatically opens your browser'), the authentication flow, and a prerequisite (logged into QuantConnect account). This enhances understanding of the tool's interactive nature without contradicting annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with three sentences that are front-loaded (starts with the core purpose) and efficient. Each sentence adds value: the first states the purpose, the second explains the browser automation, and the third provides a prerequisite. No wasted words, though minor formatting issues exist.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (interactive authentication), annotations cover safety and idempotency, and an output schema exists (so return values need not be explained). The description adds crucial context about the browser flow and prerequisites, making it fairly complete for an agent to use the tool effectively, though it could mention the parameter briefly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention parameters at all. However, there is only one parameter ('brokerage'), which is an enum with clear values (e.g., 'alpaca', 'tradestation'). The description fails to add meaning beyond the schema, but with a single parameter and high schema clarity, a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Authorize an external connection with a live brokerage or data provider.' It specifies the verb ('authorize') and resource ('external connection'), but does not differentiate from sibling tools, as no similar authorization tools are listed among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (for authorizing external connections) and provides prerequisites (must be logged into QuantConnect account in browser), but does not explicitly state when not to use it or name alternatives. It offers some context but lacks explicit exclusions or comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 valuable behavioral context beyond annotations: it explains the effect of omitting nodes (all nodes become inactive, autoSelectNode=true) and clarifies the tool's dual functionality (activating specific nodes vs. deactivating all). This goes beyond what annotations convey about safety and idempotency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (two sentences) and front-loaded: the first sentence states the primary purpose, the second explains the alternative behavior. Every word earns its place with no redundancy or fluff. The structure logically presents the main use case followed by the edge case.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (managing node activation states), the description covers the core behavior well. Annotations provide safety context (idempotent, non-destructive), and there's an output schema (though not shown), so return values don't need explanation. The description explains the key behavioral nuance (nodes parameter effect), making it reasonably complete for agent use, though it could benefit from more parameter details given the low schema coverage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the schema provides no parameter descriptions. The description adds some semantic context: it explains the effect of providing nodes (activate them) versus omitting them (deactivate all, enable autoSelectNode). However, it doesn't detail the 'projectId' parameter or the format of 'nodes' (array of strings). Since schema coverage is low, the description partially compensates but leaves gaps in parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Update the active state of the given nodes to true.' This specifies the verb ('update'), resource ('nodes'), and the specific action ('active state to true'). It distinguishes from siblings like 'read_project_nodes' (which reads) and 'update_project' (which updates project metadata). However, it doesn't explicitly differentiate from other node-related tools since none exist in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage context: 'If you don't provide any nodes, all the nodes become inactive and autoSelectNode is true.' This implies when to use the tool (to activate specific nodes or deactivate all nodes) and hints at the default behavior. However, it doesn't explicitly state when to use this tool versus alternatives (like 'read_project_nodes' for checking current status) or mention prerequisites (e.g., needing a valid projectId).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 value by specifying that it returns the version 'that's running', clarifying it's for the active server instance rather than a static or latest version. This contextual detail enhances understanding beyond the annotations, though it doesn't cover aspects like rate limits or auth needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the key information ('Returns the version') with no wasted words. It is appropriately sized for a simple tool and every part of the sentence contributes to understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (0 parameters, read-only operation), the description is complete enough. It clearly states the purpose, and with annotations covering safety and an output schema presumably detailing the return value, no additional explanation of behavior or outputs is necessary. It adequately covers all needed context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema description coverage, the schema fully documents the lack of inputs. The description doesn't need to add parameter details, so it appropriately focuses on the tool's purpose. A baseline of 4 is given as it compensates well for the trivial parameter scenario.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Returns') and resource ('version of the QC MCP Server that's running'), distinguishing it from siblings like 'read_latest_mcp_server_version' which likely fetches a different version reference. It precisely defines what the tool does without being vague or tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for checking the current server version, but does not explicitly state when to use this tool versus alternatives (e.g., 'read_latest_mcp_server_version' for a different version type) or provide any exclusions. It offers basic context but lacks explicit guidance on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 value by specifying that it returns the 'latest' version, which is behavioral context not covered by annotations. It does not contradict annotations, and while it doesn't detail rate limits or auth needs, it provides useful additional information about the version scope.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the key information ('Returns the latest version') with zero waste. Every word earns its place, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, 100% schema coverage, annotations with readOnlyHint, and an output schema exists, the description is complete enough. It clearly states the purpose and scope ('latest version'), and with the output schema handling return values, no additional details are needed for this simple read operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are 0 parameters, and schema description coverage is 100%, so no parameter information is needed. The description does not add parameter semantics, but with no parameters, a baseline of 4 is appropriate as it adequately describes the tool's function without unnecessary details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Returns') and resource ('latest version of the QC MCP Server'), distinguishing it from the sibling tool 'read_mcp_server_version' which likely returns a different version (e.g., current or specific). The verb 'Returns' is precise and the scope 'latest version' is well-defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'latest version,' suggesting it should be used when the most recent version is needed, but it does not explicitly state when to use it versus alternatives like 'read_mcp_server_version' or provide exclusions. The context is clear but lacks explicit guidance on sibling tool differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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