IDA Pro MCP

by icryo

Overview Schema Related Servers Score Discussions

Python

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Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.6.0
Disambiguation3/5
The tool set has clear distinctions in many areas, such as separate tools for reading different data types (data_read_byte, data_read_word, etc.) and distinct operations like add_comment vs. delete_comment. However, there is notable overlap between tools like get_struct_info_simple and analyze_struct_detailed, and between get_global_variable_value_at_address and the data_read_* functions, which could cause confusion despite descriptions guiding usage.
Naming Consistency4/5
Most tools follow a consistent verb_noun pattern (e.g., add_comment, get_function_by_address, list_functions), with clear and descriptive names. There are minor deviations, such as analyze_struct_detailed (verb_adjective_noun) and execute_script (verb_noun), but overall the naming is predictable and readable across the set.
Tool Count2/5
With 56 tools, the count is excessive for typical MCP server purposes, making it heavy and potentially overwhelming. While IDA Pro is a complex tool, this many tools suggests poor scoping, as many could be consolidated (e.g., multiple data_read_* tools into a single parameterized tool) without losing functionality.
Completeness5/5
The tool set provides comprehensive coverage for reverse engineering tasks in IDA Pro, including analysis (decompile_function, disassemble_function), data manipulation (read/write memory, rename variables), structure handling, and scripting. It supports full CRUD operations for comments, variables, and types, with no obvious gaps for the domain, ensuring agents can perform complex workflows without dead ends.
Average 3.1/5 across 56 of 56 tools scored. Lowest: 1/5.
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 status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
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?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states it's a 'simple function' to 'get' information, implying a read-only operation, but doesn't specify what 'basic structure information' includes, whether it requires permissions, has side effects, or how it behaves (e.g., error handling, return format). This is inadequate for a tool with no 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's appropriately sized for a simple tool, though it could be more informative. The structure is straightforward, making it easy to parse, but it lacks depth that might justify more content.
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 no annotations and no output schema, the description is incomplete for a tool that likely returns data. It doesn't explain what 'basic structure information' entails, such as fields or metadata, leaving the agent uncertain about the tool's output. For a read operation with minimal structured data, this gap reduces usability.
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 100% description coverage, with the single parameter 'name' documented as 'Name of the structure'. The description adds no additional meaning beyond this, such as format examples or constraints. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't need to given the schema's completeness.
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 'Simple function to get basic structure information' restates the tool name 'get_struct_info_simple' without adding specificity. It uses the verb 'get' and resource 'structure information' but doesn't clarify what 'basic' means or distinguish it from sibling tools like 'get_struct_at_address' or 'get_defined_structures'. This is borderline tautological with minimal added value.
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 any context, prerequisites, or exclusions, nor does it reference sibling tools like 'analyze_struct_detailed' or 'get_struct_at_address' that might serve similar purposes. This leaves the agent with no usage direction.
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?
No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions 'detailed analysis' but doesn't explain what this analysis returns, whether it's read-only or has side effects, performance characteristics, or error conditions. This leaves significant behavioral gaps for a tool that presumably provides complex output.
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, efficient sentence that gets straight to the point without unnecessary words. It's appropriately sized for a single-parameter tool, though it could be more specific about what 'analysis' entails.
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 named 'analyze_struct_detailed' with no annotations and no output schema, the description is insufficient. It doesn't explain what constitutes 'detailed analysis' or what information is returned, leaving the agent guessing about the tool's capabilities and output format given the complexity implied by the name.
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 100% with one parameter ('name' of structure to analyze), so the schema already documents the parameter adequately. The description adds no additional parameter semantics beyond what's in the schema, meeting the baseline for high schema 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 'Detailed analysis of a structure with all fields' states the general purpose (analyzing a structure) but is vague about what 'analysis' entails and doesn't distinguish it from sibling tools like 'get_struct_info_simple' or 'get_struct_at_address'. It specifies 'with all fields' which adds some specificity, but doesn't clarify what type of analysis is performed.
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 'get_struct_info_simple' or 'get_struct_at_address'. The description doesn't mention prerequisites, context, or exclusions, leaving the agent with no usage guidelines beyond the basic purpose statement.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('set') which implies a mutation, but doesn't describe effects (e.g., whether changes are reversible, if it updates decompilation views, or requires specific permissions). No rate limits, side effects, or response format are mentioned, leaving significant gaps for a mutation tool.
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, efficient sentence with no wasted words, making it easy to parse. However, it's front-loaded with the core action but lacks additional context that could enhance usability, slightly limiting its effectiveness.
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 (a mutation with 3 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like side effects, error conditions, or return values, which are critical for safe and effective use in a decompilation/analysis context.
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 100%, so the input schema fully documents all three parameters (function_address, variable_name, new_type). The description doesn't add any meaning beyond what the schema provides—it doesn't explain parameter relationships, format details, or constraints. Baseline 3 is appropriate as 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 'Set a local variable's type' clearly states the action (set) and target (local variable's type), but it's somewhat vague about what 'type' means in this context and doesn't differentiate from sibling tools like 'set_global_variable_type' or 'set_stack_frame_variable_type'. It avoids tautology but lacks specificity about the domain (decompilation/analysis).
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 'set_global_variable_type' or 'set_stack_frame_variable_type'. The description doesn't mention prerequisites, context (e.g., after decompilation), or exclusions, leaving the agent to infer usage from the tool name and parameters alone.
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?
No annotations are provided, so the description carries full burden. It states the tool retrieves variables but does not disclose behavioral traits such as permissions needed, rate limits, whether it's read-only or mutative, or what happens if the function address is invalid. This leaves significant gaps for an agent to understand how to invoke it safely.
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, efficient sentence with no wasted words. It is front-loaded with the core action and target, making it easy to parse. However, it could be slightly more structured by including key usage notes, but it remains appropriately concise.
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 one parameter with full schema coverage and an output schema exists, the description is minimally complete. However, as a tool with no annotations and in a context with many sibling tools, it lacks guidance on usage and behavioral context, which reduces completeness for effective agent 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 100%, with the parameter 'function_address' well-documented in the schema. The description adds no additional meaning beyond implying it retrieves variables for a 'given function', which aligns with the schema. Baseline score of 3 is appropriate as the schema handles parameter documentation adequately.
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 action ('Retrieve') and target ('stack frame variables for a given function'), which clarifies the tool's purpose. However, it does not differentiate from sibling tools like 'get_global_variable_value_at_address' or 'get_local_variable_type', leaving ambiguity about scope. The description is clear but lacks 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 does not mention prerequisites (e.g., needing a disassembled function) or contrast with tools like 'get_global_variable_value_by_name' or 'list_functions'. The description offers no usage context or exclusions.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Set' implies a mutation operation, but the description does not specify whether this change is reversible, requires specific permissions, affects other parts of the system, or has side effects (e.g., breaking existing calls). It lacks details on error conditions, rate limits, or response format, leaving significant gaps in understanding 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, direct sentence with zero wasted words. It is front-loaded and efficiently conveys the core action without unnecessary elaboration, making it easy to parse quickly. This is an example of optimal conciseness for a simple tool.
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 of a mutation tool with no annotations and no output schema, the description is incomplete. It does not explain what a prototype is, what the tool returns, potential errors, or how it interacts with other tools (e.g., 'get_function_by_address'). For a tool that modifies function data, more context is needed to ensure safe and correct usage by an 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 100% description coverage, with clear titles and descriptions for both parameters ('function_address' and 'prototype'). The description does not add any meaning beyond the schema, such as explaining the format of the address or prototype syntax. Since the schema is well-documented, a baseline score of 3 is appropriate, as the description does not compensate but also does not detract.
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 'Set a function's prototype' clearly states the action (set) and target (function prototype), which is adequate. However, it lacks specificity about what a 'prototype' entails in this context (e.g., function signature, parameters, return type) and does not distinguish this tool from potential siblings like 'rename_function' or 'set_global_variable_type', which also modify function-related data. It avoids tautology but remains vague.
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 (e.g., needing a valid function address), exclusions, or related tools like 'get_function_by_address' for verification. Without such context, an agent must infer usage from the tool name alone, which is insufficient for effective selection.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Set' implies a mutation, but the description doesn't specify whether this requires specific permissions, if the change is reversible, what happens to existing data, or any side effects (e.g., validation, error handling). For a mutation tool with zero annotation coverage, this leaves critical behavioral traits undocumented.
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 front-loaded with the core action and resource, making it easy to parse quickly. Every word contributes directly to stating the tool's purpose, achieving optimal conciseness for such a simple operation.
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 of a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., permissions, side effects), usage guidelines, and what the tool returns. While the schema covers parameters well, the overall context for safe and correct invocation is insufficient, especially compared to sibling tools that might handle similar operations.
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 100%, with clear descriptions for both parameters ('variable_name' and 'new_type'). The description adds no additional semantic context beyond what the schema provides, such as examples of valid types or naming conventions. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema adequately documents the parameters without extra help from 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 'Set a global variable's type' clearly states the action (set) and resource (global variable's type), making the purpose understandable. However, it's somewhat vague about what 'type' means in this context (e.g., data type, classification) and doesn't distinguish this tool from sibling tools like 'set_local_variable_type' or 'set_stack_frame_variable_type', which perform similar operations on different variable scopes.
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., whether the variable must exist), exclusions, or compare it to similar tools like 'set_local_variable_type' or 'rename_global_variable'. Without such context, an agent might struggle to choose the correct tool for modifying global variable properties.
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?
With no annotations provided, the description carries full burden but only states the action without disclosing behavioral traits such as read-only vs. mutative nature, error handling, permissions needed, or rate limits. It lacks details on what 'get' returns or any operational constraints.
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, front-loaded and appropriately sized for a simple tool. It avoids redundancy and is structurally sound.
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, 100% schema coverage, and presence of an output schema, the description is minimally adequate. However, it lacks context on usage scenarios or behavioral details, making it incomplete for optimal agent understanding without additional structured data.
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 100%, so the schema already documents the 'address' parameter. The description adds no meaning beyond the schema, such as address format or examples. Baseline 3 is appropriate as the schema handles parameter documentation adequately.
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 'Get a function by its address' states the verb and resource clearly but is vague about what 'get' entails (e.g., retrieving metadata, code, or details). It distinguishes from siblings like 'get_function_by_name' by specifying 'address' but lacks specificity on the function's scope or output.
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 'get_function_by_name' or 'get_current_function'. The description implies usage for functions identified by address but offers no context on prerequisites, exclusions, or comparisons with sibling tools.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Get a function by its name', which implies a read-only operation, but doesn't clarify if it returns detailed metadata, code, or a simple reference; whether it requires specific permissions; or how it handles missing functions. This leaves significant gaps in understanding the tool's behavior 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 extremely concise—a single sentence with no wasted words. It's front-loaded and directly states the tool's purpose, making it easy to parse quickly. However, this conciseness comes at the cost of completeness, as noted in other dimensions.
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 likely defines return values), the description doesn't need to explain outputs. However, with no annotations and a simple but potentially ambiguous purpose (e.g., what does 'get' return?), the description is minimally adequate. It covers the basic action but lacks depth for a tool that might interact with complex function data in a debugging or analysis context.
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 100% description coverage, with the 'name' parameter clearly documented. The description adds no additional meaning beyond what the schema provides, such as format constraints or examples. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
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 'Get a function by its name' clearly states the action (get) and resource (function), but it's vague about what 'get' entails—does it return metadata, code, or something else? It distinguishes from siblings like 'get_function_by_address' by specifying 'by name', but doesn't explain the difference in usage or output compared to similar tools.
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 'get_function_by_address', 'list_functions', or 'get_current_function'. The description implies it's for retrieving a specific function by name, but doesn't specify prerequisites, error conditions, or typical use cases, leaving the agent to infer context from sibling names alone.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While it describes what the tool does (adding comments with different types), it lacks critical behavioral details: whether this operation is destructive (e.g., overwrites existing comments), requires specific permissions, has side effects, or how errors are handled. For a mutation tool with zero annotation coverage, this is a significant gap.
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 well-structured and efficient: it starts with the core purpose in one sentence, then lists comment types with brief explanations. Each sentence adds value without redundancy. It could be slightly more front-loaded by mentioning the comment_type parameter upfront, but overall it's concise and clear.
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 (adding comments with types), no annotations, and no output schema, the description is partially complete. It covers the basic purpose and parameter semantics but lacks behavioral transparency (e.g., mutation effects, error handling) and usage guidelines. For a tool that modifies data without safety annotations, more context on risks or outcomes 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 100%, so the schema already documents all three parameters (address, comment, comment_type) with descriptions and defaults. The description adds some value by listing and briefly explaining the comment_type options (e.g., 'regular', 'repeatable'), which clarifies their semantics beyond the schema's enum-like list. However, it doesn't provide additional syntax or format details for parameters, so it meets the baseline for high schema 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: 'Add a comment at the specified address.' It specifies the verb ('Add') and resource ('comment'), and the list of comment types provides additional specificity. However, it doesn't explicitly distinguish this tool from sibling tools like 'set_comment' or 'delete_comment' in terms of when to use each, 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 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 'set_comment' or 'delete_comment' from the sibling list. It lists comment types but doesn't explain when to choose one type over another or any prerequisites (e.g., whether the address must be valid or within a specific context). This lack of contextual guidance limits its utility for an AI agent.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('create') but doesn't clarify if this is a destructive mutation, what permissions are required, whether it overwrites existing variables, or what happens on success/failure. For a mutation tool with zero annotation coverage, this leaves 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately front-loaded with the core action, though it could be slightly more structured (e.g., by explicitly listing parameters).
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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, or side effects, which are critical for an agent to use it correctly in a low-level debugging context with sibling tools like 'delete_stack_frame_variable'.
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 100%, with each parameter clearly documented in the schema. The description adds minimal value beyond the schema by mentioning 'offset' and 'type' but doesn't provide additional context like format examples or constraints. This meets the baseline of 3 when the schema does the heavy lifting.
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 stack variable') and specifies the target context ('for a given function'), which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'rename_stack_frame_variable' or 'set_stack_frame_variable_type', which handle similar stack frame variable operations but with different purposes.
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., whether the function must be disassembled first), exclusions, or comparisons to related tools like 'delete_stack_frame_variable' or 'get_stack_frame_variables', leaving the agent to infer usage context.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'Create or update' but doesn't specify permissions needed, whether changes are reversible, side effects (e.g., if it affects other analyses), or error handling. For a mutation tool with zero annotation coverage, this is a significant gap in 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, efficient sentence with zero waste—it directly states the tool's purpose without redundancy. It is appropriately sized and front-loaded, making it easy to parse 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 (a mutation operation with no annotations and no output schema), the description is incomplete. It doesn't explain what 'local type' entails, how the tool behaves on success or failure, or what the user can expect after invocation. For a tool that modifies data in a technical context, more detail is needed to be fully helpful.
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 100%, so the input schema already documents the single parameter 'c_declaration' with examples. The description adds no additional meaning beyond what the schema provides, such as syntax rules or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.
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 or update') and resource ('a local type from a C declaration'), making the purpose evident. It distinguishes itself from siblings like 'set_local_variable_type' or 'get_defined_structures' by focusing on C declarations. However, it doesn't specify what 'local type' means in this context (e.g., in a decompiler or debugger), 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 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. For example, it doesn't clarify if this is for reverse engineering, debugging, or code analysis contexts, or how it differs from sibling tools like 'set_local_variable_type' or 'get_defined_structures'. The description lacks any 'when' or 'when not' instructions, leaving usage ambiguous.
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?
With no annotations, the description carries full burden but provides limited behavioral insight. It mentions that deleting 'anterior/posterior' types deletes all lines, which is useful context, but lacks details on permissions, reversibility, error conditions, or what happens to the data. For a destructive operation, this is insufficient.
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 two sentences that directly convey core information without fluff. It's front-loaded with the main action and efficiently adds a behavioral note.
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 tool with no annotations and no output schema, the description is incomplete. It lacks critical details like success/error responses, side effects beyond line deletion, or dependencies. The context signals indicate moderate complexity (2 params), but the description doesn't adequately compensate for missing structured data.
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 100%, so the schema fully documents parameters. The description adds minimal value by implying 'address' targets a comment and hinting at 'comment_type' effects for 'anterior/posterior', but doesn't elaborate beyond schema details. Baseline 3 is appropriate given high schema 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 action ('Delete') and target ('a comment at the specified address'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'set_comment' or 'get_comments' beyond the verb 'delete'.
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 behavior for 'anterior/posterior' types but doesn't explain when to choose this over other comment-related tools or prerequisites for deletion.
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?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states the action is deletion but lacks critical details: whether this is destructive (likely yes, but not confirmed), if it requires specific permissions, what happens on success/failure (e.g., error if variable doesn't exist), or side effects. The description is minimal and doesn't compensate for the absence of 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 a single, straightforward sentence with no wasted words, making it efficient and easy to parse. It's front-loaded with the key action ('Delete'). However, it could be slightly more structured by including context or usage hints, but it remains appropriately concise for its 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?
Given the complexity of a deletion tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'delete' entails operationally, potential errors, or return values. For a tool that likely modifies state, more behavioral context is needed to guide safe and correct usage, making this inadequate despite the clear schema.
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 100%, with both parameters ('function_address' and 'variable_name') well-documented in the schema. The description adds no additional meaning beyond the schema, such as format examples or constraints. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't enhance parameter understanding but also doesn't detract.
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 target ('named stack variable for a given function'), making the purpose understandable. It distinguishes from siblings like 'create_stack_frame_variable' and 'rename_stack_frame_variable' by specifying deletion, though it doesn't explicitly contrast with them. The description is specific but could be more precise about what 'delete' entails 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., whether the variable must exist), exclusions, or related tools like 'get_stack_frame_variables' for checking variables first. Usage is implied only by the action name, leaving the agent to infer context from sibling tool names without explicit direction.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action ('returns a list') without detailing aspects like whether the list is paginated, sorted, or includes metadata, what happens if no structures exist, or any performance considerations. This leaves significant gaps for a tool that likely interacts with a complex system (e.g., reverse engineering).
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, efficient sentence with no wasted words. It is front-loaded with the core action, making it easy to parse. However, it could be slightly more informative without losing conciseness, such as by adding a brief context hint.
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 0 parameters, 100% schema coverage, and an output schema exists, the description does not need to detail inputs or return values. However, for a tool in a complex domain (implied by sibling tools like disassembly and analysis functions), the description lacks context on what 'defined structures' entails and behavioral traits, making it minimally adequate but with clear gaps in completeness.
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 tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description does not need to add parameter semantics, as there are none to explain. A baseline score of 4 is appropriate since no parameters exist, and the description does not mislead about 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 states the tool's purpose as 'Returns a list of all defined structures,' which is clear but vague. It specifies the verb ('returns') and resource ('defined structures'), but does not differentiate from sibling tools like 'search_structures' or 'get_struct_at_address,' nor does it clarify what 'defined structures' means in this context (e.g., user-defined vs. all structures).
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 sibling tools like 'search_structures' and 'get_struct_at_address,' there is no indication of whether this tool is for listing all structures without filtering, making it unclear when to prefer it over other options.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Get' implies a read operation, the description doesn't address important behavioral aspects like whether this requires specific permissions, what happens if the address or structure name is invalid, whether memory is accessed, or what format the returned values take. This leaves significant gaps for a tool that presumably reads memory or analysis data.
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 gets straight to the point with zero wasted words. It's appropriately sized for a tool with two parameters and follows a clear subject-verb-object structure.
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 presumably reads memory or analysis data at an address (with no output schema and no annotations), the description is insufficient. It doesn't explain what 'structure field values' means in practice, what format they're returned in, whether this is a memory read operation or analysis of existing data, or what happens with invalid inputs. Given the complexity implied by the tool name and the lack of structured metadata, more context is needed.
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 100%, with both parameters clearly documented in the schema. The description adds minimal value beyond what's already in the schema - it mentions 'address' and 'structure' but doesn't provide additional context about parameter relationships, valid formats, or usage examples. The baseline of 3 is appropriate when the schema does the heavy lifting.
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 structure field values') and target ('at a specific address'), which is a specific verb+resource combination. However, it doesn't differentiate itself from sibling tools like 'get_struct_info_simple' or 'analyze_struct_detailed', which might provide similar or overlapping functionality with structures.
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 multiple structure-related tools in the sibling list (get_struct_info_simple, analyze_struct_detailed, search_structures), there's no indication of what makes this tool distinct or when it's the appropriate choice.
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?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Rename a function' implies a mutation operation, but the description doesn't specify whether this requires specific permissions, whether the rename is reversible, what happens to existing references, or if there are constraints on the new name. For a mutation tool with zero annotation coverage, this is a significant gap in behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, immediately conveying the core purpose without unnecessary elaboration.
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 mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns (success/failure, error conditions), behavioral implications (e.g., whether renaming affects disassembly or decompilation), or integration with sibling tools. The agent lacks critical context for safe and effective 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 100%, with both parameters ('function_address' and 'new_name') clearly documented in the schema. The description adds no additional parameter semantics beyond what's already in the schema (e.g., format of addresses, naming conventions, or implications of empty 'new_name'). Baseline 3 is appropriate when the schema does the heavy lifting.
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 'Rename a function' clearly states the action (rename) and target resource (function), providing a specific verb+resource combination. However, it doesn't differentiate this tool from sibling renaming tools like 'rename_global_variable', 'rename_local_variable', or 'rename_stack_frame_variable', which all follow the same pattern for different resource types.
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 (e.g., needing an existing function), exclusions, or comparison with similar tools like 'set_function_prototype' which might also affect function naming. 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Rename a global variable' implies a mutation operation but provides no information about permissions required, whether the rename affects existing references, error conditions, or what happens if the new_name is empty (despite the schema hinting at default behavior). The description lacks critical behavioral context for a mutation tool.
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 that directly states the tool's purpose without any wasted words. It's front-loaded and gets straight to the point, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens after renaming, whether the operation is reversible, what permissions are needed, or how it interacts with sibling renaming tools. The 100% schema coverage helps with parameters, but the overall context for using this tool remains inadequate.
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 100%, so the schema already documents both parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema. The baseline score of 3 reflects adequate coverage through the schema alone, though the description contributes nothing extra.
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 ('Rename') and resource ('global variable'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like rename_function, rename_local_variable, or rename_stack_frame_variable, which all perform similar renaming operations on different resource types.
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 about when to use this tool versus alternatives. There are multiple renaming tools in the sibling list (rename_function, rename_local_variable, rename_stack_frame_variable), but the description doesn't explain that this one specifically handles global variables rather than functions, local variables, or stack frame variables.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool renames a local variable but doesn't mention side effects (e.g., whether it updates references in the decompiled code), permission requirements, error conditions, or what happens if the new_name is empty (as hinted in the schema). This leaves significant gaps for a mutation tool.
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 purpose with zero wasted words. It's appropriately sized and front-loaded, making it easy to parse 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?
For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like side effects, error handling, or return values, which are critical for safe and effective use. The high schema coverage helps with parameters, but overall context is lacking.
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 100%, so the schema already documents all three parameters thoroughly. The description adds no additional meaning beyond what's in the schema (e.g., it doesn't clarify what 'function_address' format is or explain the 'empty for a default name' behavior for new_name). Baseline 3 is appropriate when the schema does the heavy lifting.
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 ('rename') and target ('a local variable in a function'), which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like rename_global_variable or rename_stack_frame_variable, which perform similar operations on different variable types.
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 rename_global_variable or rename_stack_frame_variable. The description lacks context about prerequisites (e.g., whether the function must be decompiled first) or typical scenarios for renaming local variables.
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?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the action is a 'change' (implying mutation) but doesn't disclose permissions needed, whether changes are reversible, effects on related data, or error conditions. This is inadequate for a mutation tool with zero 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, efficient sentence with no wasted words. It front-loads the core action and target, making it easy to parse quickly, though it lacks depth due to its brevity.
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 mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what happens on success/failure, return values, or side effects. Given the complexity of modifying stack frame variables in a disassembly context, more behavioral context is needed.
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 100%, so parameters are well-documented in the schema. The description adds no additional meaning beyond implying the tool operates on stack variables, which is already clear from the tool name and parameter descriptions. This meets the baseline for high schema 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 action ('Change the name') and target ('stack variable for an IDA function'), making the purpose understandable. However, it doesn't differentiate from sibling tools like rename_function, rename_global_variable, or rename_local_variable, which all perform similar renaming operations on different entities.
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 (e.g., needing an existing stack variable), exclusions, or comparisons to similar tools like rename_local_variable or delete_stack_frame_variable, 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the action ('Set a comment') but fails to clarify whether this overwrites existing comments, requires specific permissions, or has side effects. For a mutation tool with zero annotation coverage, this is a significant gap in 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, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., overwrite behavior, permissions), usage context, and expected outcomes. The high schema coverage helps with parameters, but overall completeness is inadequate for a tool that modifies data.
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 schema description coverage is 100%, with both parameters ('address' and 'comment') well-documented in the schema. The description adds no additional meaning beyond what the schema provides, such as format details or constraints. Baseline 3 is appropriate when the schema handles parameter documentation adequately.
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 ('Set a comment') and the target ('for a given address in the function disassembly and pseudocode'), making the purpose unambiguous. It distinguishes itself from sibling tools like 'add_comment' and 'delete_comment' by specifying the 'set' action, though it doesn't explicitly contrast with them.
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 'add_comment' or 'delete_comment', nor does it mention any prerequisites or contextual constraints. It simply states what the tool does without indicating appropriate scenarios.
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?
No annotations are provided, so the description carries full burden. It implies a mutation ('set'), but doesn't disclose behavioral traits like whether changes are reversible, if it requires specific permissions, or what happens on failure (e.g., invalid type). This is inadequate for a mutation tool with zero 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, efficient sentence with zero waste. It's front-loaded with the core purpose and appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavior, error handling, or return values, which are critical for an agent to use it correctly. The high schema coverage doesn't 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 100%, so the schema already documents all three parameters. The description adds no additional meaning beyond what's in the schema, such as format examples or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.
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 ('set the type') and target ('stack variable'), specifying it's for a 'disassembled function'. It distinguishes from siblings like 'set_global_variable_type' and 'set_local_variable_type' by focusing on stack variables, but doesn't explicitly contrast with 'create_stack_frame_variable' or 'delete_stack_frame_variable'.
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 like 'create_stack_frame_variable' or 'rename_stack_frame_variable'. It mentions the context ('disassembled function') but doesn't specify prerequisites, such as whether the function must be analyzed or the variable must exist.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves metadata but doesn't specify what kind of metadata (e.g., IDB version, analysis status, file info), whether it's read-only or has side effects, or any performance considerations. This leaves significant gaps for an agent to understand 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, efficient sentence with no wasted words. It's front-loaded and directly states the tool's purpose without unnecessary elaboration, making it 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 0 parameters, 100% schema coverage, and an output schema exists, the description is minimally adequate. However, it lacks details on what metadata is returned (though the output schema may cover this) and doesn't provide context to distinguish it from sibling tools, leaving room for improvement in a complex server environment.
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 tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter semantics, so it meets the baseline expectation. No additional value is required here.
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 'Get metadata about the current IDB', which is a clear verb+resource combination. However, it doesn't differentiate from sibling tools like 'get_struct_info_simple' or 'get_defined_structures' that might also retrieve metadata-like information. The purpose is understandable but generic.
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 many sibling tools that could retrieve metadata (e.g., 'get_struct_info_simple', 'get_defined_structures'), there's no indication of what specific metadata this tool provides or when it's the appropriate choice. Usage is implied only by the name.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('decompile') but doesn't explain what decompilation entails (e.g., output format, whether it's read-only or modifies state, potential side effects, or performance implications). This is a significant gap for a tool that likely involves complex analysis.
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 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's complexity (decompilation is non-trivial), no annotations, and an output schema (which should cover return values), the description is minimally adequate. It states what the tool does but lacks details on behavior, usage context, or error handling, leaving gaps for an agent to operate 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?
The description adds minimal meaning beyond the input schema, which has 100% coverage for the single parameter 'address'. It clarifies that the address is for 'the function to decompile', but this is already implied by the schema's description. Baseline 3 is appropriate as the schema does the heavy lifting.
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 ('decompile') and resource ('a function at the given address'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'disassemble_function' or 'get_function_by_address', which might handle similar concepts 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?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites, context (e.g., after analysis), 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but lacks details on behavior such as output format, pagination, error handling, or performance considerations (e.g., rate limits). For a read operation with no annotations, this leaves significant gaps in understanding how the tool behaves beyond its basic function.
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 front-loads the key information ('Get all callers') and directly specifies the input ('of the given address'), making it easy to parse quickly. Every part of the sentence contributes to understanding the tool's purpose.
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 covers return values), 1 parameter with full schema coverage, and no annotations, the description is minimally adequate. It states the purpose but lacks behavioral details and usage context. For a simple read tool, it meets basic needs but doesn't provide enough information for optimal agent use without relying heavily on structured fields.
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 schema description coverage is 100%, with the parameter 'function_address' well-documented in the schema. The description adds no additional semantic context beyond implying it's the address to query for callers. Since the schema handles parameter documentation adequately, the baseline score of 3 is appropriate, as the description doesn't enhance or clarify parameter meaning further.
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 all callers') and the target resource ('of the given address'), making the purpose understandable. It distinguishes from siblings like 'get_callees' by focusing on callers rather than callees, though it doesn't explicitly mention this distinction. However, it lacks specificity about what 'callers' means in this context (e.g., functions calling the given 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?
No guidance is provided on when to use this tool versus alternatives. While it's clear this is for retrieving callers of a function address, there's no mention of prerequisites, when not to use it, or how it differs from similar tools like 'get_xrefs_to' (which might provide cross-references). The description assumes context without explicit usage instructions.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves cross references but doesn't describe what 'cross references' entail (e.g., code/data references, directionality), output format, pagination, or error handling. This leaves significant gaps for a tool that likely queries a complex system like a disassembler or debugger.
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 front-loads the core purpose ('Get all cross references') and is appropriately sized for a simple query tool, 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 has an output schema (which should define return values) and high schema coverage for its single parameter, the description is minimally adequate. However, without annotations and with many sibling tools in a complex domain (e.g., reverse engineering), it lacks context on behavior, limitations, and differentiation, leaving room for improvement.
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 100%, with the parameter 'address' clearly documented in the schema. The description adds minimal value by mentioning 'given address' but doesn't elaborate on address format (e.g., hex, virtual address), validation, or examples beyond what the schema provides, meeting the baseline for high schema 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 action ('Get') and target resource ('cross references'), specifying the input ('given address'). It distinguishes from sibling 'get_xrefs_to_field' by focusing on address-level cross-references rather than field-level, though it doesn't explicitly mention this 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 like 'get_callees', 'get_callers', or 'get_xrefs_to_field'. The description lacks context about prerequisites, typical use cases, 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the action ('Get all cross references') but lacks behavioral details such as output format, performance characteristics, error conditions, or whether it's read-only or has side effects. For a tool with no annotations, this is insufficient.
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 purpose without unnecessary words. It directly communicates the tool's function in a compact form, earning its place.
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), 100% parameter schema coverage, and no annotations, the description is minimally adequate. However, it lacks context about usage scenarios, behavioral traits, or integration with sibling tools, leaving gaps for an agent to fully understand when and how 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?
Schema description coverage is 100%, with both parameters clearly documented in the schema. The description adds minimal value by implying the parameters identify a struct field, but doesn't provide additional semantics beyond what the schema already specifies. Baseline 3 is appropriate given high schema 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 verb ('Get') and resource ('all cross references to a named struct field'), specifying it retrieves references to a struct member. It distinguishes from sibling 'get_xrefs_to' by focusing on field-level references rather than general cross-references, though it doesn't explicitly name the sibling for 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?
No guidance is provided on when to use this tool versus alternatives like 'get_xrefs_to' or other analysis tools. The description implies usage for struct field analysis but lacks explicit context, prerequisites, or exclusion criteria.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions pagination and filtering, but lacks details on permissions, rate limits, error handling, or what 'matching' entails beyond the filter parameter. This is inadequate for a tool with database access and multiple parameters.
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 purpose ('List matching functions in the database') and appends key behavioral traits ('paginated, filtered') without any wasted words. It's appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 100% schema coverage for inputs, the description's gaps in behavioral transparency and usage guidelines are partially mitigated. However, for a database query tool with no annotations, more context on safety and constraints 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 100%, so the schema fully documents parameters like offset, count, and filter with their types and descriptions. The description adds no additional parameter semantics beyond what's in the schema, meeting the baseline for high 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 action ('List matching functions') and resource ('in the database'), with additional context about pagination and filtering. However, it doesn't explicitly differentiate from its sibling 'list_functions' (which likely lacks filtering), missing full sibling distinction 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?
No guidance is provided on when to use this tool versus alternatives like 'list_functions' or 'get_function_by_name'. The description mentions filtering but doesn't specify scenarios or exclusions, leaving usage context implied at best.
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?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions pagination, which is helpful, but doesn't describe authentication requirements, rate limits, error conditions, or what 'globals' actually represent in this database context. For a tool with no annotation coverage, this leaves 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence that communicates the core functionality and pagination behavior. Every word earns its place with no wasted text.
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 100% schema description coverage, the description provides adequate but minimal context. However, for a tool with no annotations and in a complex sibling environment with filtering alternatives, it could do more to help an agent understand when and 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 100%, so the schema already fully documents both parameters (offset and count). The description doesn't add any parameter-specific information beyond what's in the schema. This meets the baseline expectation when schema coverage is complete.
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 all globals') and resource ('in the database'), and specifies pagination behavior. However, it doesn't differentiate from sibling 'list_globals_filter' tool, which appears to offer filtered listing capabilities.
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 existence of 'list_globals_filter' suggests there are filtering options available, but the description doesn't indicate when to choose this unfiltered listing tool over the filtered version or other related tools.
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?
With no annotations provided, the description carries full burden but only states the basic action. It doesn't disclose behavioral traits such as whether this is a read-only operation, if it requires specific permissions, what format the output takes, or any limitations like pagination 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 purpose without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'Local types' are in this context, what the output format looks like, or any prerequisites, leaving significant gaps for an AI agent to understand and use the tool effectively.
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, but it also doesn't compensate for any gaps since there are none, warranting a baseline score above 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 action ('List all') and resource ('Local types in the database'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'list_functions' or 'list_globals' by explaining what distinguishes 'Local types' from other listable entities.
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. Given sibling tools like 'list_functions' and 'list_globals', the description lacks context on whether this is for debugging, analysis, or other scenarios, leaving usage unclear.
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?
No annotations are provided, so the description carries the full burden. It mentions the search is 'by name pattern' but lacks details on behavioral traits such as permissions needed, rate limits, output format, or whether it's read-only or destructive. This leaves significant gaps for an agent to understand how to use it effectively.
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 front-loads the key information ('search for structures') and is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 and high input schema coverage, the description is somewhat complete but lacks behavioral context. Without annotations, it should ideally cover more about the tool's operation, such as return values or usage scenarios, to fully guide an 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?
Schema description coverage is 100%, with the parameter 'filter' documented as a case-insensitive pattern. The description adds minimal value beyond the schema by specifying 'by name pattern', but it doesn't provide additional context like examples or constraints. Baseline 3 is appropriate given the high schema 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 action ('search for structures') and resource ('structures'), with specificity about the search criterion ('by name pattern'). It distinguishes from some siblings like 'get_defined_structures' or 'get_struct_at_address' by implying a pattern-based search, though it doesn't explicitly differentiate from all relevant siblings.
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 explicit guidance on when to use this tool versus alternatives is provided. The description implies usage for searching structures by name pattern, but it doesn't specify contexts, prerequisites, or exclusions compared to siblings like 'get_defined_structures' or 'list_functions_filter'.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool checks if the plugin is running, but does not explain what 'running' means (e.g., active connection, loaded state), what happens if it's not running (e.g., error response, timeout), or any performance considerations like latency. This leaves gaps in understanding 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: 'Check if the IDA plugin is running'. It is front-loaded with the core action and resource, with no unnecessary words or redundant information. This makes 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 that the tool has 0 parameters, 100% schema coverage, and an output schema exists (which likely handles return values), the description is minimally complete. However, it lacks details on behavioral aspects like error handling or operational context, which could be important for a connection-checking tool in a debugging environment. It meets basic needs but has room for improvement.
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 tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description does not need to add parameter semantics, as there are none to document. A baseline score of 4 is appropriate for a parameterless tool, as the description's focus is on purpose rather than 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 tool's purpose: 'Check if the IDA plugin is running'. It specifies the verb ('Check') and the resource ('IDA plugin'), making it easy to understand what the tool does. However, it does not explicitly differentiate itself from sibling tools, though its purpose is distinct enough in 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 does not mention prerequisites, such as needing the plugin to be installed, or suggest other tools for related tasks like troubleshooting connection issues. 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions conversion between representations but doesn't disclose behavioral traits like what formats are supported beyond decimal/hex, whether the conversion is bidirectional, error handling, or performance characteristics. The description is minimal and lacks 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 a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, clearly stating the core functionality without unnecessary elaboration.
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 simple conversion purpose, 100% schema coverage, and the presence of an output schema (which handles return values), the description is reasonably complete. However, it could benefit from more behavioral context since no annotations are provided.
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 100%, so the schema already documents both parameters (text and size). The description adds no additional meaning about parameters beyond implying number conversion, which aligns with the schema. Baseline 3 is appropriate when schema does the heavy lifting.
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: converting numbers between different representations (decimal, hexadecimal). It specifies the verb 'convert' and the resource 'number', but doesn't distinguish from siblings since no other conversion tools are listed 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 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 use, or comparison with other tools that might handle similar data transformations.
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?
No annotations are provided, so the description carries full burden. It states the tool retrieves the 'currently selected' address, implying it's a read-only operation dependent on user state, but doesn't disclose behavioral traits like what happens if no address is selected (error, null return), whether it requires specific permissions, or rate limits. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 directly states the tool's function with zero wasted words. It's front-loaded with the core purpose ('Get the address'), 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.
Completeness3/5
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, and an output schema exists, the description is minimally complete. However, as a tool with no annotations, it lacks context about error conditions, dependencies on user state, or return format details that the output schema might cover. For a simple read operation, it's adequate but leaves behavioral questions unanswered.
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 semantics (none exist), which is appropriate. Baseline is 4 for 0 parameters, as the description correctly avoids unnecessary parameter 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 tool's purpose with a specific verb ('Get') and resource ('address currently selected by the user'). It distinguishes from siblings by focusing on the current user selection rather than functions, structures, or other data types. However, it doesn't explicitly differentiate from potential address-related siblings (none exist in the provided list).
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 user to have selected an address first), exclusions, or related tools for other address-related operations. The sibling list shows no direct alternatives, but context signals suggest this is part of a reverse engineering/debugging toolset where address selection is a common operation.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves the currently selected function but does not explain what 'selected' means (e.g., UI context, programmatic state), potential errors, or output format. This leaves significant gaps in understanding 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 with no wasted words, making it highly concise and front-loaded. It efficiently conveys the core purpose 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 no parameters, an output schema exists (which should cover return values), and no annotations, the description is minimally adequate. However, it lacks context on what 'selected' entails and how this differs from sibling tools, leaving room for improvement in completeness.
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 tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description appropriately does not discuss parameters, as none exist, aligning with the baseline expectation for parameterless tools.
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') and the resource ('function currently selected by the user'), making the purpose evident. However, it does not differentiate this tool from similar siblings like 'get_function_by_address' or 'get_function_by_name', which would require explicit comparison to achieve 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 such as 'get_function_by_address' or 'get_function_by_name', nor does it mention prerequisites or context for selection. It lacks explicit when/when-not instructions or named alternatives.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states a read operation ('Get'), implying it's likely non-destructive, but doesn't specify permissions, rate limits, output format, or whether it returns all entries at once or paginates. For a tool with zero annotation coverage, this is insufficient.
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 purpose, making it easy to parse quickly, which is ideal for a simple tool.
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 0 parameters, 100% schema coverage, and an output schema exists, the description is minimally adequate. However, it lacks context about what 'entry points' are (e.g., in a database context), which could help the agent understand when to use it, especially with many similar listing siblings.
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 tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it correctly doesn't mention any, earning a baseline high score for this dimension.
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') and resource ('all entry points in the database'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'list_functions' or 'list_segments', which also retrieve collections of items from the database, so it misses full 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. With many sibling tools that list various database items (e.g., 'list_functions', 'list_segments'), there's no indication of what 'entry points' are or when this specific retrieval is appropriate, leaving usage ambiguous.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions pagination, which is useful, but fails to describe critical traits such as whether this is a read-only operation, potential performance impacts, rate limits, or authentication requirements. For a tool with no annotation coverage, this leaves significant gaps in understanding its 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 purpose ('List all functions in the database') and includes essential behavioral detail ('paginated') without any wasted words. It is appropriately sized and 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 that an output schema exists, the description does not need to explain return values. It covers the basic purpose and pagination behavior adequately. However, for a tool with no annotations and sibling alternatives, it lacks guidance on usage and behavioral traits, slightly reducing 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 100%, so the input schema already documents both parameters ('offset' and 'count') thoroughly. The description adds no additional meaning or context beyond what the schema provides, such as default values or usage tips, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 ('functions in the database'), making the purpose specific and understandable. However, it does not explicitly differentiate from its sibling 'list_functions_filter', which appears to offer filtered listing capabilities, leaving some ambiguity about when to choose one over the other.
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_functions_filter'. It mentions pagination but does not specify scenarios where this unfiltered listing is preferred or any prerequisites for usage, leaving the agent without clear selection criteria.
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?
No annotations are provided, so the description carries full burden. It mentions pagination, which is useful behavioral context, but lacks details on permissions, rate limits, error conditions, or what 'imported symbols' entails in this context. For a tool with no annotations, this leaves significant gaps in understanding its 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 with no wasted words. It's front-loaded with the core purpose and includes key details (name, module, paginated) without redundancy. Every element earns its place, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 (simple list operation), 100% schema coverage, and presence of an output schema (which handles return values), the description is reasonably complete. It covers the core action and pagination behavior. However, with no annotations and many sibling listing tools, it could benefit from more context on scope or limitations.
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 100%, with clear descriptions for offset and count parameters. The description adds no parameter-specific information beyond what's in the schema. According to rules, with high schema coverage, the baseline is 3 even without param info 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 verb 'list' and resource 'imported symbols', specifying they include 'name and module' and are 'paginated'. It distinguishes from siblings like list_functions or list_strings by focusing on imports, though it doesn't explicitly contrast with them. The purpose is specific but lacks explicit 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?
No guidance on when to use this tool versus alternatives is provided. The description doesn't mention prerequisites, context, or exclusions. With many sibling tools for listing different entities (functions, strings, globals), the absence of usage guidelines leaves the agent without direction on selecting this specific list tool.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('List all segments') but doesn't describe what 'segments' are in this context, how the list is formatted, whether it's paginated, or any performance considerations. This leaves significant gaps for a tool with no 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, efficient sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized for a no-parameter tool and front-loads the 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 0 parameters, 100% schema coverage, and an output schema exists, the description is minimally adequate. However, with no annotations and a potentially complex domain (binary analysis), it could benefit from more context about what 'segments' are or example output. The output schema helps but doesn't fully compensate for the lack of behavioral details.
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 tool has 0 parameters, and the schema description coverage is 100% (empty schema). The description doesn't need to explain parameters, so it appropriately avoids parameter details. A baseline of 4 is justified since there are no parameters to document.
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 the resource 'segments in the binary', making the purpose specific and understandable. It doesn't explicitly differentiate from sibling tools like 'list_functions' or 'list_imports', but the resource specificity ('segments') provides implicit 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 like 'list_functions' or 'list_imports'. The description states what it does but offers no context about when it's appropriate or what prerequisites might exist.
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?
No annotations are provided, so the description carries full burden. It mentions pagination, which is a key behavioral trait, but doesn't disclose other important aspects like rate limits, authentication needs, error conditions, or what the paginated output looks like. For a read operation with no annotations, this 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 a single, efficient sentence with zero waste. It's front-loaded with the core purpose ('List all strings in the database') and adds necessary context ('paginated') without redundancy. 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 low complexity (simple list operation), 100% schema coverage, and existence of an output schema (which means return values are documented elsewhere), the description is reasonably complete. It covers the core purpose and pagination behavior, though it could benefit from more behavioral context given the lack of annotations.
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 100%, so the schema fully documents both parameters (offset and count). The description adds no additional parameter semantics beyond implying pagination, which is already covered by the parameters' existence. Baseline 3 is appropriate when the schema does the heavy lifting.
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 ('all strings in the database'), making the purpose unambiguous. It distinguishes from 'list_strings_filter' by specifying 'all strings' versus filtered strings, though it doesn't explicitly name the sibling. The mention of pagination adds useful scope information.
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 explicit guidance on when to use this tool versus alternatives like 'list_strings_filter' is provided. The description implies usage for retrieving all strings without filtering, but lacks context about prerequisites, performance considerations, or clear differentiation from sibling tools.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions what the tool returns ('basic blocks with their instructions and successor/predecessor relationships') but lacks details on permissions, rate limits, error handling, or whether it's a read-only operation. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
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 two sentences that directly state the purpose and output. There is no wasted text, though it could be slightly more structured by explicitly separating purpose from return details. Every sentence earns its place by providing 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?
Given the tool's moderate complexity (analyzing function control flow), the presence of an output schema (which likely covers return values), and high schema description coverage, the description is reasonably complete. It specifies what is retrieved and the return structure, but could improve by addressing behavioral aspects like error cases or usage context, especially since no annotations are provided.
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 100% description coverage, with the 'address' parameter documented as 'Address of the function to analyze.' The description does not add any additional meaning or context beyond this, such as format examples or constraints. Baseline score of 3 is appropriate since the schema adequately covers parameter semantics.
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 tool's purpose: 'Get the control flow graph of a function, including all basic blocks and their connections.' It specifies the verb ('Get'), resource ('control flow graph of a function'), and scope ('basic blocks and their connections'), distinguishing it from siblings like 'decompile_function' or 'disassemble_function' which focus on different aspects of function analysis.
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, exclusions, or compare it to similar tools like 'decompile_function' or 'disassemble_function' that might serve related purposes in analyzing functions. Usage is implied only by the purpose statement.
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?
No annotations are provided, so the description carries full burden. It mentions wildcard support and return format, but lacks critical behavioral details: whether it's read-only/destructive, permission requirements, performance/rate limits, error handling, or pagination behavior for large results. The description is insufficient for a mutation-sensitive 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?
Two concise sentences with zero waste. First sentence states purpose and key feature (wildcards), second describes return format. Well-structured and front-loaded with 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 3 parameters with full schema coverage and an output schema (implied by context signals), the description is adequate but incomplete. It lacks behavioral context (no annotations) and usage guidance, which are important for a search tool in a binary analysis environment with many sibling tools.
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 100%, so the schema fully documents all parameters. The description adds minimal value beyond the schema—it mentions wildcard support (implied in schema's example) and context bytes (output-related). Baseline 3 is appropriate when schema does the heavy lifting.
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 ('Search for a byte pattern in the binary'), the resource ('the binary'), and distinguishes from siblings by specifying it returns addresses with context bytes. This is more specific than generic search tools like search_structures.
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 like data_read_byte or read_memory_bytes. It doesn't mention prerequisites (e.g., binary must be loaded) or exclusions. The description only states what it does, not when to choose it.
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?
No annotations are provided, so the description carries full burden. It states the tool gets assembly code but doesn't disclose behavioral traits like whether it requires specific permissions, how it handles invalid addresses, if it's read-only or has side effects, or any rate limits. The API compatibility note adds some context but doesn't address core behavioral transparency needed for a tool with no 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, efficient sentence that front-loads the core purpose ('Get assembly code for a function') and adds a relevant contextual note. There's no wasted verbiage, repetition, or unnecessary elaboration, making it appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 full schema coverage and an output schema exists (per context signals), the description is reasonably complete. It clearly states what the tool does and adds API context. However, for a tool with no annotations, it could better address behavioral aspects like safety or error handling to fully compensate for the lack of structured metadata.
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 100% description coverage, with the single parameter 'start_address' well-documented in the schema. The description doesn't add any parameter-specific information beyond what the schema provides, such as address format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to.
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 assembly code for a function' specifies the verb (get) and resource (assembly code for a function). It distinguishes from siblings like 'decompile_function' by focusing on assembly rather than decompiled code, though it doesn't explicitly contrast with other disassembly-related tools. The API compatibility note adds context but doesn't affect core purpose clarity.
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 mentioning API compatibility with older IDA builds, suggesting it's for disassembly tasks in that context. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'decompile_function' or 'patch_address_assembles', nor does it mention prerequisites or exclusions. The context is clear but lacks specific comparative guidance.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but lacks details on behavior: it does not specify if this requires prior analysis (e.g., disassembly), what the output format is (though an output schema exists), whether it includes indirect calls, or if there are rate limits or permissions needed.
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—it directly states the tool's purpose without redundancy or unnecessary elaboration, making it easy to parse and front-loaded with 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?
Given the tool's moderate complexity (retrieving callees from a function address), the description is complete enough for basic understanding. It lacks behavioral details, but the presence of an output schema reduces the need to explain return values. However, without annotations, it could benefit from more context on usage and behavior.
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 100%, so the schema already documents the single parameter 'function_address' with its description. The description adds no additional meaning beyond implying it's for retrieving callees, but does not clarify format (e.g., hex address) or constraints (e.g., valid ranges). Baseline 3 is appropriate as the schema does the heavy lifting.
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 ('Get all the functions called') and the target resource ('by the function at function_address'), distinguishing it from sibling tools like 'get_callers' (which would get functions that call a given function) and 'get_function_by_address' (which retrieves function details rather than its callees).
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 (e.g., whether the function must be defined or analyzed), exclusions, or comparisons to similar tools like 'get_callers' or 'decompile_function' (which might also reveal callees).
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?
With no annotations provided, the description carries the full burden. It discloses pagination and filtering behavior, which is useful. However, it lacks details on permissions, rate limits, error conditions, or what 'matching' entails beyond the filter parameter. It doesn't contradict annotations since none exist.
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 key information (list, matching globals, paginated, filtered) with zero wasted words. Every part earns its place by clarifying scope and behavior.
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 an output schema (which handles return values), 100% schema coverage, and no annotations, the description is reasonably complete. It covers the core action and key behavioral traits (paginated, filtered), but could improve by addressing usage context or more behavioral details like error handling.
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 100%, so the schema fully documents parameters. The description adds minimal value by implying filtering but doesn't elaborate on semantics beyond what's in the schema (e.g., how 'filter' works with 'case-insensitive contains or /regex/ syntax' is already in the schema). 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 verb 'List' and resource 'matching globals in the database', specifying it's paginated and filtered. It distinguishes from the sibling 'list_globals' by mentioning filtering, but doesn't explicitly contrast with 'list_globals' or other list tools like 'list_functions_filter'.
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_globals' (unfiltered) or other filtered list tools (e.g., 'list_functions_filter'). It mentions filtering but doesn't specify scenarios or prerequisites for its use.
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?
With no annotations provided, the description carries the full burden. It discloses key behavioral traits: pagination and filtering, which are essential for understanding how the tool operates. However, it lacks details on permissions, rate limits, error handling, or what 'database' refers to, leaving gaps in behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads key information ('List matching strings') and includes essential details ('paginated, filtered') without waste. Every word earns its place, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 (a filtered list operation with pagination), no annotations, and an output schema (which handles return values), the description is reasonably complete. It covers the core action and key behaviors but could improve by addressing usage context or database specifics, though the output schema reduces the need for return value explanation.
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 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by implying filtering semantics ('matching strings'), but doesn't elaborate on parameter interactions or provide additional context. Baseline 3 is appropriate given high schema 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 verb ('List') and resource ('matching strings in the database'), making the purpose evident. It distinguishes from the sibling 'list_strings' by specifying filtering, though it doesn't explicitly contrast with 'list_strings_filter' (which appears to be the same tool) or other list tools like 'list_functions_filter'.
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 filtering but doesn't specify scenarios or prerequisites, such as when to choose this over 'list_strings' or other filtering tools like 'list_functions_filter'. Usage 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.
Behavior2/5
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 mentions the compile-time condition ('if known at compile-time'), which is useful behavioral context. However, it doesn't disclose other important traits like whether this is a read-only operation, what happens if the variable doesn't exist, error conditions, or performance characteristics. The description adds some value 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. The first sentence states the purpose, and the second provides usage guidance. Every sentence earns its place with no wasted words, making it front-loaded and efficient.
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 that there's an output schema (which handles return values), 1 parameter with 100% schema coverage, and no annotations, the description provides adequate context. It covers the core purpose and gives important usage guidance about preferring this over data_read functions. However, for a tool that reads values with compile-time constraints, more behavioral transparency would be beneficial.
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 100%, so the schema already documents the single parameter 'variable_name' with its description. The description doesn't add any parameter-specific information beyond what's in the schema. According to the rules, when schema coverage is high (>80%), the baseline is 3 even with no param info 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 tool's purpose: 'Read a global variable's value (if known at compile-time)'. It specifies the verb ('Read') and resource ('global variable's value'), making the function clear. However, it doesn't explicitly differentiate from sibling tools like 'get_global_variable_value_at_address' or 'data_read_*' functions beyond a general preference statement.
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 provides explicit guidance: 'Prefer this function over the `data_read_*` functions.' This gives clear context about when to choose this tool over alternatives. However, it doesn't specify when NOT to use it (e.g., for runtime values) or mention other alternatives like 'get_global_variable_value_at_address'.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool reads bytes but does not specify permissions required, potential side effects (e.g., if reading protected memory causes errors), rate limits, or error handling. This leaves significant gaps for a tool that interacts with memory, which could be risky or complex.
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 very concise with only two sentences, each serving a clear purpose: the first states the tool's function, and the second provides usage guidelines. There is no wasted text, and it is front-loaded with 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 that an output schema exists, the description does not need to explain return values. However, for a memory-reading tool with no annotations, the description lacks details on behavioral aspects like safety, permissions, or error conditions. The usage guidelines are strong, but overall completeness is moderate due to missing behavioral context.
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 100%, so the input schema already documents both parameters ('memory_address' and 'size') adequately. The description does not add any additional meaning or context beyond what the schema provides, such as format details for 'memory_address' (e.g., hexadecimal) or constraints on 'size' (e.g., maximum bytes).
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 ('bytes at a given address'), making the purpose specific and understandable. However, it does not explicitly distinguish this tool from its siblings like 'data_read_byte', 'data_read_dword', etc., which appear to perform similar memory reading operations but with different data types or scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool: 'Only use this function if `get_global_variable_at` and `get_global_variable_by_name` both failed.' This clearly defines the context and alternatives, helping the agent choose appropriately among sibling tools.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions the tool reads a 2-byte WORD value, it doesn't specify what happens on invalid addresses (e.g., errors, null returns), whether it requires specific permissions, or any rate limits. For a read operation with zero annotation coverage, this leaves 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences that each serve a clear purpose: the first defines the tool's function, and the second provides critical usage guidance. There is zero wasted text, making it highly efficient and front-loaded.
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 (single parameter, read-only operation), the presence of an output schema (which handles return values), and 100% schema coverage, the description is reasonably complete. It effectively covers purpose and usage guidelines, though it could benefit from more behavioral context given the lack of annotations.
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 schema description coverage is 100%, with the address parameter well-documented in the schema. The description adds no additional parameter semantics beyond what the schema already provides (e.g., format examples, constraints). Given the high schema coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 ('2 byte value at the specified address as a WORD'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like data_read_byte, data_read_dword, etc., beyond the implied word size difference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool: 'Only use this function if `get_global_variable_at` failed.' This clearly defines the alternative scenario and establishes a fallback usage pattern, which is excellent for agent decision-making.
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 tool retrieves multiple comment types and includes function comments when relevant, which adds behavioral context beyond a simple 'get'. However, it doesn't mention permissions, rate limits, error conditions, or the format/scope of returned data, leaving gaps for a read 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 two concise sentences with zero waste: the first states the core purpose and scope, and the second adds a critical behavioral nuance. It's front-loaded with essential information and efficiently structured.
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 one parameter with full schema coverage and an output schema (implied by 'Has output schema: true'), the description is reasonably complete. It clarifies the types of comments retrieved and the function comment inclusion, which adds value beyond structured fields. However, for a tool with no annotations, it could better address behavioral aspects like error handling or data format.
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 100%, with the parameter 'address' documented in the schema. The description adds semantic context by explaining what 'address' means in this context (e.g., that it can be within a function to trigger additional comment retrieval), but doesn't provide syntax or format details beyond the schema. Baseline 3 is appropriate given high schema coverage.
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 verb 'Get' and resource 'all comments at the specified address', specifying the types of comments included (regular, repeatable, anterior, posterior) and the special case for function comments. It distinguishes from sibling tools like 'add_comment', 'delete_comment', and 'set_comment' which modify rather than retrieve comments.
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 when comments at an address are needed, including function comments when applicable. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_metadata' or 'get_struct_at_address' that might also provide comment-like information, nor does it 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.
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 tool is for reading (not writing) and mentions the compile-time address requirement, which adds useful context. However, it lacks details on permissions, error handling, or performance implications, leaving behavioral gaps for a tool with no 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 extremely concise and front-loaded: two sentences with zero waste. The first sentence states the purpose, and the second provides usage guidance, both earning their place without redundancy or fluff.
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 that there is an output schema (which handles return values) and 100% schema coverage for the single parameter, the description is reasonably complete. It covers purpose and usage guidelines but could improve by addressing sibling differentiation or more behavioral details, though the output schema reduces the need for return value explanation.
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 schema description coverage is 100%, so the schema already documents the 'address' parameter. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. This meets the baseline for high schema coverage but does not enhance 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: 'Read a global variable's value by its address (if known at compile-time)'. It specifies the verb ('Read'), resource ('global variable's value'), and method ('by its address'), but does not explicitly differentiate from its sibling 'get_global_variable_value_by_name', which reads by name instead of address.
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 provides clear usage guidance: 'Prefer this function over the `data_read_*` functions.' This indicates when to use this tool versus alternatives, specifically naming the 'data_read_*' functions as less preferred. However, it does not mention when to use this tool versus 'get_global_variable_value_by_name' or other siblings, which is a minor gap.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool reads a byte value, implying a read-only operation, but does not disclose other behavioral traits such as error handling, permissions required, rate limits, or what happens if the address is invalid. For a tool with no annotation coverage, this leaves significant gaps in understanding its 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 extremely concise and front-loaded, consisting of two sentences that each earn their place: the first defines the purpose, and the second provides critical usage guidance. There is no wasted text, making it efficient for an agent 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 low complexity (single parameter, no nested objects) and the presence of an output schema (which handles return values), the description is mostly complete. It covers purpose and usage guidelines well. However, the lack of annotations and minimal behavioral transparency slightly reduces completeness, as agents might need more context on error cases or constraints.
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 schema description coverage is 100%, with the parameter 'address' well-documented in the schema as 'Address to get 1 byte value from'. The description adds minimal semantics beyond this, only reinforcing the address usage. With high schema coverage, the baseline score of 3 is appropriate as the schema does the heavy lifting.
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 ('Read') and resource ('1 byte value at the specified address'), distinguishing it from sibling tools like data_read_dword, data_read_qword, data_read_string, and data_read_word which handle different data sizes/types. It precisely defines the tool's function 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 Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly provides usage guidance by stating 'Only use this function if `get_global_variable_at` failed.' This gives clear context for when to use this tool versus an alternative (get_global_variable_at), including a specific exclusion rule, which is ideal for agent decision-making.
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 states the action ('Read the string') but lacks details on behavioral traits such as error handling, permissions needed, or what happens if the address is invalid. It adds some context with the usage condition, but more behavioral disclosure would be helpful for a tool with no 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 very concise with two sentences that directly state the purpose and usage guidelines. There is no wasted text, and it is front-loaded with the core action, making it efficient and well-structured.
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 an output schema (which handles return values), no annotations, and high schema coverage, the description is reasonably complete. It covers purpose and usage well but could benefit from more behavioral context, such as error cases or performance considerations, to fully compensate for the lack of annotations.
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 100% description coverage, with the 'address' parameter documented as 'Address to get string from'. The description does not add further meaning beyond this, such as address format or constraints. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema already provides adequate 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 clearly states the verb ('Read') and resource ('string at the specified address'), making the purpose specific and understandable. However, it does not explicitly differentiate this tool from sibling tools like 'data_read_byte', 'data_read_word', etc., which likely read different data types from addresses, so it misses full 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 Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: 'Only use this function if `get_global_variable_at` failed.' This clearly indicates when to use this tool versus an alternative, specifying a prerequisite condition and naming the alternative tool.
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 full burden. It clearly indicates this is a read operation (not destructive) and implies it reads from memory addresses, but doesn't disclose potential errors (e.g., invalid addresses), permissions needed, or rate limits. The description adds basic context but lacks comprehensive 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?
Two sentences with zero waste. First sentence states the core purpose, second provides crucial usage guidance. Perfectly front-loaded and appropriately sized for a simple read operation.
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 simple read operation with 100% schema coverage and an output schema (implied by 'Has output schema: true'), the description is mostly complete. It clearly states purpose, provides excellent usage guidance, and the output schema will handle return values. Minor gap in behavioral transparency for error cases.
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 100%, with the address parameter well-documented in the schema. The description adds minimal value beyond the schema by specifying it reads '4 byte value' and 'as a DWORD', but doesn't provide additional format or validation details. Baseline 3 is appropriate when schema does the heavy lifting.
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 ('Read'), resource ('4 byte value at the specified address'), and data type ('as a DWORD'), distinguishing it from sibling tools like data_read_byte, data_read_word, and data_read_qword that handle different data sizes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when-not-to-use guidance: 'Only use this function if `get_global_variable_at` failed.' This directly addresses alternative selection by naming a specific sibling tool (get_global_variable_value_at_address) and specifying a clear condition for usage.
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 describes the core behavior (reading 8 bytes from an address) but lacks details on permissions, error handling, or memory safety. It adds some context by mentioning the fallback to `get_global_variable_at`, but more behavioral traits would be helpful.
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 with zero waste: the first states the purpose, and the second provides usage guidance. It is front-loaded and efficiently structured, with every sentence earning 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 low complexity (one parameter, 100% schema coverage, and an output schema exists), the description is reasonably complete. It covers purpose and usage context well, but as a low-level memory read operation without annotations, more behavioral details (e.g., error conditions) would enhance 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 100%, so the schema already documents the 'address' parameter. The description implies the address is for reading 8 bytes but doesn't add format or validation details beyond the schema. Baseline 3 is appropriate when the schema handles parameter documentation.
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 ('Read the 8 byte value') and resource ('at the specified address as a QWORD'), distinguishing it from sibling tools like data_read_byte, data_read_dword, and data_read_word by specifying the 8-byte QWORD data type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides explicit guidance on when to use this tool ('Only use this function if `get_global_variable_at` failed'), naming a specific alternative and establishing a clear fallback context, which helps differentiate it from other read operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: the code's access to IDA modules, the use of a 'result' variable for returns, and a warning about database modification and power. This covers safety, output mechanism, and environmental context beyond basic execution.
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 and front-loaded, starting with the core purpose, followed by access details, return mechanism, warning, and an example. Each sentence adds value without redundancy, and the structure guides the user from general to specific information efficiently.
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 complexity (arbitrary code execution with database modification risk), no annotations, and an output schema present, the description is complete. It covers purpose, behavior, warnings, and provides an example, addressing the need for guidance without repeating structured data. The output schema handles return values, so no additional explanation is required.
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 100%, so the schema already documents both parameters ('code' and 'timeout_seconds'). The description adds minimal param-specific semantics, only implying code execution through the example. It does not provide additional syntax or format details beyond what the schema offers, meeting the baseline for high coverage.
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 tool's purpose as 'Execute arbitrary IDAPython code in the IDA environment,' specifying both the action (execute) and resource (IDAPython code). It distinguishes itself from sibling tools by emphasizing arbitrary code execution capability, unlike more specific tools like 'decompile_function' or 'rename_function.'
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 provides clear context for usage by mentioning access to IDA modules and a warning about database modification, but it does not explicitly state when to use this tool versus alternatives. It implies usage for custom operations not covered by other tools, though no direct comparisons or exclusions are made.
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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