Frida MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation4/5
Most tools have distinct purposes with clear boundaries, such as frida_attach for attaching to processes and frida_memory_read for reading memory. However, some overlap exists, like frida_hook_function, frida_intercept_method, frida_java_hook_method, and frida_objc_hook_method, which all involve hooking but target different platforms or languages, potentially causing confusion if not carefully described.
Naming Consistency5/5All tool names follow a consistent snake_case pattern with a 'frida_' prefix, making them predictable and easy to parse. The naming convention is uniform across all 55 tools, with no deviations in style or structure.
Tool Count2/5With 55 tools, the count is excessive for a single server, likely overwhelming for agents and leading to decision paralysis. While Frida is a comprehensive framework, this many tools suggests poor scoping, as many could be consolidated or grouped into subcategories.
Completeness5/5The tool set provides complete coverage for dynamic instrumentation and analysis tasks, including process management, memory operations, hooking, scripting, and platform-specific features for Android and iOS. No obvious gaps are present; it supports full lifecycle operations from spawning to debugging.
Average 2.9/5 across 55 of 55 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- No commit activity data available
- 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.jsonto 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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the action without behavioral details. It doesn't disclose if this is a read-only or destructive operation, what permissions or device states are required, side effects, or error conditions, making it inadequate 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no wasted words, making it highly concise. It's front-loaded with the core action, though this brevity comes at the cost of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema coverage, no output schema, and a mutation tool with 2 parameters, the description is incomplete. It lacks essential context like behavioral traits, parameter meanings, and expected outcomes, making it insufficient for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no information about parameters. It doesn't explain what 'device_id' or 'device_type' are, their roles in disabling spawn gating, or how they interact, leaving both parameters undocumented and uninterpretable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Disable spawn gating' states the action (disable) and target (spawn gating), providing a basic purpose. However, it's vague about what 'spawn gating' entails and doesn't differentiate from sibling tools like 'frida_enable_spawn_gating' beyond the opposite action, lacking specificity about scope or effects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., that spawn gating must be enabled first), dependencies on other tools, or typical workflows, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- 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 inspects an APK but doesn't describe what the inspection involves (e.g., read-only analysis, potential side effects, output format, or any limitations like file size constraints). 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function. It's appropriately sized and front-loaded with the core action, though it could be more structured by including key details. There's no wasted text, making it concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of APK inspection (likely involving analysis tasks), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the inspection returns (e.g., metadata, vulnerabilities, code structure) or behavioral aspects, leaving the agent with insufficient context to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 'apk_path' clearly documented as 'Path to APK file'. The description doesn't add any meaning beyond this (e.g., format requirements, examples, or constraints), so it meets the baseline of 3 where the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool inspects an Android APK file using frida-apk, which provides a basic verb (inspect) and resource (APK file). However, it's vague about what 'inspect' entails (e.g., extracting metadata, analyzing code, checking permissions) and doesn't distinguish it from sibling tools like frida_list_modules or frida_list_imports that might also analyze APK components. The purpose is clear but lacks specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an APK file available), context for inspection (e.g., static analysis vs. dynamic), or how it differs from other frida tools that might handle APK-related tasks. 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?
With no annotations, the description carries full burden but provides minimal behavioral insight. 'Detach' implies ending a connection, but it doesn't disclose whether this is destructive (e.g., stops debugging), has side effects, requires specific states, or what happens post-detachment. It lacks details on permissions, rate limits, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no wasted words, making it appropriately concise. However, it's overly terse and could benefit from slightly more context without losing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's likely complexity (involving session management in a debugging context), no annotations, and no output schema, the description is incomplete. It fails to explain what detachment does, its effects, or return values, leaving significant gaps for an agent to understand the tool's behavior fully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'session_id', which is documented as 'Session ID from frida_attach'. The description adds no additional meaning beyond this, so it meets the baseline of 3 where the schema handles parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Detach from a session' clearly states the action (detach) and target (a session), but it's vague about what 'detach' entails operationally. It distinguishes from siblings like 'frida_attach' by implying an inverse operation, but lacks specificity about the session's nature or effects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 logically follows 'frida_attach', the description doesn't explicitly state this relationship, prerequisites, or any context for detachment (e.g., after debugging).
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?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It doesn't describe whether the call is synchronous/asynchronous, error handling, performance impact, security implications, or what happens if the method doesn't exist. For a tool that executes code in a live Android environment, this lack of transparency is critical and inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without fluff. It's front-loaded with the essential action and target, and the parenthetical '(Android)' adds necessary context concisely. Every word earns its place, making it optimally brief for the information provided.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (executing Java methods in Android via Frida), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't address behavioral risks, return values, error cases, or dependencies on other tools (e.g., 'frida_attach' for sessions). For a tool with potential side effects in a dynamic analysis context, this is a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is low (20%), with only 'args' having a description ('Method arguments'). The description adds no parameter semantics beyond what the schema provides—it doesn't explain 'session_id' (Frida session identifier), 'class_name' format (e.g., fully qualified), 'method_name' specifics, or 'static' implications. With 5 parameters and poor schema coverage, the description fails to compensate, leaving most parameters undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Call a method') and target ('on a Java class or instance'), with the parenthetical '(Android)' providing platform context. It distinguishes from siblings like 'frida_java_hook_method' (which hooks rather than calls) and 'frida_objc_call_method' (which targets Objective-C). However, it doesn't specify the verb's scope (e.g., synchronous execution, return value handling), making it slightly less specific than a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an active Frida session), compare it to 'frida_evaluate' (for JavaScript) or 'frida_rpc_call' (for RPC), or specify use cases like testing or debugging. The agent must infer usage from the tool name and context alone.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers almost no information. It doesn't indicate whether this operation requires specific permissions, if it's destructive (e.g., overwrites local files), what happens on failure, or any rate limits. The single sentence lacks essential operational context for a file transfer tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place, though this brevity comes at the cost of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 4 parameters, no annotations, and no output schema, the description is severely inadequate. It doesn't address behavioral aspects like safety or side effects, provide usage context, or explain parameter interactions. Given the complexity of file operations in a device instrumentation context, more guidance is needed for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 50% (2 of 4 parameters have descriptions), and the description adds no parameter-specific information beyond the generic 'file from the device' context. It doesn't explain the purpose of 'device_id' or 'device_type', clarify path formats, or provide examples. The description fails to compensate for the schema's gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('pull/download') and resource ('a file from the device'), making the purpose immediately understandable. It distinguishes itself from sibling tools like 'frida_push_file' by specifying directionality. However, it doesn't specify the exact mechanism or context (e.g., Frida instrumentation), 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 Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an attached device), compare it to similar tools like 'frida_push_file' for upload operations, or specify scenarios where file transfer is appropriate versus other data access methods. This leaves the agent with minimal contextual cues.
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 states 'resume a spawned process,' implying a mutation that changes process state, but doesn't disclose behavioral traits such as required permissions, side effects (e.g., resumes execution), error conditions, or what 'resume' means operationally. 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no wasted words. It's front-loaded with the core action and target, making it easy to parse quickly. Every word earns its place, achieving optimal conciseness for the given content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a mutation tool with no annotations, 3 parameters, 33% schema coverage, and no output schema), the description is incomplete. It lacks details on behavior, parameter usage, output expectations, and context within the sibling tools. For a tool that likely resumes process execution, more information 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.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 33% (only 'pid' has a description). The description adds no parameter semantics beyond the schema—it doesn't explain 'device_id' or 'device_type' usage, or how parameters interact (e.g., 'device_type' enum values affect 'device_id'). With low coverage and no compensation in the description, it falls short of providing adequate meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('resume') and target ('a spawned process'), which is clear but vague. It doesn't specify what 'resume' entails in this context (e.g., from a paused state) or differentiate from siblings like 'frida_attach' or 'frida_detach', which are related to process interaction. The purpose is understandable but lacks specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., requires a previously spawned or attached process), exclusions, or how it relates to siblings like 'frida_spawn' (to start) or 'frida_detach' (to disconnect). The description assumes context without explicit 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that spawn gating 'intercept[s] new processes before they run,' which hints at a monitoring/mutation capability, but doesn't specify whether this requires specific permissions, affects system stability, has side effects, or what the expected outcome is. For a tool that likely modifies runtime behavior, 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.
Conciseness5/5Is 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 simple action and front-loads the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a tool that likely modifies process interception behavior), no annotations, no output schema, and 0% schema coverage for parameters, the description is incomplete. It explains what the tool does at a high level but lacks crucial details about parameters, behavioral implications, and usage context that would be needed for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning neither parameter (device_id, device_type) is documented in the schema. The description adds no information about these parameters—it doesn't explain what they are, when they're required, or how they affect the operation. This leaves both parameters completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Enable spawn gating') and the purpose ('to intercept new processes before they run'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from its sibling 'frida_disable_spawn_gating' beyond the obvious enable/disable distinction, 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 Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a device connection first), when spawn gating is appropriate versus other interception methods, or what happens after enabling it. The context is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- 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 it's a listing operation, implying read-only behavior, but doesn't disclose any behavioral traits like permissions needed, rate limits, output format, or whether it requires device connectivity. For a 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core purpose in the first clause. The parenthetical note adds useful context without verbosity. It's appropriately sized for a simple listing tool, with no wasted sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't explain parameters, behavioral aspects, or return values, leaving the agent with insufficient information for reliable tool use in a complex Frida ecosystem.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds no information about the two parameters (device_id and device_type), their purposes, or how they affect the listing. Without this, the agent lacks context for proper invocation, failing to address the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List all installed applications') and target resource ('on a device'), with a helpful note about mobile device relevance. It distinguishes from obvious siblings like frida_list_processes or frida_list_modules by specifying applications, though it doesn't explicitly differentiate from all siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 mobile devices as 'useful' but doesn't specify if it's exclusive to them, required prerequisites, or when to choose other listing tools like frida_list_processes. This leaves the agent without 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?
No annotations are provided, so the description carries the full burden. It mentions the output includes 'state and context', which adds some behavioral detail, but lacks critical information: whether this is a read-only operation, if it requires specific permissions, potential side effects (e.g., pausing threads), or error conditions. 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose. Every word contributes meaning without redundancy or fluff, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It omits parameter details, behavioral traits (e.g., safety, side effects), and output specifics (e.g., format, pagination). For a tool in a complex debugging context with many siblings, this leaves significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It doesn't mention the 'session_id' parameter at all, leaving its purpose, format, and source undocumented. The description adds no parameter semantics beyond what's inferred from the tool name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does 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 threads in the process'), specifying what information is returned ('with their state and context'). It distinguishes from siblings like frida_list_processes (lists processes) and frida_list_modules (lists modules), 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 Guidelines2/5Does 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., requiring an active Frida session), context (e.g., debugging scenarios), or exclusions (e.g., not for enumerating processes).
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 what the tool does but lacks behavioral details: it doesn't mention permissions needed, whether it requires an attached device, error conditions (e.g., if no frontmost app exists), return format, or rate limits. 'Get' implies a read operation, but without annotations, more transparency is needed for a mutation-risk context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single, front-loaded sentence with zero waste. Every word ('Get', 'frontmost application', 'mobile devices') contributes essential information without redundancy. It's appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters with 0% schema coverage, no annotations, and no output schema, the description is incomplete. It adequately states the purpose but lacks parameter details, behavioral context, and output information. For a tool in a complex Frida ecosystem with many siblings, more guidance is needed to ensure correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for two undocumented parameters. It adds no information about device_id or device_type parameters—not explaining what they represent, their formats, or default behaviors. The mention of 'mobile devices' hints at context but doesn't clarify parameter usage or requirements.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and target ('the frontmost application'), specifying it's for mobile devices. It distinguishes itself from siblings like frida_get_process or frida_get_device_info by focusing on the currently active application rather than processes or device information. However, it doesn't explicitly mention Frida context or differentiate from all siblings like frida_list_applications.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a connected device), when-not-to-use scenarios, or compare it to siblings like frida_get_process_info or frida_list_applications. The mobile device specification offers some context but no explicit usage rules.
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 what the tool does, not how it behaves. It doesn't disclose whether this is a read-only operation, if it requires specific permissions, what format the list returns, or any error conditions. The description adds minimal behavioral context 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.
Conciseness5/5Is 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 simple query 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 2 parameters (0% schema coverage), no annotations, and no output schema, the description is inadequate. It doesn't explain the 'spawn gate' concept, parameter usage, return format, or behavioral characteristics. Given the complexity implied by the sibling tools and lack of structured data, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but provides no parameter information. It doesn't explain what 'device_id' and 'device_type' mean, when they're required, or how they affect the operation. The description fails to add meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'list of processes waiting in spawn gate', making the purpose specific and understandable. It doesn't explicitly differentiate from siblings like 'frida_list_processes' or 'frida_get_process', but the 'spawn gate' context provides some distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'frida_list_processes' or 'frida_get_process'. The description implies it's for processes in a 'spawn gate', but doesn't explain what that means or when this state occurs.
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 it 'gets' info, implying a read-only operation, but doesn't disclose behavioral traits like whether it requires specific permissions, if it's safe to call repeatedly, rate limits, or what happens if the session is invalid. The description adds minimal context 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('Get detailed info') and includes relevant examples. There is zero waste, and every word earns its place by clarifying scope and content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on parameters, behavioral constraints, return values, and usage context. For a tool in a complex environment like Frida with many siblings, more guidance 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.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions 'attached process' which hints at the session_id parameter's purpose, but doesn't explain what session_id is, its format, or how to obtain it. With 1 undocumented parameter, the description adds some meaning but insufficient to fully compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('detailed info about the attached process') with specific examples of what info is retrieved ('arch, platform, threads, etc.'). It distinguishes from siblings like frida_get_device_info or frida_get_frontmost by specifying it's about the attached process, but doesn't explicitly differentiate from frida_get_process which might be similar.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an attached session), exclusions, or comparisons to siblings like frida_get_process or frida_enumerate_threads. Usage is implied by the name 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 the full burden. It states the tool lists modules/libraries but doesn't disclose behavioral traits such as whether it's read-only, what permissions are required, if it returns structured data, or any limitations (e.g., performance impact). This is a significant gap 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that is front-loaded with the core purpose. There is no wasted text, making it appropriately sized for its content, though it could benefit from additional details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a tool for dynamic analysis with Frida), lack of annotations, no output schema, and incomplete parameter documentation, the description is insufficient. It doesn't cover return values, error conditions, or operational context, leaving the agent with significant gaps in understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no meaning beyond the input schema, which has 0% coverage. It doesn't explain what 'session_id' is, how to obtain it, or its format. With one undocumented parameter and no compensation in the description, this falls below the baseline of 3 for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List all loaded modules/libraries') and resource ('in a process'), providing a specific verb+resource combination. It distinguishes itself from siblings like frida_list_exports or frida_list_imports by focusing on modules/libraries rather than symbols or imports/exports, 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 Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an active session), exclusions, or suggest other tools for related tasks like frida_list_symbols or frida_enumerate_ranges, 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool finds 'live instances on the heap,' implying a read-only operation, but doesn't clarify critical behaviors: whether it requires specific permissions, has performance impacts (heap scanning can be intensive), returns structured data, handles errors, or has limitations like only working with attached processes. The description is too minimal for a tool that interacts with runtime memory.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It front-loads the core action ('Find live instances') and includes essential context ('ObjC class on the heap' and 'iOS/macOS'). Every element earns its place, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (heap scanning in a dynamic instrumentation context), lack of annotations, 0% schema coverage, and no output schema, the description is incomplete. It omits critical details: expected outputs (e.g., list of instance addresses), error conditions, performance implications, and dependencies like an active Frida session. For a low-level debugging tool, this leaves too much undefined.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It only implicitly relates to 'class_name' by mentioning 'ObjC class,' but adds no meaning for 'session_id' (critical for Frida operations) or 'limit' (defaults to 10). Without explaining what these parameters do or their formats, the description fails to bridge the schema gap, leaving key inputs ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does 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 ('Find') and resource ('live instances of an ObjC class on the heap'), and specifies the target platforms ('iOS/macOS'). It distinguishes itself from siblings like 'frida_objc_enumerate_classes' by focusing on instance discovery rather than class enumeration. However, it doesn't explicitly contrast with 'frida_java_find_instances' beyond the ObjC/Java distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an active Frida session), compare it to similar tools like 'frida_java_find_instances' or 'frida_objc_enumerate_classes', or specify scenarios where it's appropriate (e.g., debugging memory issues). The platform context ('iOS/macOS') is helpful but insufficient for usage decisions.
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 but offers minimal information. It states what the tool does but doesn't explain what 'hooking' entails (e.g., intercepting method calls, modifying behavior), potential side effects, security implications, or expected outcomes. For a complex tool with mutation capabilities, 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence) and front-loaded with the core purpose. There's no wasted language or unnecessary elaboration, making it efficient for quick comprehension while still conveying the essential action and target.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex tool with 5 parameters, no annotations, no output schema, and low schema coverage, the description is inadequate. It doesn't explain what the tool returns, how hooks behave at runtime, error conditions, or platform-specific considerations. The minimal description leaves too many contextual questions unanswered for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 20% (only 'method_name' has a description), and the tool description adds no parameter information beyond what's in the schema. It doesn't explain what 'session_id' represents, the format of 'class_name', or the purpose of 'log_args' and 'log_return' flags. With 5 parameters and low schema coverage, the description fails to compensate for the documentation gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Hook') and target ('Objective-C method') with platform context ('iOS/macOS'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'frida_hook_function' or 'frida_java_hook_method', which would require more specific comparison to achieve 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 Guidelines2/5Does 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 'frida_hook_function' or 'frida_intercept_method' from the sibling list. There's no mention of prerequisites (e.g., needing an active Frida session), specific use cases, or limitations, leaving the agent with insufficient context for proper tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- 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 a socket connection') but fails to mention critical behaviors like whether this requires specific permissions, if the connection persists, error handling, or side effects on the target process. This leaves significant gaps in understanding the tool's operational impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently conveys the core purpose without unnecessary words. It is front-loaded with the main action and context, making it easy to parse and understand quickly, which is ideal for conciseness in tool descriptions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of socket creation in a target process, no annotations, no output schema, and low schema coverage, the description is incomplete. It lacks details on behavior, parameters, return values, error cases, and integration with sibling tools, making it insufficient for safe and effective use by an AI agent in this context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must compensate but adds no parameter details. It doesn't explain what 'session_id', 'host', 'port', or 'type' represent, their formats, or constraints beyond the schema's enum for 'type'. This lack of semantic context makes parameter usage ambiguous for the agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a socket connection') and specifies the context ('from within the target process'), which distinguishes it from general socket creation tools. However, it doesn't explicitly differentiate from potential sibling tools like network-related operations in the Frida ecosystem, though the context of 'within the target process' provides some distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 other Frida tools for network operations or system-level socket creation. It lacks context about prerequisites, typical use cases, or comparisons with sibling tools, leaving the agent to infer usage based on the tool name and description 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 the full burden of behavioral disclosure. It mentions that it 'Returns a session ID for further operations,' which hints at stateful behavior and follow-up actions, but fails to disclose critical traits like whether this is a read-only or destructive operation, permission requirements, potential side effects (e.g., pausing the process), or error conditions. 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded, consisting of two clear sentences that directly state the action and outcome. There is no wasted language or redundancy, making it efficient and easy to parse for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of attaching to a process (a potentially stateful or invasive operation), no annotations, no output schema, and low schema coverage, the description is insufficient. It lacks details on behavioral traits, error handling, return format beyond 'session ID,' and how it integrates with sibling tools, leaving the agent with incomplete 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.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is low at 33%, with only the 'target' parameter documented in the schema. The description adds no parameter-specific information beyond what the schema provides, such as clarifying 'device_id' or 'device_type' usage. Since schema coverage is below 50%, the description does not compensate adequately, resulting in a baseline score that reflects incomplete parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Attach to a running process') and the resource ('a running process'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'frida_spawn' (which starts a new process) or 'frida_get_process' (which retrieves process info without attaching), leaving room for improvement in 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 Guidelines2/5Does 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 'frida_spawn' for starting processes or 'frida_detach' for ending sessions. It lacks context on prerequisites (e.g., needing a running process) or exclusions, offering only basic functional information without 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?
No annotations are provided, so the description carries the full burden. It mentions the tool is 'Useful for debugging and analysis', which hints at read-only behavior, but doesn't disclose critical details like whether it requires active debugging sessions, potential performance impacts, error conditions, or the format of the returned backtrace. 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences: the first states the purpose, and the second adds context. It's front-loaded with the core functionality, though it could be slightly more structured by explicitly mentioning parameters or output. There's no wasted text, making it efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of debugging tools, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, error handling, output format, and usage constraints. For a tool with 3 parameters and no structured support, this minimal description doesn't provide enough context for reliable agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67% (2 out of 3 parameters have descriptions), and the description doesn't add any parameter-specific information beyond the schema. It doesn't explain the semantics of 'session_id' or how the backtrace is structured. With moderate schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate for the missing details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get stack backtrace for a thread' specifies a verb ('Get') and resource ('stack backtrace'), and 'Useful for debugging and analysis' provides context. However, it doesn't explicitly differentiate from sibling tools like 'frida_enumerate_threads' or 'frida_trace', which might also be used for debugging.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes 'Useful for debugging and analysis', which implies a general context but doesn't specify when to use this tool versus alternatives. No explicit guidance is provided on prerequisites, when-not-to-use scenarios, or comparisons with sibling tools like 'frida_stalker_trace' or 'frida_enumerate_threads'.
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 tool 'Returns symbols exported by the C code,' which adds some behavioral context. However, it lacks critical details: it doesn't specify if this is a read-only or destructive operation, what happens on failure, or any performance or security implications of compiling and loading C code.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise and front-loaded: it states the core purpose in the first clause and the return behavior in the second. Both sentences earn their place by providing essential information without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of compiling and loading C code, the lack of annotations, and no output schema, the description is incomplete. It doesn't cover error handling, side effects, or the format of returned symbols. For a tool with three parameters and potential security implications, more context is needed to guide safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67%, with two parameters (code and symbols) having descriptions and one (session_id) lacking. The description adds no additional parameter semantics beyond what's in the schema. It implies the tool uses the code and symbols parameters but doesn't explain their roles further. With moderate schema coverage, a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Compile and load inline C code for high-performance hooks.' It specifies the verb (compile and load), resource (inline C code), and context (for hooks). However, it doesn't explicitly differentiate from siblings like frida_compile_agent or frida_native_function, which may have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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, such as needing an active session, or compare it to siblings like frida_compile_agent or frida_inject_script. The agent must infer usage from the purpose 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 mentions the core functionality but doesn't describe behavioral traits such as whether this requires specific permissions, if it's read-only or has side effects, error handling, performance characteristics, or output format. For a debugging tool with potential security implications, this lack of context 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's functionality without unnecessary words. It's front-loaded with the core purpose and uses clear language. Every part of the sentence earns its place by describing the bidirectional capability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a debugging tool with no annotations and no output schema, the description is incomplete. It lacks information on behavioral traits, error conditions, output format, and how it fits within the broader Frida toolset. While concise, it doesn't provide enough context for safe and effective use in a dynamic debugging environment.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67% (2 out of 3 parameters have descriptions in the schema: 'address' and 'name'). The description adds minimal value beyond the schema by implying the tool can work bidirectionally (address to symbol or symbol to address), which helps interpret the parameters. However, it doesn't clarify the relationship between 'address' and 'name' (e.g., if they're mutually exclusive) or provide additional context for 'session_id', leaving some semantic gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Resolve debug symbol information from an address or find address from symbol name.' This specifies the verb ('resolve'/'find') and resource ('debug symbol information'/'address'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'frida_list_symbols' or 'frida_resolve_exports', which might have overlapping functionality in a Frida debugging context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an active Frida session), exclusions (e.g., not working on detached processes), or comparisons to sibling tools like 'frida_list_symbols' (which might list symbols without resolving addresses). Usage is implied by the functionality described 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'protections' but doesn't explain what the tool returns (e.g., list format, pagination), potential side effects, or error conditions. For a tool that likely interacts with process memory, 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.
Conciseness5/5Is 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. Every part of the sentence contributes directly to understanding the tool's function, 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of memory enumeration in a debugging context, no annotations, no output schema, and incomplete parameter documentation, the description is insufficient. It doesn't address return values, error handling, or behavioral nuances, leaving critical gaps for an AI agent to operate effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (only 'protection' has a description), and the description adds no additional parameter information beyond what's in the schema. It implies filtering by protection but doesn't clarify the 'session_id' parameter or provide examples beyond the schema's basic filter note. Baseline 3 is appropriate as the schema covers half the parameters adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Enumerate') and target ('memory ranges/maps in the process'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'frida_list_modules' or 'frida_memory_scan', which might have overlapping functionality in memory analysis contexts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 the many sibling tools related to memory (e.g., 'frida_memory_scan', 'frida_list_modules'), the description lacks context about use cases, prerequisites, or comparisons, leaving the agent to infer usage.
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 evaluates JavaScript in a Frida runtime, implying it's a read/write operation that could affect the process, but doesn't disclose critical traits like potential side effects (e.g., memory modification, crashes), authentication needs, rate limits, or error handling. The description is minimal and lacks behavioral context 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded, making it easy to understand at a glance. Every part of the sentence contributes to clarifying the purpose, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of evaluating arbitrary JavaScript in a runtime (a potentially powerful and risky operation), the description is incomplete. No annotations are provided to cover safety or behavioral traits, and there's no output schema to explain return values. The description lacks details on prerequisites (e.g., how to attach a process), error cases, or example usage, making it inadequate for safe and effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (only the 'code' parameter has a description). The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain what 'session_id' means or provide context for the JavaScript code. With partial schema coverage, the description doesn't compensate for the undocumented 'session_id' parameter, resulting in a baseline score of 3 due to the schema handling some documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Evaluate arbitrary JavaScript in the Frida runtime of an attached process.' It specifies the verb ('evaluate') and resource ('JavaScript'), and distinguishes it from siblings by focusing on runtime evaluation rather than attachment, inspection, or other operations. However, it doesn't explicitly differentiate from similar tools like frida_inject_script or frida_rpc_call, which might also involve code execution.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'attached process,' implying a prerequisite, but doesn't specify when to choose this over other code-execution tools like frida_inject_script or frida_rpc_call. There are no explicit when/when-not instructions or named alternatives, 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 states the tool retrieves 'detailed information' and 'system parameters,' but doesn't specify what kind of information (e.g., OS version, memory, connectivity), whether it's read-only (implied by 'Get'), or any potential side effects (e.g., if it requires device connectivity or permissions). 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Get detailed information about a specific device') and adds clarifying scope ('including system parameters'). There's no wasted verbiage, and it's appropriately sized for a simple retrieval tool. However, it could be slightly more structured by explicitly separating purpose from context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (device info retrieval), no annotations, and no output schema, the description is minimally adequate. It covers the what ('detailed information') and scope ('system parameters'), but lacks details on return format, error conditions, or prerequisites (e.g., device availability). For a tool with no structured output, more context on expected results would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters ('device_id' and 'device_type') fully described in the schema. The description adds no additional parameter semantics beyond implying the tool targets 'a specific device,' which aligns with the schema. Since the schema does the heavy lifting, 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get detailed information') and target ('about a specific device'), including the scope of information ('system parameters'). It distinguishes this from sibling tools like 'frida_list_devices' (which likely lists multiple devices) by focusing on detailed info for a specific device. However, it doesn't explicitly contrast with 'frida_get_process_info' which might provide similar detail for processes rather than devices.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. The description doesn't mention when this tool is appropriate (e.g., for device-level diagnostics vs. process-level operations) or when to prefer other tools like 'frida_list_devices' for enumeration or 'frida_get_process_info' for process details. Usage is implied by the tool name and description but not articulated.
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 'detailed info' but does not specify what that includes (e.g., memory usage, threads, permissions), whether it requires specific permissions or device connectivity, or potential side effects (e.g., if it pauses the process). This leaves significant gaps for a tool that interacts with system processes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is 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 states what the tool does and the key parameter usage, making it easy to parse quickly. There is no wasted verbiage or structural issues.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of process inspection in a tool like Frida, the description is incomplete. No annotations are provided to clarify safety or behavior, and there is no output schema to describe the returned 'detailed info'. The description lacks details on what information is retrieved, error conditions, or dependencies (e.g., device connectivity). For a tool with three parameters and no structured support, this is inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal meaning beyond the input schema. It clarifies that the 'process' parameter can be a 'name or PID', which is useful but already implied by the schema's description. With schema description coverage at 33% (only one parameter documented), the description does not compensate for undocumented parameters like 'device_id' and 'device_type', leaving their purposes unclear. The baseline is 3 due to the schema's partial coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get detailed info about a specific process by name or PID.' It specifies the verb ('Get'), resource ('detailed info'), and target ('specific process'), making the intent unambiguous. However, it does not differentiate from sibling tools like 'frida_get_process_info' or 'frida_list_processes', which likely serve related but distinct purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 sibling tools such as 'frida_get_process_info' (which might retrieve different or overlapping information) or 'frida_list_processes' (which likely lists processes without details). There are no exclusions, prerequisites, or context for usage beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- 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 can 'log calls, modify arguments, or change return values,' it fails to describe critical behaviors: whether hooking persists across sessions, potential performance impacts, error handling, or security implications. For a powerful hooking 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('Hook a specific function') and lists key capabilities without unnecessary elaboration. Every word earns its place, making it easy to parse quickly while conveying essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a function-hooking tool with no annotations and no output schema, the description is incomplete. It lacks information on return values, error conditions, side effects (e.g., whether hooks affect system stability), and dependencies like requiring a valid session_id. For a tool with five parameters and significant behavioral implications, this leaves too many unknowns for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 80%, with clear descriptions for most parameters (e.g., 'Module name (or null for main executable)'). The description adds minimal value beyond the schema by implying that 'on_enter' and 'on_leave' parameters are for JavaScript code to run at function entry/exit, but this is already suggested by the schema. Since the schema does most of the work, 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('hook', 'log', 'modify', 'change') and identifies the resource ('a specific function'). It distinguishes itself from siblings like frida_trace or frida_intercept_method by specifying the capability to modify arguments and return values, not just tracing. However, it doesn't explicitly differentiate from frida_java_hook_method or frida_objc_hook_method, which are similar but language-specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 like needing an active Frida session, nor does it compare with siblings such as frida_trace (for tracing only) or frida_java_hook_method (for Java-specific hooking). Without this context, an agent might misuse it in inappropriate 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?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions injection but doesn't disclose critical traits: whether this requires elevated privileges, if it's destructive to the process, potential side effects (e.g., process instability), or error handling. The description is functional but lacks transparency about risks and 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with zero wasted words. It front-loads the core action and resource, making it immediately understandable without unnecessary elaboration. Every word earns its place, achieving optimal conciseness for the stated purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (library injection into processes), lack of annotations, no output schema, and incomplete parameter coverage, the description is inadequate. It doesn't address safety, permissions, return values, or error conditions, leaving significant gaps for an AI agent to understand how to use this tool effectively in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67% (4 of 6 parameters have descriptions), so the baseline is 3. The description adds no parameter-specific semantics beyond implying 'library_path' refers to a shared library file. It doesn't explain parameter interactions (e.g., how 'entrypoint' and 'data' relate) or provide examples, relying on the schema for most documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('inject') and target ('shared library into target process'), specifying the file types (.so/.dll/.dylib). It distinguishes from sibling tools like frida_inject_script (which injects scripts rather than libraries) by focusing on library injection. However, it doesn't explicitly contrast with all siblings, keeping it at 4 rather than 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 frida_inject_script or frida_spawn. It lacks context about prerequisites (e.g., process must be running), exclusions, or typical use cases, offering only a basic functional statement without 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 states the tool injects and runs a script, implying mutation and potential side effects, but doesn't disclose critical behaviors such as permission requirements, whether it's reversible (e.g., via frida_detach or frida_unload_script), error handling, or performance impacts. The mention of script capabilities (e.g., modify behavior) hints at destructiveness but lacks explicit warnings or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, with the core purpose stated in the first sentence and additional context in the second. Both sentences earn their place by clarifying the tool's action and script capabilities. However, it could be slightly more structured by explicitly mentioning prerequisites or linking to sibling tools.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a script injection tool with no annotations and no output schema, the description is incomplete. It lacks information on behavioral traits (e.g., side effects, error handling), usage context (e.g., dependencies on other tools), and output details (e.g., what happens after injection, message capture behavior). For a mutation tool in a security context, this leaves significant gaps for an agent to operate safely and effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, providing clear details for all parameters (session_id, script, on_message). The description adds no additional parameter semantics beyond what's in the schema, such as script syntax examples or session_id validation rules. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema adequately documents parameters without extra description value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Inject and run a Frida JavaScript script in a process.' It specifies the action (inject and run), target (process), and technology (Frida JavaScript script), distinguishing it from siblings like frida_attach (which attaches to a process) or frida_hook_function (which hooks specific functions). However, it doesn't explicitly differentiate from frida_inject_library, which also involves injection but with libraries instead of scripts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 what the script can do (e.g., hook functions, intercept calls), but doesn't specify prerequisites (e.g., requires an attached session via frida_attach), exclusions, or comparisons to similar tools like frida_hook_function or frida_inject_library. This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- 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 states the tool intercepts methods but doesn't explain what interception entails (e.g., modifies runtime behavior, requires specific permissions, may affect app stability), the scope of interception (e.g., system-wide or process-specific), or any side effects. 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for the tool's complexity and front-loads the core purpose immediately, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (method interception is a powerful, potentially destructive operation), lack of annotations, and absence of an output schema, the description is insufficient. It doesn't cover behavioral implications, error conditions, return values, or safety considerations, leaving critical gaps for an agent to use this tool effectively and safely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 75% (3 of 4 parameters have descriptions), providing a solid baseline. The description adds no additional parameter semantics beyond what the schema already documents (class_name, method_name, implementation, session_id). It doesn't clarify parameter relationships, format requirements, or provide examples, so it meets but doesn't exceed the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Intercept') and target ('Objective-C method (iOS) or Java method (Android)'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'frida_hook_function', 'frida_objc_hook_method', or 'frida_java_hook_method', which appear to offer similar hooking/interception capabilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 the various hooking-related sibling tools. It doesn't mention prerequisites (e.g., needing an active Frida session), specific use cases, or exclusions, leaving the agent with insufficient context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- 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 the return type ('class names') and optional filtering, but lacks critical behavioral details: whether this is a read-only operation, potential performance impact, permissions required, or error conditions. 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first clause, followed by return details. It uses two concise sentences with zero wasted words, making it easy to parse quickly. Every sentence earns its place by adding essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 2 parameters with only 50% schema coverage, the description is incomplete. It doesn't address behavioral traits (e.g., safety, performance), output format details beyond 'class names', or error handling. For a tool in a complex domain like Frida with many siblings, more context is needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (only 'pattern' has a description). The description adds minimal value by mentioning 'optional pattern to filter classes', which aligns with the schema's 'pattern' parameter. However, it doesn't explain 'session_id' or provide additional context beyond what's implied. With partial schema coverage, the description doesn't fully compensate but meets the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Enumerate all loaded Java classes (Android)' with a specific verb ('enumerate') and resource ('loaded Java classes'), plus platform context ('Android'). It distinguishes from some siblings like 'frida_java_find_instances' but not all Java-related tools (e.g., 'frida_java_hook_method').
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. While it mentions an optional pattern for filtering, it doesn't specify scenarios where this is preferred over other enumeration tools (e.g., 'frida_objc_enumerate_classes' for Objective-C) or when to avoid it. Usage is implied but not clearly defined.
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 'live instances on the heap' and implies a read-only operation, but doesn't specify critical details like whether this requires specific permissions, how results are returned (e.g., format, pagination), potential performance impacts, or error conditions. For a tool with no 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that clearly states the tool's purpose without unnecessary words. It's front-loaded with the core action and includes essential context ('on the heap (Android)'). Every part of the sentence 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a debugging/memory inspection tool), lack of annotations, no output schema, and low schema description coverage (33%), the description is incomplete. It doesn't cover behavioral aspects like return format, error handling, or prerequisites (e.g., needing an attached session), leaving significant gaps for the agent to operate effectively in a Frida context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 33% (only 'class_name' has a description), and the description doesn't add any parameter-specific information beyond what's in the schema. It implies parameters like 'class_name' and possibly 'limit' through context, but doesn't explain their semantics, such as what 'session_id' refers to or how 'limit' affects results. With low schema coverage, the description fails to compensate adequately, resulting in a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Find live instances of a Java class on the heap (Android).' It specifies the verb ('Find'), resource ('live instances of a Java class'), and context ('on the heap (Android)'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'frida_java_enumerate_classes' or 'frida_objc_find_instances', which is why it doesn't achieve 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 Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an active Frida session), exclusions, or comparisons to similar tools like 'frida_java_enumerate_classes' (which lists classes) or 'frida_objc_find_instances' (for Objective-C). This lack of contextual usage information leaves the agent to infer when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- 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 logging and modification capabilities, but lacks critical behavioral details: required permissions, side effects (e.g., impact on app stability), error handling, or output format. For a hooking tool with potential destructive effects, 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single sentence with zero waste. It's front-loaded with the core purpose and efficiently lists key features. Every word earns its place, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (hooking with modification capabilities), lack of annotations, no output schema, and incomplete parameter documentation, the description is inadequate. It doesn't address safety, output format, or error conditions, leaving significant gaps for an AI agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 57%, with 4 of 7 parameters having descriptions. The description adds minimal value beyond the schema—it hints at 'log calls, modify args/return values,' which loosely relates to 'log_args', 'log_return', and 'modify_return' parameters. However, it doesn't explain parameter interactions or provide additional context to compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Hook a Java method (Android). Log calls, modify args/return values.' It specifies the verb (hook), resource (Java method), and platform (Android), and outlines key capabilities. However, it doesn't explicitly differentiate from sibling tools like 'frida_hook_function' or 'frida_objc_hook_method' beyond mentioning Java/Android context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 (e.g., 'frida_hook_function', 'frida_intercept_method', 'frida_objc_hook_method'), there's no indication of context, prerequisites, or exclusions. Usage is implied by the name and description 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?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the action ('Load a DEX file dynamically') but doesn't disclose critical traits like whether this requires specific permissions, if it's destructive to the runtime, potential side effects, or error handling. 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.
Conciseness5/5Is 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 redundancy. It's front-loaded and wastes no words, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that performs a dynamic loading operation (likely a mutation) with no annotations and no output schema, the description is insufficient. It lacks details on behavioral implications, return values, error conditions, and how it fits within the Frida ecosystem, leaving significant gaps for an AI agent to operate safely and effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67% (2 out of 3 parameters have descriptions), so the schema provides moderate documentation. The description adds no parameter-specific information beyond what's in the schema, such as explaining the purpose of 'class_name' or format examples for 'dex_path'. Baseline 3 is appropriate given the schema's partial coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Load') and target ('DEX file dynamically into the Android runtime'), making the purpose understandable. However, it doesn't differentiate from sibling tools like frida_inject_library or frida_inject_script that also involve loading code, so it lacks 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 Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an active Frida session), exclusions, or comparisons to similar tools like frida_inject_script for script loading, 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 states the action ('Kill') but doesn't explain critical traits: whether this requires elevated permissions, if it's destructive (likely yes, but unstated), potential side effects (e.g., process termination without cleanup), or error conditions (e.g., invalid PID handling). 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with zero wasted words. It's front-loaded with the core action and efficiently communicates the primary purpose without unnecessary elaboration, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations, low schema coverage, and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., destructiveness, permissions), parameter usage beyond 'pid', and expected outcomes or errors. This makes it inadequate for safe and effective tool invocation in a complex environment like Frida.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is low (33%), with only 'pid' documented. The description adds no parameter details beyond implying 'pid' is used for killing, which the schema already covers. It doesn't explain 'device_id' or 'device_type' (e.g., their roles in targeting processes on different devices), failing to compensate for the coverage gap. The baseline is 3 due to the single documented parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Kill') and target ('a process by PID'), which is specific and unambiguous. It distinguishes itself from siblings like frida_detach or frida_resume by focusing on termination rather than disconnection or continuation. However, it doesn't explicitly contrast with all sibling tools, keeping it from 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 Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an attached process first), exclusions (e.g., not for system processes), or related tools like frida_detach for graceful disconnection. This lack of context leaves the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- 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 what the tool does but doesn't cover important behavioral aspects like whether it's read-only, what permissions are required, potential side effects, or the format of the returned data. For a 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently communicates the core function without any wasted words. It's appropriately sized for a simple 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, and incomplete parameter documentation (50% coverage), the description is insufficient. It doesn't explain what the tool returns, what format the exports are listed in, or any behavioral characteristics. Given the complexity of Frida tools and the lack of structured documentation, this description leaves too many gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (only 'module' has a description). The description doesn't add any parameter semantics beyond what's in the schema - it doesn't explain what 'session_id' represents or provide additional context about the 'module' parameter. With moderate 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and resource 'exported functions from a module', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'frida_list_imports' or 'frida_list_symbols', 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 Guidelines2/5Does 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 'frida_list_imports' or 'frida_list_modules', nor does it mention prerequisites such as needing an active Frida session. It's a basic statement of function with no contextual usage information.
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 but only states the action without detailing traits like whether it's read-only, potential side effects, performance implications, or output format. It lacks context on what 'imported functions' means in the Frida framework, leaving behavioral aspects unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is 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 front-loaded and wastes no space, making it easy to parse quickly while conveying the essential action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of Frida tools and the lack of annotations and output schema, the description is insufficient. It doesn't explain what 'imported functions' entail, how results are returned, or any limitations, leaving significant gaps for an AI agent to understand the tool's full context and usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter-specific information beyond what the schema provides. With 50% schema description coverage (only 'module' has a description), the description doesn't compensate for the undocumented 'session_id' parameter. Since schema coverage is moderate, the baseline score of 3 applies, as the description doesn't enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('List') and resource ('imported functions in a module'), making it immediately understandable. However, it doesn't explicitly differentiate from its sibling 'frida_list_exports', which likely lists exported functions instead of imported ones, missing an opportunity for clearer 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 Guidelines2/5Does 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 'frida_list_exports' or 'frida_list_modules', nor does it mention any prerequisites or context for usage. It simply states what the tool does without indicating appropriate scenarios or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- 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 states the tool lists debug symbols but does not disclose behavioral traits like whether it requires an active Frida session, potential performance impacts, error handling, or output format. This is a significant gap 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.
Conciseness5/5Is 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 and directly conveys the core function, 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of Frida debugging tools, no annotations, and no output schema, the description is incomplete. It lacks details on session requirements, symbol types, output structure, and error conditions, making it inadequate for safe and effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67% (2 out of 3 parameters have descriptions). The description mentions 'module' but does not add meaning beyond the schema's 'Module name' description. It implies filtering via 'filter' but provides no extra details. With moderate schema coverage, the description offers minimal additional value, aligning with the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List') and target resource ('debug symbols from a module'), making the purpose understandable. However, it does not differentiate from sibling tools like 'frida_list_exports' or 'frida_list_imports', which also list symbols but with different scopes or types, so it 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 Guidelines2/5Does 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 'frida_list_exports' for exported symbols or 'frida_list_imports' for imported symbols. There is no mention of prerequisites, context, or exclusions, 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?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the return value ('Returns the address of allocated memory'), which is helpful, but doesn't mention critical behaviors: whether allocation persists, permission requirements, potential side effects (like process instability), error conditions, or that it's a write operation (implied but not explicit). For a low-level memory manipulation tool, 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with zero waste: the first states the action and target, the second states the return value. Perfectly front-loaded with the core purpose, appropriately sized for the tool's complexity, and every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-level memory allocation tool with no annotations, no output schema, and incomplete parameter documentation, the description is inadequate. It doesn't address safety concerns, error handling, persistence of allocations, or integration with other memory operations. Given the technical complexity and potential risks of memory manipulation, more context is needed despite the concise structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67% (2 of 3 parameters have descriptions). The description adds no additional parameter information beyond what's in the schema. With moderate schema coverage, the baseline is 3 - the description neither compensates for the undocumented 'session_id' parameter nor adds meaningful context about parameter interactions or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Allocate memory') and target ('in the target process'), with a specific verb+resource combination. It distinguishes from obvious siblings like frida_memory_read/write/protect by focusing on allocation rather than manipulation. However, it doesn't explicitly differentiate from all memory-related tools in the extensive sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. With many sibling tools (including frida_memory_protect, frida_memory_read, frida_memory_write), the description doesn't indicate prerequisites (e.g., requires an attached session), appropriate contexts, or what alternatives exist for different memory operations.
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 'Change memory protection/permissions' implies a mutation operation, it doesn't specify critical details like required permissions, potential side effects (e.g., crashing if invalid), or error handling. For a low-level memory tool with zero annotation coverage, this is a significant gap in safety and 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Change memory protection/permissions for a memory region.' It's front-loaded with the core action and resource, with zero wasted words. This makes it easy to parse quickly, though it could benefit from more detail given the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (low-level memory operation), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like safety, prerequisites, or return values, which are crucial for an agent to use this tool correctly. The high schema coverage helps, but overall context is insufficient for such a sensitive operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 75% (3 of 4 parameters have descriptions), so the schema does most of the work. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't clarify format for 'address' or valid values for 'protection'). With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't detract either.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Change memory protection/permissions for a memory region.' It specifies the verb ('change') and resource ('memory protection/permissions'), making it easy to understand. However, it doesn't explicitly differentiate from siblings like frida_memory_alloc, frida_memory_read, or frida_memory_write, which handle different memory operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an active session), exclusions, or comparisons to sibling tools like frida_memory_alloc (for allocation) or frida_memory_write (for writing). This leaves the agent to infer usage from context 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 the full burden of behavioral disclosure. It states the core action but lacks critical details: it doesn't mention permissions needed (e.g., debugger access), potential risks (e.g., crashing the target process), rate limits, or what the output looks like (e.g., raw bytes vs. formatted data). For a low-level memory operation, 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a straightforward tool, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of memory operations and the lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like safety, permissions, or output format, leaving the agent with insufficient context to use the tool effectively in a Frida debugging environment.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 67% (2 out of 3 parameters have descriptions), so the baseline is 3. The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain the 'session_id' purpose, address format constraints beyond hex, or size limitations (e.g., maximum bytes).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Read bytes') and target ('from a specific memory address'), providing a specific verb+resource combination. It distinguishes itself from sibling tools like 'frida_memory_write' by focusing on reading rather than writing, though it doesn't explicitly differentiate from other memory-related tools like 'frida_memory_scan'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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., requiring an active Frida session), compare it to similar tools like 'frida_memory_scan' for broader searches, or specify appropriate contexts (e.g., debugging vs. forensics).
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 without behavioral details. It doesn't disclose whether this is a read-only operation, potential performance impacts, memory usage, or output format (e.g., list of addresses). This leaves significant gaps for a memory scanning tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is 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 appropriately sized for the tool's complexity, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (memory scanning with 3 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects, output expectations, or usage context, leaving the agent with insufficient information to use the tool effectively beyond basic invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67% (2 of 3 parameters have descriptions), providing a baseline. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain 'session_id' context or 'pattern' format variations), so it doesn't compensate for the partial coverage but doesn't detract either.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('scan') and resource ('process memory') with the specific action ('for a pattern'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'frida_search_strings' or 'frida_enumerate_ranges' that also involve memory operations, preventing 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 Guidelines2/5Does 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 'frida_search_strings' for string searches or 'frida_enumerate_ranges' for memory region listing. It lacks context about prerequisites (e.g., requiring an attached session) or exclusions, 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the write operation but doesn't mention critical aspects like required permissions (e.g., memory access rights), potential side effects (e.g., crashing the target process), or error conditions. This is inadequate for a low-level memory manipulation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is 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 sized and front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex, potentially destructive memory write operation with no annotations and no output schema, the description is insufficient. It lacks information about behavioral traits (e.g., safety, side effects), return values, or error handling, leaving significant gaps for an AI agent to use this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67% (2 out of 3 parameters have descriptions), so the baseline is 3. The description adds no additional parameter information beyond what's in the schema (e.g., it doesn't explain the 'session_id' parameter or provide context for 'address' and 'data' formats).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Write bytes') and target ('to a specific memory address'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'frida_memory_read' or other memory manipulation tools, which would be needed for 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 Guidelines2/5Does 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 'frida_memory_read' or 'frida_memory_alloc', nor does it mention prerequisites (e.g., requiring an active session). There's only an implied context of memory manipulation without explicit usage boundaries.
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 the action ('Call a native function') but lacks critical details: it doesn't specify if this is a read-only or destructive operation, what permissions or session states are required, potential side effects (e.g., crashing the target process), error handling, or return format. For a low-level tool with no 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded: two sentences that directly state the tool's core functionality and key parameters. There is no wasted language, and every word contributes to understanding the tool's purpose and basic usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (low-level native function calling), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral risks, session dependencies, error scenarios, or output structure, leaving critical gaps for safe and effective use. The high schema coverage helps with parameters but doesn't compensate for missing operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal value beyond the input schema, which has 80% coverage. It mentions 'Specify return type and argument types,' which aligns with the schema's 'return_type' and 'arg_types' parameters but doesn't provide additional context like type syntax examples or validation rules. With high schema coverage, the baseline is 3, and the description doesn't significantly enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Call a native function directly by address or name.' It specifies the verb ('Call') and resource ('native function'), and distinguishes it from siblings like frida_hook_function or frida_trace by focusing on direct invocation rather than interception or tracing. However, it doesn't explicitly differentiate from frida_java_call_method or frida_objc_call_method, which are higher-level language-specific tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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., requiring an active Frida session), compare it to siblings like frida_hook_function for hooking instead of calling, or specify scenarios where direct native function calls are appropriate (e.g., low-level debugging vs. high-level scripting).
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 lacks behavioral details. It doesn't disclose critical traits like potential side effects (e.g., method execution may modify state), error handling, performance impact, or return format. The phrase 'Call an Objective-C method' implies a mutation, but specifics like permissions or rate limits are omitted, leaving gaps for safe agent use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is 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 function and context. It's front-loaded with the core action and avoids redundancy, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (calling methods with potential side effects), no annotations, no output schema, and incomplete parameter documentation, the description is inadequate. It doesn't cover behavioral risks, return values, or usage context, leaving the agent under-informed for safe and effective invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (3 of 6 parameters have descriptions), so the description must compensate but adds no parameter details beyond the schema. It mentions 'class or instance' which hints at 'instance_handle' and 'static' usage, but doesn't explain their interplay or provide examples. Baseline 3 is appropriate as the schema does partial work, but the description offers minimal extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Call an Objective-C method') and target ('on a class or instance'), specifying the platform context ('iOS/macOS'). It distinguishes from siblings like 'frida_java_call_method' by focusing on Objective-C, but doesn't explicitly differentiate from similar tools like 'frida_objc_hook_method' beyond the verb 'call' vs. 'hook'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an active Frida session), compare to siblings like 'frida_objc_hook_method' for hooking instead of calling, or specify scenarios (e.g., debugging, testing). The description only states what it does, not when to apply 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 the full burden of behavioral disclosure. It states what the tool does but lacks critical behavioral details: it doesn't mention that this is a read-only operation (safe for enumeration), doesn't describe the return format (e.g., list of class names or objects), and doesn't cover potential side effects like performance impact or session requirements. The description is minimal and misses key 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single sentence that directly states the tool's function. It's front-loaded with the core action and includes relevant platform context. There's no wasted verbiage, making it efficient for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (enumeration in a dynamic analysis context), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like safety, return format, or session dependencies, which are crucial for an AI agent to use it correctly. The minimal description leaves significant gaps in understanding how the tool operates.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (only 'pattern' has a description). The description adds no parameter-specific information beyond what's implied by the tool name (e.g., 'session_id' is required for Frida operations). It doesn't explain parameter usage, such as how 'pattern' filters classes or what format 'session_id' should be. With moderate schema coverage, the description provides minimal additional value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does 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 ('Enumerate') and resource ('all loaded Objective-C classes'), and specifies the target platforms ('iOS/macOS'). However, it doesn't explicitly differentiate from sibling tools like 'frida_java_enumerate_classes' or 'frida_list_modules', which serve similar enumeration purposes for different targets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'frida_java_enumerate_classes' for Java classes or 'frida_list_modules' for module enumeration, nor does it specify prerequisites such as needing an active Frida session. 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('push/upload') which implies a write operation, but doesn't cover critical aspects like required permissions, whether it overwrites existing files, error handling, or performance characteristics (e.g., file size limits). This leaves significant gaps for safe and effective use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is 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 front-loaded with the core action, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a file upload operation with 4 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., side effects, error conditions), parameter usage, and expected outcomes, which are essential for an agent to invoke this tool correctly in a dynamic environment.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (two parameters have descriptions, two do not). The description adds no additional parameter information beyond what's in the schema—it doesn't explain the meaning of 'device_id' or 'device_type', or provide examples for paths. Since schema coverage is moderate, the baseline score of 3 reflects that the description doesn't compensate for the gaps but doesn't worsen them either.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('push/upload') and resource ('a file to the device'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from its sibling 'frida_pull_file' (which presumably downloads files), though the distinction is implied through the verb choice.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 the description implies it's for file transfer to a device, it doesn't mention prerequisites (e.g., device connectivity), constraints, or when to choose other tools like 'frida_pull_file' for reverse operations.
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 'finds functions' but doesn't describe what happens operationally: e.g., whether this is a read-only search, if it requires an active session, potential performance impacts, or error conditions. The mention of 'ApiResolver' hints at a specific Frida feature but lacks detail on 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Find functions matching a pattern using ApiResolver. Supports wildcards.' It's front-loaded with the core purpose and includes a useful detail 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of Frida tools (dynamic instrumentation), no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't cover behavioral aspects like safety, performance, or error handling, and leaves key parameters unexplained. For a tool in this context, more detail is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 33% (only the 'query' parameter has a description), so the description must compensate. It adds some value by mentioning 'wildcards' and implying pattern matching, which aligns with the query parameter's example. However, it doesn't explain the 'session_id' or 'limit' parameters, leaving gaps in understanding their roles and constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Find functions matching a pattern using ApiResolver. Supports wildcards.' It specifies the verb ('Find'), resource ('functions'), and mechanism ('ApiResolver'), which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'frida_list_exports' or 'frida_list_symbols', which appear related, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'ApiResolver' and 'wildcards', but doesn't explain context, prerequisites, or exclusions. With many sibling tools in the Frida ecosystem, this lack of differentiation leaves the agent guessing about appropriate use cases.
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 calling an RPC function but does not specify permissions needed, side effects, error handling, or response format. For a tool that likely interacts with injected scripts, 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It is front-loaded and efficiently conveys the core purpose without unnecessary details, 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of calling RPC functions in injected scripts, no annotations, and no output schema, the description is incomplete. It lacks information on behavioral traits, error cases, and what the tool returns, which is crucial for effective use in this context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 (script_id, method, args). The description does not add any extra meaning beyond what the schema provides, such as examples or constraints, but the baseline is 3 since the schema handles the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Call') and target ('exported RPC function in an injected script'), making the purpose understandable. However, it does not explicitly differentiate this tool from sibling tools like 'frida_evaluate' or 'frida_native_function', which might also involve calling functions, so it lacks 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 Guidelines2/5Does 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 like 'frida_evaluate' or 'frida_java_call_method', there is no indication of context, prerequisites, or exclusions, 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 full burden for behavioral disclosure. While 'search' implies a read operation, it doesn't specify whether this requires special permissions, whether it's safe to use on live processes, what happens when the limit is reached, or what format the results take. The description lacks crucial behavioral context for a memory operation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a straightforward 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a memory search tool with 4 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what 'session_id' represents, how results are returned, whether the search is destructive, or any performance considerations. The context demands more completeness for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 25% (only the 'pattern' parameter has a description). The tool description doesn't mention any parameters, so it adds no semantic value beyond what the sparse schema provides. The baseline is 3 since the schema does exist, but the description fails to compensate for the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('search for strings') and target ('in process memory'), providing a specific verb+resource combination. However, it doesn't differentiate from similar sibling tools like 'frida_memory_scan' or 'frida_memory_read', which also operate on process memory.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 also interact with process memory (frida_memory_scan, frida_memory_read, frida_enumerate_ranges), there's no indication of when string searching is appropriate versus other memory operations.
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 that the tool 'returns call logs with arguments and return values', which gives some insight into output behavior. However, it lacks critical details such as whether this is a read-only or destructive operation, performance implications, rate limits, or error handling. For a tool with six parameters and no annotations, 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded, consisting of only two sentences that directly state the tool's purpose and return value. Every word earns its place, with no redundant or vague language. This makes it easy for an AI agent to quickly grasp the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (six parameters, no annotations, no output schema, and many sibling tools), the description is incomplete. It lacks usage guidelines, behavioral details, and output specifications. While concise, it does not provide enough context for an AI agent to fully understand how and when to use this tool effectively in the broader Frida toolset.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not add any parameter-specific information beyond what the input schema provides. With a schema description coverage of 67%, the schema documents most parameters well (e.g., 'target', 'include', 'duration'), but parameters like 'device_id' and 'device_type' have limited or no descriptions in the schema. The description does not compensate for these gaps, so it meets the baseline of 3 where the schema does the heavy lifting but doesn't enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does 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 ('trace') and resource ('function calls matching a pattern'), and mentions the return value ('call logs with arguments and return values'). However, it does not explicitly differentiate from sibling tools like 'frida_stalker_trace' or 'frida_hook_function', which may have overlapping or related functionality in the Frida ecosystem.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 available (e.g., 'frida_stalker_trace', 'frida_hook_function'), there is no indication of specific use cases, prerequisites, or exclusions. This lack of context makes it difficult for an AI agent to choose appropriately among similar 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 full burden. It states the tool unloads a script but doesn't disclose behavioral traits such as whether this is destructive (likely yes, as unloading implies removal), what permissions are required, whether it's synchronous/asynchronous, or what happens on failure (e.g., 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words. It's front-loaded with the core action ('Unload') and efficiently conveys the essential purpose without unnecessary elaboration, 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.
Completeness2/5Given 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 potential side effects), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like safety, error conditions, or return values, leaving the agent with insufficient context for reliable invocation in a dynamic environment like Frida scripting.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'script_id' documented as 'Script ID from frida_inject_script'. The description adds no additional meaning beyond this, such as format examples or validation rules. 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Unload') and target ('a previously injected script'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like frida_detach or frida_kill that might also terminate script-related processes, leaving some ambiguity about when to choose this specific unloading operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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., that a script must be currently loaded), exclusions, or relationships to siblings like frida_detach (which might detach from a process) or frida_inject_script (which injects scripts). This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- 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 the return format (PID, name, parameters) but lacks critical behavioral details: whether this requires device connection, permissions, potential side effects, rate limits, or error conditions. For a tool interacting with devices, 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with zero waste: first states the action and scope, second specifies the 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.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 2 parameters, no annotations, and no output schema, the description is minimally adequate. It covers purpose and return format but lacks behavioral context, usage guidance, and parameter details. Given the complexity of device interaction tools, it should provide more operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (device_id has description, device_type lacks description). The description doesn't add any parameter-specific information beyond what's in the schema. With moderate schema coverage, baseline 3 is appropriate as the description doesn't compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and resource 'running processes on a device', specifying what information is returned (PID, name, parameters). It distinguishes from siblings like frida_list_applications (apps vs processes) and frida_get_process (single vs all processes), though not explicitly named.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 frida_list_applications or frida_get_process. The description implies it's for listing all processes, but doesn't specify use cases, prerequisites, 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the tool is 'very powerful but heavy,' which hints at performance impact, but doesn't specify critical behaviors like whether it requires specific permissions, if it's destructive (e.g., alters execution), what the output format is, or any rate limits. This leaves significant gaps for an agent to understand how to use it safely and effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded, consisting of just one sentence: 'Trace execution at instruction/block level using Stalker. Very powerful but heavy.' Every word earns its place by conveying purpose and a key behavioral trait without any waste or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a low-level tracing tool with no annotations and no output schema, the description is incomplete. It lacks details on what the tool returns, how to interpret results, potential side effects (e.g., performance degradation), or error conditions. For a powerful tool like this, more context is needed to guide an agent effectively, especially without structured fields to fill the gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 75%, with three of four parameters having descriptions in the schema (thread_id, events, duration). The description adds no additional parameter semantics beyond what's in the schema, such as explaining the 'session_id' (which lacks a schema description) or providing examples for the 'events' array. Since the schema does most of the work, the baseline score of 3 is appropriate, but the description doesn't compensate for the 25% coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Trace execution at instruction/block level using Stalker.' It specifies the verb ('trace') and resource ('execution'), and distinguishes it from the simpler 'frida_trace' sibling tool by emphasizing its power and heaviness. However, it doesn't explicitly differentiate from all other sibling tools like 'frida_hook_function' or 'frida_intercept_method' that might also involve tracing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some implied usage guidance by noting it's 'very powerful but heavy,' suggesting it should be used for detailed tracing when performance overhead is acceptable. However, it doesn't explicitly state when to use this tool versus alternatives like 'frida_trace' (which likely offers lighter tracing) or other debugging tools in the sibling list, nor does it mention any prerequisites 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. It mentions 'compile' and 'useful for complex agents with dependencies,' which implies a build/transformation process, but doesn't disclose behavioral traits like whether it's read-only or destructive, error handling, performance implications, or output format. For a compilation 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: two concise sentences that directly state the purpose and usage context without any wasted words. Every sentence earns its place by providing essential information efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (compilation with dependencies), no annotations, and no output schema, the description is moderately complete. It covers the basic purpose and context but lacks details on behavioral traits, error handling, or output specifics. It's adequate as a minimum viable description but has clear gaps for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 (source_code and output_filename) with descriptions. The description adds no additional parameter semantics beyond what's in the schema. According to the rules, with high schema coverage, the baseline score is 3, as the description doesn't need to compensate but also doesn't add value here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Compile a Frida agent (JavaScript/TypeScript) using frida-compile.' It specifies the verb ('compile'), resource ('Frida agent'), and technology ('frida-compile'), making it distinct from sibling tools like frida_evaluate or frida_inject_script. However, it doesn't explicitly differentiate from all siblings, as some might also involve compilation or processing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage guidance: 'Useful for complex agents with dependencies.' This suggests when to use it (for complex agents) but doesn't explicitly state when not to use it or name alternatives. It lacks clear exclusions or comparisons to sibling tools, such as frida_evaluate for simpler scripts.
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 of behavioral disclosure. It describes the action (listing devices) and return format (device ID, name, type), but lacks details on permissions, rate limits, or error handling. For a read-only tool with zero annotation coverage, this is adequate but leaves 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.
Conciseness5/5Is 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 available Frida devices') and includes essential details (scope and return values) without redundancy. Every word earns its place, making it highly concise and well-structured for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is nearly complete: it states the action, scope, and return format. However, it lacks behavioral details like error cases or performance considerations, which would be beneficial for full context. For a low-complexity tool, this is sufficient but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so no parameter information is needed. The description does not add param details, which is appropriate, but it compensates by explaining the return values, enhancing understanding beyond the empty schema. Baseline is 4 for zero-param tools when description provides useful context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('List all available Frida devices') and resource ('devices'), distinguishing it from siblings like frida_get_device_info or frida_get_process_info by focusing on enumeration rather than detailed information retrieval. It explicitly mentions the scope ('local, USB, remote') and return values ('device ID, name, and type'), making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for discovering available devices before operations like attaching or spawning, as seen in sibling tools (e.g., frida_attach, frida_spawn), but does not explicitly state when to use this tool versus alternatives. No exclusions or specific contexts are provided, leaving usage inferred from the tool's purpose rather than direct guidance.
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: the process starts in suspended state (not running), returns a PID (output format), and requires frida_resume to activate. However, it doesn't mention permissions needed, potential side effects, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with zero waste. The first sentence states the core action and output. The second provides crucial usage guidance. Every word earns its place, and information is front-loaded appropriately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a process-spawning tool with no annotations and no output schema, the description covers the basic operation and relationship to frida_resume. However, it lacks details about error handling, security implications, or what happens to the spawned process if not resumed. Given the complexity and lack of structured data, it's adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67% (4 of 6 parameters have descriptions). The description adds no parameter-specific information beyond what's in the schema. With moderate schema coverage, the baseline is 3 since the schema does most of the work, but the description doesn't compensate for the undocumented parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Spawn a new process in suspended state') and resource (process), and distinguishes it from siblings by explicitly mentioning the complementary tool 'frida_resume'. It goes beyond the tool name by specifying the suspended state.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does 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 ('Spawn a new process in suspended state') and when to use an alternative ('Use frida_resume to start it'), clearly differentiating it from other process-related tools like frida_attach or frida_kill.
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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