MCP RE Server

Server Quality Checklist

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

Latest release: v1.0.0
Disambiguation4/5
Most tools target distinct resource+action pairs, but there is some overlap among binary analysis tools (analyze_binary, ghidra_analyze, radare2_analyze, pestudio_analyze) and between analyze_project and get_architecture_advice. Descriptions help differentiate them, so ambiguity is limited.
Naming Consistency2/5
Naming conventions are inconsistent: verb_noun (analyze_project, execute_command), tool_prefix_action (ghidra_analyze, yara_scan), and noun_phrase (network_analysis, memory_forensics) are mixed. While tool_prefix is consistent within the RE tools, overall there is no single predictable pattern.
Tool Count3/5
With 22 tools, the server is on the heavy side, and the mix of project development tools (scaffold_project, add_docker) with reverse engineering tools makes the scope feel broad. The count is within the 16-25 range but feels over-scoped for a supposed 'RE Server'.
Completeness4/5
The reverse engineering domain is well-covered: static analysis, dynamic analysis, memory forensics, network analysis, YARA scanning, and debugging. Minor gaps exist (e.g., no dedicated disassembly tool), but Ghidra/Radare2 handle that. The extra non-RE tools don't detract from RE completeness.
Average 2.8/5 across 22 of 22 tools scored. Lowest: 1.5/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

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

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

How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of explaining behavior. It merely states 'Read a file' with no disclosure of return format, side effects, or limitations, leaving the agent completely uninformed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is brief, it is under-specified rather than concise. The single sentence provides no informative value, so it fails to earn its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is inadequate for even a simple tool. It gives no information about what reading a file involves, and the presence of many sibling tools makes the lack of contextual distinction a serious deficiency.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, yet the description does not compensate. It does not mention the 'path' parameter or clarify its expected format, making the parameter semantic gap entirely unaddressed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description is a tautology: it simply restates the tool name in plain language without adding specificity. It does not distinguish read_file from siblings like write_file or list_directory, and offers no detail about file types or source.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided for when to use this tool versus alternatives. The description lacks any context, prerequisites, or examples that would help an agent decide between read_file and other sibling tools.
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, the description bears full responsibility for disclosing behavior. It only says 'Execute a shell command' with no details about side effects, security implications, output, or environment. This is dangerously under-specified for a command execution tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short, but it is not effective conciseness—it lacks substance. Every word is minimal but missing critical context. It reads more like a label than a helpful description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that executes arbitrary shell commands, the description is completely inadequate. It provides no information about shell type, environment, output handling, or potential risks, and the schema is equally sparse.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and neither the schema nor the description explains the purpose of 'command' or 'cwd'. The description adds no meaning beyond the parameter names themselves.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose clearly: 'Execute a shell command'. It uses a specific verb and resource, and while it doesn't explicitly distinguish from siblings, the siblings are specialized analysis tools, making this generic execution tool distinct enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of use cases, prerequisites, or exclusions. The agent is left guessing about the appropriate 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 must disclose behavioral traits itself. It states it generates a scaffold with Docker and tests, but does not reveal side effects (e.g., file system writes), required permissions, reversibility, or return values. This is insufficient for a mutation-oriented tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no extraneous information. It is front-loaded and straightforward, though it under-specifies details that are penalized in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, no output schema, and minimal parameter info, this description is severely incomplete. It provides only a high-level action without the context needed for safe and correct invocation, especially considering the three parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention any parameters. It does not explain the meaning of 'requirements', 'language', or 'outputDir', nor how they relate to Docker and tests. The description adds no value beyond the schema's bare field names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a clear verb ("Generate") and specifies the resource ("project scaffold"), which distinguishes it from sibling tools like add_docker and add_tests. However, it does not explicitly clarify whether this is for new projects or existing ones, making it not fully distinguishing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives like add_docker or add_tests. It does not indicate prerequisites, intended scenarios, or exclusions, leaving the agent without clear usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It implies a write operation but does not disclose whether it overwrites, appends, creates directories, or requires special permissions. For a mutation tool, this is a significant behavioral gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no redundant words, making it concise. However, it is under-specified rather than efficiently detailed, omitting essential behavioral context that would help an agent use the tool correctly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only two parameters, but no output schema and no annotations leave critical uncertainty about overwriting behavior, path resolution, and error handling. The description is too brief to be fully self-contained for safe invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning to the parameters 'path' and 'content' beyond their names. The schema provides only types and required status, so the description fails to compensate for the lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Write content to a file' clearly states the tool's verb and resource, distinguishing it from read_file and list_directory. However, it does not explicitly differentiate from potential write-related siblings (none present) or mention overwrite vs. append semantics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusion criteria. The description simply states the action without any context about file paths, existence handling, or 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Add Docker configuration' without revealing whether files will be overwritten, what project files are modified, whether it is destructive, or what side effects occur. This is insufficient for a tool that modifies an existing project.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no filler, which is good. However, it is under-specified for a tool with three parameters and no other context; it is concise but not appropriately sized to convey necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple but has no annotations, no output schema, and zero schema description coverage. The description fails to explain what Docker files will be created, what the parameters control, or what the outcome looks like. This is incomplete for an agent deciding whether and how to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention any of the three parameters (hasDb, language, framework). While the parameter names are somewhat self-explanatory, the description adds no meaning about allowed values, defaults, or how they affect the Docker configuration. The burden is not met.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action ('Add Docker configuration') and a specific resource ('existing project'), which distinguishes it from tools like scaffold_project that create new projects. However, it does not explicitly differentiate from other project-modifying tools such as add_tests, so it stops short of full sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use on existing projects but provides no explicit 'when to use' guidance, no prerequisites, and no mention of alternatives like scaffold_project or add_tests. The user is left to infer when this tool is appropriate versus other project-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It merely states the action without revealing return format, hidden-file handling, sorting, error behavior, or permission requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no filler. It is front-loaded and easy to parse, though it could arguably use more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description is still incomplete. It does not specify what the returned directory listing contains (e.g., file names, full paths, metadata) or any behavioral nuances like recursion or sorting.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter 'path' with zero description coverage, and the description does not mention it at all. No additional meaning is provided beyond the parameter name and type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List directory contents' clearly specifies the verb (List) and resource (directory contents), making the purpose obvious. It is distinct from sibling tools like read_file and write_file, though it lacks detail on whether it lists names, metadata, or recursively.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There are no context signals, exclusions, or references to sibling tools, leaving the agent without direction on suitable scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the action and mode; it does not disclose side effects, output format, whether the binary is modified, or any prerequisites. An agent has no idea what a 'headless Ghidra analysis' entails behaviorally.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. It is efficient and to the point, though extremely minimal; it avoids verbosity but could be more substantive without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no elaboration on what analysis performs or returns, the description is incomplete for an agent. It doesn't clarify the difference between 'basic' and 'full' analysis, nor does it explain the result format, making it insufficient for confident invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides descriptions for both parameters (filePath and analysisType), giving 100% coverage. The tool description adds no additional parameter semantics, so it stays at the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Analyze') and the resource ('binary') with a specific method ('Ghidra headless mode'), which distinguishes it from generic analysis tools. However, 'analyze' is broad and doesn't explicitly differentiate from closely related siblings like ghidra_decompile or analyze_binary.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. With sibling tools such as ghidra_decompile, radare2_analyze, and analyze_binary, the lack of any comparison or selection criteria leaves the agent without direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 disclosing behavioral traits. It simply states the action without elaborating on side effects (e.g., whether existing tests are overwritten), required permissions, or the nature of the modifications. This is insufficient for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no filler or redundant wording. It is concise and front-loaded, effectively communicating the core action without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with three undocumented parameters, no annotations, and no output schema, the description is drastically incomplete. It does not explain what the parameters do, what files are affected, or what the expected outcome is, making it inadequate for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has zero description coverage for its three parameters (hasDb, language, framework), and the tool description does not mention them at all. The description provides no meaning for these parameters, leaving the agent without any clue about how they influence the tool's behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Add unit and integration tests' uses a specific verb ('Add') and a clear resource ('unit and integration tests'), which immediately distinguishes this tool from siblings like 'add_docker' or 'scaffold_project'. It clearly states the tool's core function without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, exclusions, or scenarios where another tool might be more appropriate. The usage context is only implied by the name and action, not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'get advice' without revealing whether it scans existing files, calls an external model, or produces a report. There is no added context about side effects, permissions, or output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no filler. It is front-loaded with the core purpose, making it easy to parse quickly. No unnecessary information is included.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and no annotations, the description is far too sparse. It does not explain what the advice looks like, any limitations, or how the language parameter affects the result. A simple tool still needs more context to be properly used.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain the parameters. It only hints that 'requirements' is the input via 'based on requirements', but says nothing about the optional 'language' parameter or any format expectations. This is minimal compensation for the missing schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides architectural advice based on requirements, which distinguishes it from the sibling tools (none of which offer advice). The verb 'get' is a bit generic, but the resource 'architectural advice' is specific enough for a 4.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: when you have requirements and need architectural advice. However, it does not explicitly mention when not to use this tool or mention alternatives like analyze_project, so it only reaches an implied-level score.
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 present, so the description carries the full burden. It only states 'analyze' without disclosing whether the operation is read-only, what it returns, whether it has side effects, or any permission requirements. This leaves the tool's behavior opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no filler words. It effectively states the tool's primary function without unnecessary elaboration, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description should explain what the analysis produces or what actions are performed. It does not, leaving the tool's output and behavior undefined. Even for a simple tool with one optional parameter, this is insufficient for an agent to understand the full context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully documents the only parameter 'path' as 'Directory to scan' (100% coverage). The description adds no additional meaning about this parameter, so the baseline score of 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Analyze API endpoints in the project' uses a specific verb ('analyze') and resource ('API endpoints'), making its core function clear. It is distinguishable from broader siblings like 'analyze_project' because it focuses specifically on API endpoints, though it does not explicitly reference alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus siblings such as 'analyze_project', 'validate_api_structure', or 'review_security'. The description gives no context about prerequisites, typical use cases, or situations where alternative tools would be preferred.
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 must fully disclose behavior. It only states the tool analyzes and provides feedback, without clarifying whether it is a safe read-only operation, what side effects might occur, or what form the feedback takes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the primary action. It is concise and easy to scan, though the brevity sacrifices important behavioral details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description leaves the feedback format, scope, and any limitations ambiguous. For a simple one-parameter tool it is minimally viable, but it does not fully equip an agent to predict the tool's response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, 'path', is fully described in the input schema with 100% coverage. The description adds no extra parameter semantics, but the schema already explains it adequately, so this is a reasonable baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Analyze project structure') and intended outcome ('provide architectural feedback'), using a specific verb and resource. However, it does not distinguish itself from sibling tools like get_architecture_advice, which may overlap in purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives such as analyze_api or get_architecture_advice. The description does not mention prerequisites, exclusions, or typical scenarios, leaving the agent without decision support.
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 must fully explain behavior, but it only says 'provides Volatility commands and quick wins.' It does not clarify whether the tool executes commands, returns output, or requires special permissions, and 'quick wins' is vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded, but the phrase 'quick wins' is vague filler. It earns a high score for brevity and clarity, but a perfect score would require every phrase to add value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one param, no output schema), but the description fails to convey enough context about what the agent will receive or how to interpret results. It lacks details on output format, typical findings, or limitations, making it incomplete for real use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description for dumpFile ('Path to memory dump file'). The tool description adds little beyond the schema, only rephrasing 'memory dump', so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses a specific verb ('Analyze') and resource ('memory dump'), clearly distinguishing from siblings like analyze_binary or network_analysis. The mention of 'Volatility commands' hints at the tool's function, but it's slightly ambiguous whether it actually runs the analysis or merely suggests commands.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use or when-not-to-use guidance is provided. It does not mention alternatives or scenarios where this tool is preferred over sibling analysis tools, which is important given many similar siblings exist.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only says it analyzes with PE Studio features. It doesn't disclose whether the operation is read-only, whether an external GUI is invoked, or what kind of analysis results are produced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, front-loaded with the core action and resource, with zero wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations or output schema and multiple binary-analysis siblings, this description is too sparse. It fails to mention what 'PE Studio features' includes, expected output, or how it differs from similar analyzers.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter (filePath) with a basic description. The description adds no additional semantic detail beyond 'Path to PE file', so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'Analyze' with resource 'PE (Windows) file' and tool-specific 'PE Studio features', distinguishing from general-purpose binary tools. However, it doesn't explicitly differentiate from siblings like ghidra_analyze or radare2_analyze beyond the PE/Windows scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus siblings such as ghidra_analyze, radare2_analyze, or yara_scan. It doesn't state prerequisites, limitations, or alternative conditions.
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 the full burden. It only states the basic action without disclosing side effects, return format, or whether the tool modifies code. For a security review tool, this lack of detail leaves behavioral assumptions unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no extraneous words, directly front-loading the tool's purpose. Excellent conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, and the description fails to mention expected return values or any additional context. While the tool is simple, an agent would not know what the review produces.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage: the path parameter is described as 'File or directory to review'. The description adds no additional meaning beyond this, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reviews code for security vulnerabilities, using a specific verb and resource. However, it does not differentiate from sibling analysis tools like analyze_project or ghidra_analyze, which may also perform security-related review.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, exclusions, or comparison with similar sibling tools, leaving the agent without decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only states 'Validate API follows REST best practices' with no information about side effects, output format, whether it modifies files, or required permissions. Since no annotations are provided, the description carries the full burden and fails to disclose these behavioral aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at seven words, front-loaded with the action verb, and contains no fluff. While it is terse, it is appropriately sized for a simple tool, though slightly under-specified in content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, so the description must explain what the tool returns or how results are presented. It does not. The optional path parameter and validation behavior are minimally described, leaving an agent without sufficient context to invoke the tool confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully describes the single 'path' parameter as 'Path to API files', so the description adds no additional semantics. With 100% schema coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: validating an API against REST best practices. It uses a specific verb ('Validate') and identifies the resource ('API'), which is unambiguous. However, it does not differentiate from sibling tools like analyze_api, which could overlap in scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like analyze_api or review_security. The description lacks any context about prerequisites, use cases, or exclusion criteria, leaving the agent without direction on 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 the full burden. It only states the basic action ('Scan file with YARA rules') but does not disclose behavior such as whether it is read-only, what it returns, whether default rules are used when rulesPath is omitted, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently conveys the core purpose with no wasted words. It is appropriately sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, yet the description does not mention return values, expected output format, or edge cases (e.g., missing rules). Given the many sibling tools, the lack of usage context makes this incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both filePath and rulesPath described. The description adds no extra meaning beyond the schema, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Scan') and identifies the resource (file) and purpose (malware indicators via YARA rules). It clearly conveys the tool's function, though it does not explicitly distinguish it from sibling analysis tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, no context for preconditions, and no exclusions. The agent must infer usage from the name and schema 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?
The description merely restates the tool's function and provides no behavioral details beyond the name. Since no annotations are provided, the agent gets no information about whether this is a read-only operation, what the output looks like, how it handles a missing functionName, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that immediately conveys the tool's purpose without unnecessary words. It earns its place and is appropriately front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of annotations and an output schema, the description is too minimal to provide adequate context. It omits important information about the decompilation output format, the role of the optional functionName parameter, and how this tool fits among the many binary analysis sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters (filePath and functionName), so with 100% schema coverage, the baseline is 3. The description does not add any additional meaning or context beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool decompiles binary functions using Ghidra. The verb 'decompile' and resource 'binary functions' are specific, and the mention of Ghidra distinguishes it from sibling tools like ghidra_analyze, radare2_analyze, and pestudio_analyze.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. It only states what it does, not when to use it, when not to use it, or what the prerequisites are. The description provides no exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It fails to disclose whether the tool is read-only, what output format to expect, or any side effects or limitations. While 'Analyze' hints at a non-destructive operation, this is not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, well-structured sentence that is front-loaded with the action word 'Analyze'. It is concise and free of unnecessary filler, earning full marks.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of both annotations and an output schema, the description must compensate but does not. It omits crucial behavioral details such as return values, file access mode, and what 'traffic' analysis entails. The tool is simple (one parameter), but the description still leaves the agent uncertain about expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with 'pcapFile' described as 'Path to pcap file'. The tool description adds no additional meaning beyond the schema, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Analyze') with a clear resource ('network capture (pcap)') and a defined objective ('for IOCs and traffic'). This clearly distinguishes it from sibling tools like memory_forensics or dynamic_analysis, which target different data sources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives, no prerequisites, and no mention of exclusions. The description merely states what the tool does without indicating the appropriate context or 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 the full burden of behavioral disclosure. It fails to mention that dynamic analysis typically involves executing the file, potential safety risks, or the need for a sandbox environment. The agent is left unaware of side effects, making this a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It efficiently communicates the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is too sparse for a tool that executes potentially malicious files. It lacks information about return values (e.g., whether it outputs a report), timeout semantics, and prerequisite safety measures. Given no output schema and no annotations, this is inadequate for safe and correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters. The description adds no extra meaning beyond the schema, which aligns with the baseline of 3 when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Run') and the resource ('dynamic/behavioral analysis on suspicious file'). It distinguishes itself from static analysis siblings like ghidra_analyze and radare2_analyze by emphasizing the behavioral nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for suspicious files requiring behavioral observation, but it does not explicitly state when to prefer this over static analysis tools, nor does it mention exclusions or alternatives. The context of 'suspicious file' gives some guidance, but explicit when-to-use vs. when-not-to-use is absent.
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 does not disclose that running the binary may execute arbitrary code, require ptrace permissions, or have side effects. The 'run' step implies execution but without any caution or context about safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, succinct sentence that front-loads the tool's purpose and core steps. No wasted words or redundant details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple with only 2 parameters, the description lacks behavioral context such as return values, potential side effects, or how it fits with sibling tools. No output schema exists, so more detail on what 'inspect' provides would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for both parameters (filePath and breakpoint). The description does not add extra meaning beyond the schema; it simply mentions breakpoint in passing. With high schema coverage, baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool debugs a binary using GDB, with a specific workflow (set breakpoint, run, inspect). This distinguishes it from sibling static analysis and other debugging tools like radare2_analyze or ghidra_analyze.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies its usage (interactive debugging with GDB) but does not explicitly state when to prefer it over alternatives such as radare2_analyze or dynamic_analysis. No exclusions or comparisons are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It only states the operation and output categories, without mentioning whether the operation is read-only, requires special permissions, has side effects, or what the response format is.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, immediately front-loaded with the action and tool, and contains no filler. Every word contributes meaning, 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool, the description is minimally viable but lacks details about the return format or operational constraints. Given the absence of an output schema and annotations, it would be more complete if it described what the analysis output looks like.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already defines filePath as 'Path to binary file' with 100% coverage. The description adds no additional parameter semantics beyond the schema, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses a specific verb 'Analyze' with the resource 'binary' and identifies the tool 'Radare2' plus analysis targets (functions, imports, strings). This clearly distinguishes it from sibling tools like ghidra_analyze or pestudio_analyze.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (when Radare2-based binary analysis is needed) but does not explicitly state when not to use it or compare with alternatives. Selection among siblings like ghidra_analyze or analyze_binary is left to inference.
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, the description must disclose behavior itself. It mentions 'static analysis', which implies read-only non-execution, and lists specific actions. However, it does not explicitly state that it is non-destructive, does not mention required permissions or potential side effects, and gives no hint about the output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise sentence, front-loaded with 'Static analysis', and every word contributes meaning without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter, but there is no output schema and no annotations. The description covers the core actions but leaves gaps such as what the output looks like, whether there are format restrictions, and any safety guarantees. It is minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides a 100% description coverage for the only parameter 'filePath'. The description adds no additional meaning beyond what the schema states, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: static analysis of a binary file, with specific operations listed (extract strings, check security via checksec, binary info). It uses specific verbs and a clear resource ('binary'), and it distinguishes itself from dynamic analysis siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for static analysis of binaries but does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions. It provides minimal guidance on when to prefer this tool over other analysis tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![backend-mcp MCP server](https://glama.ai/mcp/servers/RoySamson-stack/backend-mcp/badges/card.svg)](https://glama.ai/mcp/servers/RoySamson-stack/backend-mcp)

Score Badge

Copy to your README.md:

[![backend-mcp MCP server](https://glama.ai/mcp/servers/RoySamson-stack/backend-mcp/badges/score.svg)](https://glama.ai/mcp/servers/RoySamson-stack/backend-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/RoySamson-stack/backend-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server