Cybersec Toolkit

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

With no annotations provided, the description carries the full disclosure burden and largely meets it: it enumerates five detection strategies (.versions, PATH, pipx fallback, /opt, docker image) and discloses the SSH 'which <binary>' behavior for remote hosts. This gives the agent accurate expectations about scope and fallback resolution, though it doesn't mention potential slowness of the docker check or the absence of 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, tightly organized: purpose first, then detection strategies in a compact enumeration, then the remote-host behavior. Every sentence carries information and none repeats the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 2-parameter tool with a documented output schema, the description covers what the tool does, how it detects, and how it behaves remotely. The only real gap is the lack of when-to-use guidance relative to siblings, which is already penalized under usage_guidelines; overall the definition is complete enough for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and both parameters already carry descriptions, so the baseline is 3. The description adds value beyond the schema by explaining how tool_name is resolved (multi-strategy lookups that may succeed outside PATH) and by enriching host with concrete behavior (SSH + 'which <binary>'), justifying a 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence states a specific verb ('Check') with a specific resource ('if a specific cybersecurity tool is installed on the system'), and the ensuing detection-strategies sentence sharpens what 'check' means. The purpose is inherently distinct from sibling tools like list_tools, get_tool_info, and run_tool, so an agent can select it without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description makes the primary use case obvious ('check if installed') and explains the remote-host variant, but it never names alternatives or states when not to use this tool—for example, it doesn't advise verifying installation before run_tool or point to recommend_install for missing tools. Usage is implied by the purpose statement rather than explicitly guided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It comprehensively explains that the tool is local-first and deterministic, does not fetch external data itself, returns ready-to-run curl commands instead, is subject to the CYBERSEC_MCP_ALLOW_EXTERNAL policy, and requires clearing the authorization-gate skill before testing. This is far beyond minimal transparency.

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

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is tightly structured: a one-line purpose, then input/output behavior, then critical caveats about external data and authorization. Every sentence adds meaningful information without redundancy or filler, and the most important constraints are front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has one parameter, an output schema, and moderate complexity, the description covers all essential operational context: what results are returned, local-first deterministic behavior, external-data handling via curl commands, policy dependency, and the authorization gate. An agent has enough guidance to invoke the tool correctly and interpret its outputs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already fully describes the single 'cve' parameter with 100% coverage. The description adds valuable concrete examples (CVE-2021-44228, log4shell, eternalblue, zerologon, printnightmare) and reinforces accepted formats, making parameter usage clearer than the schema alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Map a CVE to the toolkit's tools, skills, and modules, plus live-lookup commands.' It clearly distinguishes this from sibling tools by centering on a CVE identifier/nickname and the mapping output, rather than generic tool/module info or CTF/bounty suggestions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context for when to use this tool: when you have a CVE id or known nickname and want curated exploitation skills, mapped tools, and relevant modules. It does not explicitly state when not to use it or name alternative tools, but the local-first deterministic behavior and live-lookup command pattern make the intended use apparent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the behavioral disclosure burden. It does disclose that the tool returns module details and what categories those details fall into, implying a read-only informational operation. However, it does not address error behavior, module existence requirements, or 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that states the main action and enumerates the key result categories without filler. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple single-parameter getter with a full input schema and an output schema, the description is largely sufficient. The only minor gap is that 'management commands' is slightly vague and there is no note about invalid or missing modules, but the overall context is complete enough for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema already fully documents the 'module' parameter. The description adds no additional param-level semantics beyond restating that the tool concerns modules, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Get') with a clear resource ('full details about a module') and enumerates the returned content: description, all tools, and management commands. This clearly distinguishes it from sibling tools like get_tool_info, get_cve_info, and list_tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool should be used when someone needs comprehensive module-level details, but it does not explicitly state when to prefer this over alternatives such as get_tool_info or list_tools. No exclusions or conditional guidance are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full burden of disclosing behavior, and it does so well: it conveys that this is a read-only preview ('before running the install command'), that it returns a 'complete list,' and that results are 'grouped by module' with 'install status for each.' The key safety-relevant trait — non-mutating — is clearly communicated even without annotations. It does not cover edge-case behavior like invalid profile names, but that is minor for a list operation.

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

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each earning its place: a front-loaded verb+resource statement, a behavioral detail sentence (grouping by module and install status), and a use-case sentence that frames when to call it. There is no repetition of schema content and no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple — one fully-documented required parameter and an output schema present, so return-value details are already specified elsewhere. The description adds the grouping behavior, install-status semantics, and preview framing. The only gap is undefined behavior for unknown profile names, which is minor for a non-mutating list operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%; the profile parameter already carries a description with concrete examples ('ctf', 'redteam', 'web', 'full'). The description's 'Given a profile name' merely reinforces the schema text and adds no new semantic detail, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence, 'List every tool that a specific profile would install,' states a specific verb (list) and a clear resource (tools for a given profile). The phrase 'before running the install command' frames it as a preview, which distinguishes it from execution-oriented siblings like run_tool and run_pipeline, and from check_installed which would report actual installation state rather than planned contents.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a clear when-to-use instruction: 'This lets you see exactly what you get before running the install command.' This situates the tool in the workflow precisely. However, it does not explicitly name alternatives or state when not to use it, such as contrasting with check_installed to clarify that this shows planned rather than current installation state.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the burden, and 'Get/Returns' clearly signals a read-only lookup with no side effects. It also discloses the exact return content, including installation status and management commands, which goes beyond a generic 'get info' claim.

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

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences: the first states the action and object, the second enumerates the returned fields. There is no fluff or repetition, and the key purpose is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter lookup with an output schema, this is complete enough to invoke correctly. It omits only explicit alternative routing and edge-case behavior (e.g., unknown tool names), which keeps it from being fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%: the single param tool_name is already documented as 'Name of the tool to look up.' The description adds no new parameter meaning, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clear verb 'Get' + specific resource 'detailed information about a cybersecurity tool', with enumerated fields (install method, module, URL, installation status, management commands) that distinguish it from sibling lookup tools like list_tools or check_installed.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The purpose is inferable: use when you need detailed tool metadata and management commands. However, there is no explicit when-to-use guidance or comparison against siblings (e.g., check_installed, list_tools), so the agent must infer the right choice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full behavioral burden and does so well. It discloses the governed execute_tool() path, safety checks, default no-autorun behavior, autonomous auto-execution, and the possibility of creating, saving, and running helper scripts persisted under manual_scripts/. This is outstanding transparency for a mutable, potentially side-effect-heavy tool.

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

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is longer than average but dense and informative; it earns its length given the tool's complexity. It front-loads the core purpose and then layers mode behavior, safety, and side effects. Minor redundancy around 'MCP toolchain' and 'agent' prevents a 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex orchestrator with 8 parameters and no annotations, the description is remarkably complete. It covers default and heavy modes, the step-by-step companion workflow, execution policy safeguards, script persistence, and the boundary between run_tool and helper scripts. Since an output schema exists, return-value detail is not required here.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds meaningful context beyond the schema by explaining that workflow/target_type default to 'auto' and are auto-detected, that mode controls whether the initial call runs commands, and that max_steps bounds autonomous execution. This enriches several parameters without needing to restate all of them.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies an orchestrator that plans, guides, or autonomously solves security tasks over the MCP toolchain. It distinguishes itself from executable siblings by positioning itself as the planning/triage layer on top of run_tool, run_pipeline, run_script, and the registry/advisors.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives strong usage context: default companion mode returns a plan without executing, while autonomous mode bootstraps and continues into the toolchain. It also notes that simple recon/HTTP commands like curl remain run_tool calls. It stops short of explicitly naming conditions for every sibling alternative, but the guidance is clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full burden. It makes the read-only nature clear with 'List' and explicitly discloses what is returned: profiles with descriptions, module lists, tool counts, and install commands. It does not mention error cases, but for a zero-parameter listing tool, no significant hidden behavior is omitted.

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

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main purpose and stays reasonably compact. There is minor redundancy between 'Shows module count, tool count, and install command' and the later 'Returns' block, but the additional context about profile range and use cases earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a low-complexity tool with no parameters and an existing output schema. The description sufficiently covers what the tool does and what it returns, including a helpful example of the range from 'osint' to 'full'. Nothing essential is missing for an agent to select and call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero parameters and schema description coverage is 100%, so the baseline is 4. There are no parameter choices to explain, and the description appropriately focuses on output content rather than parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource: 'List all 14 available installation profiles with details.' It clearly distinguishes this from sibling tools like list_tools by naming profiles as the resource, not tools, and emphasizes 'each profile is a curated set of modules.'

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool—when you need an overview of installation profiles, their module counts, tool counts, and install commands. However, it does not explicitly mention alternatives such as get_profile_tools or list_tools, nor does it state when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations supplied, the description carries the full transparency burden and meets it: it discloses the data source (tools_config.json), the shape of the result (total count, remaining filters, one entry per tool), and the fact that filters can be combined. This goes well beyond what the name or schema alone conveys.

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

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences with no filler: purpose, return composition, and usage examples are front-loaded. The closing pointer to sibling tools earns its place, and the filter examples are positioned where they are most useful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with three optional parameters and a full output schema, this description is complete. It covers what is returned, the source of the data, how filters work, and where it fits in the discovery workflow, leaving no missing information an agent would need to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds value by providing semantic mappings such as 'pipx' meaning Python-packaged, clarifying installed_only as 'only what is on this host,' and explicitly noting that filters can be combined, which is not stated in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'List and filter the 670+ cybersecurity tools in the registry,' giving a specific verb and resource. It further distinguishes itself by noting the data comes from tools_config.json and by positioning itself as the place to start 'before check_installed or get_tool_info.'

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit when-to-use guidance ('Start here to discover what exists before check_installed or get_tool_info') and concrete filter examples such as module='web', method='pipx', and installed_only=True. It does not provide an explicit when-not-to-use rule or name a direct alternative for filtered detail, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It thoroughly describes the SSH connection behavior: using StrictHostKeyChecking=accept-new, pinning the first key, and rejecting subsequent changes. It also warns about verifying fingerprints out-of-band, which is critical safety information for an agent to understand the tool's security implications.

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

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and appropriately sized. It opens with a clear summary of the tool's function, then breaks down each action in a logical flow, and ends with important security details. No sentence is wasted; each contributes to either clarifying functionality or providing necessary warnings.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (8 parameters, 4 actions, security implications) and rich input schema, the description covers all essential aspects for correct usage. It explains the relationship with sibling tools, parameter requirements per action, and safety concerns. The output schema is provided, so return value details are not needed. The description is comprehensive enough for an agent to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

While schema description coverage is 100%, the description adds significant semantic value beyond the schema. It explains the role of name and hostname as required for specific actions, clarifies that tool_allowlist restricts which tools can run, and implies how parameters like port and user have defaults. Although the schema already documents each parameter, the description provides usage context that helps an agent choose and set parameters appropriately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: managing the remote-host registry that enables run_tool and check_installed to operate over SSH. It uses a specific verb ('Add, list, test, or remove') and resource ('SSH hosts'), and differentiates itself from sibling tools by explaining its role in supporting remote execution.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit when-to-use guidance by detailing each action ('list', 'add', 'remove', 'test') and their required parameters ('add' needs name and hostname; 'test' confirms connectivity). It also covers edge cases like tool_allowlist restrictions and provides clear context for when to use this tool vs. alternatives, such as run_tool for executing tools remotely.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries the full burden. It transparently states that the tool only recommends rather than installs, and it reveals a decision principle: it avoids over-recommending when a subset suffices. This goes beyond the tool name and provides useful behavioral context, though it does not mention any limitations such as reliance on an available installation catalog.

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

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences with no filler. The first sentence states the core purpose, the second explains the mechanism, and the third adds a valuable behavioral nuance. Information is front-loaded and every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with a single parameter and an output schema, the description covers the input format, the recommendation scope, and the conservative behavior. It does not discuss prerequisites like needing an inventory of available tools or relationship to sibling tools, but these are not essential given the schema and output schema presence. Slightly more detail about what information the recommendation is based on would make it fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%: the only parameter, task, is described as 'Natural-language description of what the user wants to do.' The tool description effectively repeats this same meaning. Since the schema already fully documents the parameter, a baseline of 3 applies; no additional semantic depth is added beyond restating the input.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Recommend which profile, modules, or individual tools to install.' It clearly states the tools scope from full profiles down to individual tools, and this differentiates it from specialized siblings like suggest_for_ctf or suggest_for_bounty. The purpose is unambiguous and not a tautology.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context for when to use it: when a natural-language description of the user's goal needs an installation recommendation. It also implies a useful condition ('Avoids installing everything when only a subset is needed') without explicitly naming alternatives or exclusions. It could be stronger by contrasting with suggest_for_ctf or suggest_for_bounty, but the usage context is evident.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries the full transparency burden. It discloses per-step validation, allowlist/policy checks, 200KB stdout/stderr limits, the truncation flag, and the no-shell guarantee—substantial behavioral detail.

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

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, then uses compact paragraphs for validation and truncation details. Every sentence contributes useful behavioral or usage information, with no filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity and the absence of annotations, the description is strongly complete: it covers execution model, safety, and truncation behavior. The main remaining gap is failure semantics (e.g., what happens if a step exits non-zero), though the output schema may cover that.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already describes all three parameters with 100% coverage, so the baseline is 3. The description adds extra meaning by explaining how steps connect via stdin/stdout and how truncation is signaled, going beyond the raw schema without re-listing parameter syntax.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence states a specific action and resource: 'Execute a pipeline of tools, piping stdout from each step into stdin of the next.' This clearly distinguishes it from sibling tools like run_tool and run_script by emphasizing multi-step composition and pipe semantics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly identifies the intended use case: replacing shell piping like `strings binary | grep flag` with a safe, no-shell alternative. It does not explicitly name sibling alternatives or state when not to use it, but the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the full burden and does so thoroughly: it discloses temp-file creation, interpreter choice, stdout/stderr return, automatic cleanup, required environment variable, and lack of OS sandboxing. It also clarifies that the allow-external gate does not constrain this tool, which is exactly the behavioral context an agent needs.

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

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences with a front-loaded summary followed by essential behavioral and security details. No filler or redundant restatement of the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description, combined with a fully documented 5-parameter schema and an output schema, covers execution mechanics, cleanup, return content, security constraints, and opt-in requirements. Nothing critical is missing for an agent to call this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all five parameters in detail. The description adds global execution context but no per-parameter meaning beyond the schema, matching the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a clear verb-object statement ('Write and execute a Python or Bash script, returning its output') that identifies the exact operation and resource. It also distinguishes run_script from sibling tools by emphasizing full-code script execution via python3/bash rather than prebuilt tool or pipeline execution.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool: when arbitrary Python or Bash code must be written and executed, with an explicit security opt-in. It does not explicitly name alternatives like run_tool or state when not to use run_script, so it misses the top tier, but the intended usage is unmistakable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full burden, and it does exceptionally well: it discloses argument sanitization against shell injection, timeout clamping to 1-300s, output truncation at 200KB, network restrictions, and remote-host execution semantics. This is far beyond typical tool descriptions.

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

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main purpose and then adds dense, relevant operational details. Every sentence contributes necessary information about allowed inputs, safety, limits, or remote behavior, with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a general execution tool with four parameters and an output schema, the description is complete: it covers what can be run, how arguments are handled, timeout and output limits, network restrictions, and remote host behavior. Missing return-format details are acceptable because an output schema is present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful value above the schema by explaining that tool_name may be a registry tool or allowed system utility, that timeout is clamped, and that providing host switches execution to remote SSH mode rather than local execution.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource: 'Execute an installed cybersecurity tool or system utility and return its output.' It further narrows the scope by distinguishing registry tools and ~120 allowed system utilities, which separates it from siblings like run_script and run_pipeline without needing to name them explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear operational context: local execution by default, remote execution via SSH when host is provided, and network-target restrictions with an explicit environment variable to allow external targets. It does not explicitly state when to prefer run_tool over a named alternative, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries the full burden. It discloses what the tool returns: curated recommendations, installation status, methodology steps, common vulnerabilities, and quick wins. It does not explicitly state that it performs no modifications, but 'suggest' and the recommendation framing imply a read-only behavior.

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

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and well-structured: a clear opening sentence, a detailed breakdown of output content, and a concise list of aliases. Every sentence adds value and the most important information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a single required parameter, a complete output schema, and no complications like nesting or enums, the description covers everything needed: valid target types, aliases, what the tool returns, and its general methodology. No critical information is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema only provides two example values for target_type, while the description enumerates all seven accepted values and their aliases. This is essential for correct invocation, especially since the schema defines no enum. The description adds substantial meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: suggesting cybersecurity tools for a bug bounty target type. It enumerates the seven accepted target types and lists aliases, making the tool's scope unmistakable and differentiating it from siblings like suggest_for_ctf.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use the tool: when the user needs tool recommendations for a specific bug bounty target type. It does not explicitly discuss alternatives or exclusions, but the target-type list and bug bounty framing make selection straightforward.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the behavioral disclosure burden. It states that the tool provides curated recommendations and installation status, and that it normalizes aliases. This conveys a read-only recommendation behavior, though it does not explicitly note the absence of side effects or any system modifications.

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

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with purpose, then systematically covers supported categories and alias handling. The only minor issue is slight redundancy between the first and second sentences, but overall every part earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter tool with an output schema, the description is quite complete: it specifies valid inputs, aliases, and the nature of the output (recommendations with installation status). It could optionally mention behavior for unknown or unsupported categories, but this is not a significant gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although schema coverage is 100%, the description adds substantial value by listing all 14 accepted challenge types and common aliases. This goes far beyond the schema's generic 'Type of CTF challenge' example and directly informs correct parameter values.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Suggest') and clearly identifies the resource ('cybersecurity tools for a CTF challenge category'). It also enumerates the full set of supported challenge types, making the tool's scope unmistakable and distinguishing it from the sibling suggest_for_bounty through the CTF-specific framing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool: whenever tool suggestions for a CTF challenge category are needed. It also clarifies accepted input domains and aliases. However, it does not explicitly mention alternatives or state when not to use it, so it stops short of full routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.