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 implies a mutation operation ('Add') and specifies required parameters, but doesn't cover important aspects like permissions needed, rate limits, whether the addition is permanent or reversible, or how the blacklist affects system behavior. The description adds basic context but misses key behavioral traits.

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 front-loaded with the core purpose, followed by parameter explanations and return format. Every sentence earns its place: the first states the action, the second clarifies parameter requirements, and the Args/Returns sections are concise and informative without 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 mutation nature (no annotations), 5 parameters with 0% schema coverage, and an output schema provided, the description does a good job. It explains parameters thoroughly and includes return values, though it could better address behavioral aspects like system impact or error conditions. The output schema reduces the need for return value details.

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 description coverage is 0%, so the description must compensate. It provides clear semantics for all 5 parameters: 'file_path' and 'code' are explained as alternatives, 'reason' as justification, 'severity' with enumerated values, and 'language' as programming context. This adds significant meaning beyond the bare schema, though it doesn't detail format constraints (e.g., path 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 description clearly states the specific action ('Add a code pattern to the blacklist') and resource ('blacklist'), distinguishing it from siblings like 'firewall_remove_pattern' (removal) and 'firewall_list_patterns' (listing). The verb 'Add' is precise and the resource 'blacklist' is well-defined.

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

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

The description provides some implied usage guidance by stating 'Either file_path or code must be provided,' which helps differentiate between input methods. However, it lacks explicit guidance on when to use this tool versus alternatives like 'firewall_check' or 'firewall_check_code,' and doesn't mention prerequisites or exclusions.

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

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 and does so effectively. It describes the multi-step process (parsing, normalizing, embedding, similarity checking), mentions the use of Ollama embeddings, and references blacklisted dangerous patterns. It doesn't cover rate limits, authentication needs, or error conditions, but provides substantial operational context for a security 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 perfectly structured and front-loaded: the first sentence states the core purpose, followed by a concise process overview, then clearly labeled parameter and return value sections. Every sentence earns its place with no wasted words, making it easy for an agent to quickly understand the tool's function.

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 security-critical nature, single parameter, and comprehensive output schema, the description is complete. It explains the purpose, process, parameter meaning, and the output schema fully documents return values. No annotations exist to supplement, but the description stands adequately on its own for this complexity level.

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 has 0% description coverage for its single parameter, but the description's 'Args' section clearly explains 'file_path: Path to the code file to check'. This adds essential meaning beyond the bare schema. The description doesn't specify format requirements or constraints, but provides the fundamental semantic understanding needed.

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 with specific verbs ('check if code is safe', 'parses', 'normalizes', 'embeds', 'checks similarity') and resources ('code', 'execution tools like rlm_exec'). It explicitly distinguishes from siblings by focusing on safety checking rather than blacklist management, pattern listing, or system status operations.

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 this tool ('check if code is safe to pass to execution tools like rlm_exec'), which implicitly suggests it should be used before executing untrusted code. However, it doesn't explicitly state when NOT to use it or name specific alternative tools among the many siblings, though the purpose differentiation is strong enough to guide selection.

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 full burden. It mentions the tool checks safety but doesn't disclose what 'safe' means, potential side effects (e.g., rate limits, authentication needs), or behavioral traits like whether it's read-only or destructive. The reference to 'Same as firewall_check' is vague and doesn't add concrete behavioral details.

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

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

The description is appropriately sized and front-loaded with the core purpose. The Args and Returns sections are structured but could be more integrated; the 'Same as firewall_check' is somewhat vague and doesn't fully earn its place. Overall, it's efficient with minimal waste.

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 2 parameters with 0% schema coverage and an output schema exists, the description provides basic purpose and parameter hints but lacks details on safety criteria, error handling, or output specifics. It's minimally adequate for a simple check tool but has clear gaps in behavioral and parameter context.

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 0%, so the description must compensate. It adds meaning by explaining 'code' as the code to check and 'language' as the programming language with a default, which clarifies beyond the bare schema. However, it doesn't specify allowed languages, code format constraints, or other parameter details, leaving gaps in documentation.

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 checks if a code string is safe, specifying it works without requiring a file. It distinguishes from siblings like firewall_check (which likely requires a file) by emphasizing the string-based approach. However, it doesn't explicitly differentiate from other safety-related siblings like firewall_blacklist or firewall_list_patterns.

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 usage when you have code as a string rather than a file, suggesting an alternative to file-based checking. However, it doesn't provide explicit guidance on when to use this versus other safety tools like firewall_blacklist or firewall_system_check, nor does it mention prerequisites or exclusions.

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

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

No annotations are provided, so the description carries the full burden. It mentions the return format but lacks critical behavioral details such as whether this is a read-only operation, if it requires authentication, how it handles errors, or if there are rate limits. For a tool with no annotation coverage, this is insufficient.

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

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

The description is highly concise and well-structured: a clear purpose statement followed by formatted sections for Args and Returns. Every sentence earns its place, with no wasted words, making it easy to scan and understand quickly.

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

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

Given the tool's low complexity, 2 parameters, no annotations, but an output schema provided, the description is reasonably complete. It covers purpose, parameters, and return values, though it could improve by adding behavioral context like safety or usage guidelines relative to siblings.

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 description adds meaningful context beyond the input schema, which has 0% coverage. It explains that 'collection_name' accepts 'blacklist' or 'deltas' and 'limit' specifies the maximum number of patterns, clarifying usage that the schema alone doesn't provide. With 2 parameters and low schema coverage, this compensates well.

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 verb 'List' and the resource 'patterns in the blacklist or delta collection', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'firewall_blacklist' or 'firewall_record_delta', which might have overlapping functionality, preventing a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'firewall_blacklist' and 'firewall_record_delta' that might handle similar collections, there's no indication of context, prerequisites, or exclusions, leaving usage ambiguous.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions checking server status and model availability, which implies a read-only operation, but doesn't detail aspects like authentication needs, rate limits, or what 'availability' entails (e.g., uptime, load). It adds some context but lacks comprehensive behavioral traits.

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 appropriately sized and front-loaded, with the core purpose stated first and parameter details following in a clear, bullet-like format. Every sentence earns its place without redundancy, making it efficient and easy to parse.

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

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

Given the tool's low complexity (1 parameter, no annotations, but with an output schema), the description is reasonably complete. It covers the purpose and parameter semantics adequately, and since an output schema exists, it doesn't need to explain return values. However, it could improve by addressing sibling differentiation or more behavioral details.

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 description adds meaningful semantics for the single parameter 'force_refresh' by explaining it 'Force refresh the cached status,' which clarifies its purpose beyond the schema's basic boolean type. Since schema description coverage is 0%, this compensates well, though it doesn't cover all potential nuances like caching behavior details.

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 as 'Check Ollama server status and embedding model availability,' which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'firewall_status' or 'firewall_system_check,' which likely have overlapping monitoring functions, preventing a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools or contexts where this specific status check is preferred, such as for embedding models versus general firewall status, leaving the agent with minimal usage direction.

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 describes the tool's purpose and usage context well but lacks details on behavioral traits like authentication requirements, rate limits, or what 'recording' entails (e.g., storage, visibility, or impact on the classifier). The description doesn't contradict annotations (none provided), but it's incomplete 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.

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

The description is appropriately sized and front-loaded: the first sentence states the purpose, followed by usage guidelines, then a structured Args/Returns section. Every sentence earns its place with no redundancy, making it efficient and easy to parse.

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

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

Given the tool's complexity (mutation with 5 parameters, no annotations), the description is mostly complete: it covers purpose, usage, parameters, and includes an output schema (returns status and delta_id). However, it lacks details on behavioral aspects like permissions or effects, which are important for a mutation tool. The output schema reduces the need to explain return values, but more context on the tool's impact would improve completeness.

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?

With 0% schema description coverage, the description compensates by listing all 5 parameters (file_path, code, similar_to, notes, language) and explaining their semantics briefly (e.g., 'Path to code file', 'Code string (alternative to file_path)'). This adds significant value beyond the bare schema, though it doesn't detail constraints or interactions between parameters like file_path vs. code.

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 with specific verbs ('Record a near-miss variant') and resource ('to help sharpen the classifier'), distinguishing it from siblings like blacklisting or checking tools. It explains this is for legitimate use cases similar to blacklisted patterns or new dangerous pattern variants, providing precise differentiation.

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 states when to use this tool: 'Use this when code is similar to a blacklisted pattern but represents a legitimate use case, or when a new variant of a dangerous pattern is discovered.' This provides clear context and distinguishes it from alternatives like blacklisting or removal tools among siblings.

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 states the action ('Remove') and the return value, but doesn't cover critical aspects like permissions needed, whether the removal is reversible, potential side effects, or error handling. This is inadequate for a mutation tool with zero annotation coverage.

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

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

The description is appropriately sized and front-loaded, with the core purpose stated first, followed by structured sections for Args and Returns. There's no wasted text, though the structure could be slightly more integrated for optimal flow.

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 (a mutation with 2 parameters), no annotations, and an output schema that covers return values, the description is partially complete. It explains the action and parameters but lacks behavioral context and usage guidelines, making it adequate but with clear gaps for an agent to operate effectively.

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

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

Schema description coverage is 0%, so the description must compensate. It explains 'pattern_id' as 'The pattern ID to remove' and 'collection_name' as '"blacklist" or "deltas"', adding meaning beyond the bare schema. However, it doesn't detail format constraints or examples, leaving some gaps in parameter understanding.

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 action ('Remove a pattern') and the target ('from the blacklist or delta collection'), which is specific and unambiguous. However, it doesn't explicitly differentiate this tool from sibling tools like 'firewall_blacklist' or 'firewall_record_delta', which might handle similar collections, so it doesn't reach the highest score.

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

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

The description provides no guidance on when to use this tool versus alternatives, such as other sibling tools like 'firewall_blacklist' or 'firewall_record_delta'. It mentions the collections ('blacklist' or 'deltas') but doesn't explain the context or prerequisites for removal, leaving usage unclear.

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 mentions installation and service management actions but lacks critical details like required permissions, side effects (e.g., system changes), error handling, or confirmation of success/failure states, which are essential for a setup 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 efficiently structured with a clear opening sentence followed by a bullet-point list of parameters, each with brief explanations. Every sentence earns its place without redundancy, making it easy to scan and understand.

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 (setup operations with multiple steps), no annotations, and an output schema (which should cover return values), the description is moderately complete. It outlines the main actions but misses operational details like platform limitations beyond macOS, error scenarios, or integration with sibling tools, leaving gaps for an AI agent.

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 description adds meaningful context for all four parameters beyond the input schema, which has 0% description coverage. It explains what each boolean flag does (install, start_service, pull_model) and provides a default value for the model parameter, compensating well for the schema's lack of documentation.

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 installs Ollama via Homebrew on macOS, specifying the verb (install), resource (Ollama), and platform constraint. However, it doesn't explicitly differentiate from its sibling 'firewall_setup_ollama_direct', which appears to serve a similar purpose, preventing a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'firewall_setup_ollama_direct' or other setup methods. It lists parameters but doesn't explain prerequisites, dependencies, or typical workflows, leaving usage context unclear.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes installation location (~/Applications) and background server startup, but doesn't mention permission requirements, error handling, what happens if installation fails, or system impact. For a setup tool with zero annotation coverage, this leaves significant behavioral gaps.

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

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

The description is efficiently structured with a clear purpose statement followed by parameter explanations. Every sentence adds value, though the parameter section could be slightly more concise. The information is appropriately front-loaded with the main purpose first.

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 an output schema (which handles return values), no annotations, and the description provides good parameter semantics despite 0% schema coverage, the description is reasonably complete. It covers the main purpose, platform constraints, and parameter meanings, though additional behavioral context would improve completeness for a setup tool.

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?

With 0% schema description coverage, the description provides meaningful parameter documentation that compensates well. It explains what each boolean parameter does (download/install, start server, pull model) and provides the default model value. However, it doesn't explain parameter interactions or dependencies between install/start_service/pull_model.

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 specific action (install Ollama via direct download), the target platform (macOS), and distinguishes it from alternatives (no Homebrew, no sudo). It explicitly differentiates from the sibling tool 'firewall_setup_ollama' by specifying the direct download method.

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 about when to use this tool (macOS installation without Homebrew or sudo), but doesn't explicitly state when NOT to use it or mention specific alternatives beyond the implied sibling tool. It gives good platform and method guidance but lacks explicit exclusion criteria.

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 of behavioral disclosure. While it mentions that the tool 'returns' specific data, it doesn't describe any behavioral traits such as whether this is a read-only operation, if it requires authentication, potential rate limits, or error conditions. The description is minimal and lacks context beyond the basic output structure.

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 extremely concise and well-structured. It uses only two sentences: one to state the purpose and another to detail the return format. Every word earns its place, with no redundant or unnecessary information. The output details are clearly formatted, making it easy for an agent to parse.

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 that there is an output schema (implied by the detailed return structure in the description), the description doesn't need to explain return values further. However, for a tool with no annotations and multiple sibling tools, it lacks context about when to use it and behavioral aspects. The description is adequate but has clear gaps in guidance and transparency.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the output. This meets the baseline expectation for tools with no parameters, as it doesn't waste space on irrelevant details.

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: 'Get firewall status and statistics.' This is a specific verb+resource combination that tells the agent exactly what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'firewall_system_check' or 'firewall_ollama_status,' which likely provide overlapping or related status information.

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 no guidance on when to use this tool versus alternatives. With multiple sibling tools related to firewall status (e.g., firewall_system_check, firewall_ollama_status), the agent receives no indication of what makes this tool distinct or when it should be preferred over others. The description merely states what it does, not when to use it.

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 describes what gets verified (macOS, Apple Silicon, RAM, Homebrew) but doesn't mention what happens if requirements aren't met, whether it requires specific permissions, or what the output format looks like. The description adds some behavioral context but leaves significant gaps.

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

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

The description is perfectly concise with two sentences that each earn their place. The first sentence states the purpose and verification criteria, while the second provides clear usage guidance. No wasted words 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 simple nature (0 parameters, has output schema), the description provides adequate context about what it does and when to use it. However, with no annotations and a verification tool that could have edge cases, it could benefit from more detail about failure modes or output interpretation.

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 tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, focusing instead on the tool's purpose and usage context.

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 specific action ('Check if system meets requirements') and the target resource ('Ollama embeddings'), with explicit verification criteria listed. It distinguishes itself from siblings like 'firewall_setup_ollama' by focusing on pre-setup verification rather than installation.

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 states when to use this tool ('Use before attempting Ollama setup'), providing clear context for its application. It differentiates from alternatives by positioning itself as a prerequisite check rather than a setup or status tool.

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