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

No annotations are provided, so the description must cover behavioral traits. It describes the return value (cleared count and per-port details) and the port convention (unspecified clears all ports). It does not mention permissions or side effects beyond clearing, but the behavior is adequately disclosed for a simple 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?

The description is structured with clear sections but is slightly verbose. However, every sentence adds value, and the key 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 no output schema, the description covers return values, parameter usage, and integrates with the test workflow (clear, then request device operation, then get_recent_logs). It is complete for the tool's complexity.

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 0%, so the description fully carries the burden. It explains the port parameter's default behavior (unspecified clears all ports) and how to target specific boards. This adds crucial 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: to clear the log buffer at the start of a black-box test for clean observation. It distinguishes from sibling tools like get_recent_logs by describing the subsequent retrieval step.

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?

Explicitly states when to call (start of test) and provides a standard procedure. It also references get_recent_logs for after clearing, guiding the agent on correct usage sequence.

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?

Describes return values (entries/capacity, oldest/newest, cumulative stats, dedup). Does not explicitly state read-only but from description it's clearly a read operation. No annotations provided, so description carries burden.

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?

Highly structured with clear sections (When to call, Port convention, Return value, Loop step). No redundant sentences. Front-loaded with usage context.

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?

Overall very complete given no output schema and one parameter. Explains return fields and typical use case. Only minor gap is port parameter explanation, relying on sibling reference.

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 has 0% coverage for the single 'port' parameter. Description only references the same convention as get_recent_logs, which is insufficient standalone. Agent must look up sibling tool to understand parameter meaning.

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?

Description clearly states the tool's purpose: to check buffer fullness and see recent/oldest items. It uses a specific verb ('볼 때') and resource ('버퍼'). It distinguishes from siblings by mentioning it's for buffer info, not log retrieval or clearing.

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?

Explicitly says when to call: to quickly see buffer state, especially after clear_log_buffer for polling. Provides context for parameter usage by referencing get_recent_logs convention.

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, description fully discloses behavior: returns recent N lines in time order, deduplicates nearby duplicates with summary showing repetition count and time range, warns that precise order is lost, and suggests adjusting SERIAL_DEDUP for precision.

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?

Description is structured with clear sections in brackets ([언제 호출], [port 규약], [무엇을 반환], [팁], [루프 단계]). Each section is concise and adds essential information 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 2 parameters with no schema descriptions and no output schema, the description fully covers usage context, port protocol, return format, deduplication behavior, alternatives, and troubleshooting. It is more than sufficient for agent to invoke 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?

Though schema coverage is 0%, description explains port behavior in detail (alias, multiple boards case) and implies lines parameter by mentioning recent N lines. However, it does not explicitly describe the 'lines' parameter or its default value. Well-articulated port semantics compensate for missing schema descriptions.

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?

Description starts with '[언제 호출] 블랙박스 루프의 '결과 확인' 단계' clearly stating when to use it. It specifies it retrieves recent logs and distinguishes from siblings by mentioning alternatives like query_serial_logs and get_serial_status.

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?

Explicitly states when to call after operating equipment, how to handle multiple boards with port specification, and provides troubleshooting tips: if too many results use query_serial_logs, if empty check get_serial_status then ask human.

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 that the tool returns status arrays and single status, and mentions last_error and viewer_url fields. It does not mention destructive actions or authentication needs, but the read-only nature is implied. Slight omission of explicit safety guarantees.

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 with clear sections ([언제 호출], [무엇을 반환], [루프 단계]), each serving a distinct purpose. It is concise yet comprehensive, with no redundant sentences.

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 simple tool (one optional param, no output schema, no annotations), the description provides complete context: usage trigger, return behavior for both cases, error interpretation, and even links to viewer_url. It effectively differentiates from sibling tools.

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 only one parameter (port, optional) and 0% schema description coverage, the description fully compensates by explaining the effect of omitting (returns all ports) vs specifying (returns a single port) the parameter. This adds significant semantic value 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: to check which board is connected when logs are not coming in, and to distinguish causes like port occupancy, unconnected, or unrecognized. It specifies the return behavior for both port unspecified and specified, making the purpose unambiguous.

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

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

The description provides explicit usage context: call when logs are not incoming to verify board connection. It also gives actionable guidance on interpreting errors (e.g., if connected false with last_error occupancy, ask user to close other programs) and suggests directing users to viewer_url for manual log viewing.

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?

Without annotations, the description details the returned fields (device, description, VID, PID, etc.) and adds conditional behavior about monitoring status. It does not mention side effects or permissions, but listing ports is inherently safe.

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 neatly organized into sections ('When to call', 'What it returns', 'Loop step') with no unnecessary words. Every sentence serves a purpose.

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?

Despite having no output schema, the description fully explains the return value and monitoring behavior. It also gives context on when and how to use the tool, making it self-contained.

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 zero parameters, so schema coverage is 100%. The baseline score is 4, and the description correctly provides no redundant parameter information.

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 lists serial ports and provides specific use cases (checking which port corresponds to which board, inspecting monitoring targets). It distinguishes itself from sibling log 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 gives explicit guidance on when to call (port/board identification, monitoring check) and notes it is a one-time pre-check. It lacks explicit 'when not to use' or alternatives, 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 full burden. It discloses return format (matching lines, newest first, time ascending, collapsed grouping) and behavior when no match is found. This is adequate for a query 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 structured with clear sections (언제 호출, port 규약, etc.), making it easy to parse. It is moderately concise with no extraneous content.

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 3 params, no output schema, and no annotations, the description covers usage context, return format, and error handling. However, it omits details like whether pattern is regex or literal, and the exact effect of max_results.

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 0%, so description must compensate. It explains pattern (keyword/error/marker) and port (protocol), but max_results is only mentioned by name without full meaning. Some semantic value is added, but not comprehensive.

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: to find specific keywords/errors/markers in a buffer. It distinguishes itself from siblings like get_recent_logs by focusing on pattern matching.

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-call (searching for specific strings) and port protocol (similar to get_recent_logs). It also advises on no-match scenarios. However, it lacks explicit when-not-to-use conditions.

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