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

With no annotations, the description carries the full burden. It discloses the method (uses MD5 hashes) and the goal (identify repeated payloads that may represent noise). It does not mention side effects, but as an analysis tool this is likely read-only, so the description provides adequate 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 succinct and front-loaded with the core purpose. It follows a clear structure: summary, method, args, returns, with no filler 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?

Given the output schema exists and sibling tools like open_can_log and get_session_info provide session context, the description is mostly complete. It could mention that a session must already be open, but the session_id parameter adequately implies this.

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 min_repetitions well ('Minimum number of repetitions to consider as noise') and notes the default of 10. However, session_id is only described as 'Session identifier', lacking context on how to obtain or use it, which leaves a gap.

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 'Analyze CAN bus payload repetition to detect noise in logs', which is a specific verb (analyze) and resource (payload repetition). This distinguishes it from sibling tools like query_can_messages and scan_payload_for_value, which focus on querying or scanning specific values.

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 use when analyzing CAN logs for noise, and the mention of 'noise' sets it apart from alternatives. However, it does not explicitly state when not to use this tool or name alternative tools, so exclusions are missing.

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 burden, and it does disclose that resources are released and that it returns a confirmation message. However, it omits details such as whether the operation is reversible, error behavior if no session exists, or any side effects on other tools.

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 concise and well-structured with Args and Returns sections. Every sentence adds value, and there is no redundant 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 simple one-parameter tool, the description covers purpose, argument semantics, and return value. However, the absence of annotation safety details and explicit side effects leaves minor gaps that prevent a perfect score.

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 only defines session_id with a default of null and no description; the description adds critical meaning by stating 'Session identifier (uses most recent if not provided),' clarifying the optional behavior. This compensates for the 0% schema coverage.

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 'Close the current session and release resources' with a specific verb and resource. This distinguishes it from siblings like open_can_log and other session-related 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?

There is no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., after open_can_log) or when not to use it, leaving the agent to infer from the name.

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 adds some context, such as 'Maximum frames to return' for limit and 'hex format' for can_id, but it does not explain timestamp formats, session_id semantics, or behavior when no filters are applied. This is a moderate effort.

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 well-structured docstring with a concise summary sentence, labeled Args section, and Returns section. It is appropriately sized with no unnecessary fluff, making it easy to scan.

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 has 6 optional parameters and an output schema, and the description gives enough to attempt a call. However, it leaves significant gaps: timestamp format is unspecified, session_id is unexplained, and there is no context about how filters combine or what happens with no filters. It is adequate but not 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?

The Args section provides a description for every parameter, adding meaning beyond the schema which has no descriptions. It includes helpful details like hex format for can_id and default value for limit, though some descriptions are terse (e.g., 'Start timestamp' without format).

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 'Extract specific CAN frames by ID, channel, or time range,' which uses a specific verb and resource. However, it does not differentiate from the sibling tool 'query_can_messages', so it lacks explicit sibling distinction.

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 filtering by ID, channel, or time range, but it provides no explicit guidance on when to use this tool versus alternatives like 'query_can_messages'. There are no stated exclusions or alternative recommendations.

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 that the tool 'Returns a list of error frames' but does not mention whether it is read-only, requires an open session, or has side effects. This lack of explicit safety and side-effect disclosure is a significant gap, similar to the update_drive example.

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 concise and well-structured, with a one-line summary followed by clearly labeled Args and Returns sections. Every sentence serves a purpose, and the format is front-loaded with the main purpose. No extraneous information is present.

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 covers the main purpose, all parameters, and return type, but it lacks important context about tool invocation, such as session prerequisites (e.g., requiring an open session) and when to choose this tool over siblings. While the output schema exists, the description does not explain how sessions are managed or what constitutes an 'anomaly.' This incomplete guidance leaves gaps for a moderately complex 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?

The schema provides no parameter descriptions (coverage 0%), so the description compensates by explaining all three parameters in the 'Args' section. It lists valid values for error_type, marks channel as an optional filter, and describes session_id as a session identifier. This adds meaningful detail beyond the bare schema, though it does not fully explain every term (e.g., 'gap' or 'timeout').

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 a specific verb and resource: 'Find error frames and anomalies in CAN bus logs.' It also lists specific error types, distinguishing it from sibling tools like query_can_messages and extract_can_frames, which target general messages or frame extraction. This makes the tool's unique function 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 implies usage by describing error-focused filtering, but it does not explicitly state when to use this tool over alternatives. No exclusions or sibling tool comparisons are provided. The error_type parameter list gives additional context but does not offer clear 'use this when' guidance.

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 exist, so the description bears the full burden. It implies a read-only operation via 'Retrieve' and adds a useful behavior note: 'uses most recent if not provided.' However, it does not explain error behavior, what happens if no session exists, or what 'session state information' specifically includes, leaving gaps for a simple getter.

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 remarkably concise: a one-line purpose statement followed by a clear Args/Returns structure. Every sentence earns its place, and the most important information is front-loaded. There is zero redundancy or 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?

Given the tool's simplicity (one optional parameter, output schema present), the description covers the essential aspects: what it does, the parameter's behavior, and a return summary. It omits potential error states and when to use it, but the output schema likely handles return structure, so the description is adequate for a getter.

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 does by explaining session_id's purpose ('Session identifier') and its optionality with the default behavior ('uses most recent if not provided'). This adds meaning beyond the raw schema, though it could go further with format constraints or edge cases.

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 a specific verb and resource: 'Retrieve information about the current session state.' It is distinguishable from siblings like query_can_messages or get_statistics, though it does not explicitly differentiate itself, which would warrant a 5. The mention of 'session state' makes the purpose clear without ambiguity.

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 does not mention any prerequisites, context, or scenarios where this tool is preferred over siblings like get_statistics or find_errors. The only implicit hint is the name, but that is insufficient.

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 must carry the burden of behavioral disclosure. It only says 'Generate statistical analysis' and 'Returns: Statistical data' without detailing side effects, dependencies on an open session, or whether this is a read-only operation. The lack of any behavioral caveats leaves significant transparency 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 well-structured: a clear opening sentence followed by a parameter list and a return line. It is not overly verbose, but the 'Returns: Statistical data' line is vague and adds little. Overall, the structure is efficient and avoids unnecessary 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?

With an output schema present, the vague return statement is acceptable, but the description lacks important context like whether a session must already be open, how the statistics relate to message queries, and when to choose this over sibling tools. It covers parameters adequately but leaves usage context incomplete.

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 compensates for the 0% schema coverage by explaining stat_type with example values, interval with formats, can_id as an optional filter, and session_id as an identifier. However, it does not elaborate on what each stat_type produces, the exact interval format, or the role of session_id beyond 'identifier', so the added meaning is partial.

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 'Generate statistical analysis of CAN bus traffic' — a specific verb and resource. However, it does not explicitly differentiate from sibling tools like analyze_payload_noise or find_errors, which could also involve statistical analysis, so it misses the top score for sibling distinction.

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?

No guidance is given on when to use this tool versus alternatives. The description simply lists arguments and a generic return. There is no mention of context, exclusions, or prerequisites, so the agent gets no help deciding between this and other analysis tools.

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 must disclose behavioral traits. It mentions session_id auto-generation and return of file info, but does not explain side effects like session state modification, error handling, or permission requirements.

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

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

The description is compact, front-loaded with the purpose, and organized with Args and Returns sections. No wasted words.

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, and the description covers purpose, parameters, and return info. However, it lacks usage context (e.g., need to open before querying) and behavioral details. The output schema exists, so return details are adequate.

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 compensates by explaining file_path as a path to Kvaser CAN log and session_id as a optional auto-generated identifier. This adds meaningful context beyond the schema's type/title.

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 'Open' with a resource 'Kvaser CAN bus log file' and clarifies it's in the current session. This clearly distinguishes it from sibling tools that query/analyze/extract data.

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 explicit guidance on when to use this tool vs siblings. It implies it's an entry point ('in the current session') but doesn't state prerequisites or alternatives.

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 full responsibility for disclosing behavioral traits. It mentions the underlying engine (lnav's SQL engine) and returns format ('columns and rows'), but does not disclose side effects, safety, prerequisites (e.g., an open log session), or error behavior. The omission of session_id's role and the requirement for an active session leaves significant behavioral ambiguity.

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 concise and well-structured: a clear purpose sentence, an args list with brief explanations, and a returns line. Every element serves a purpose, with no unnecessary detail.

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 covers the basic purpose and parameters, and an output schema exists to define return values. However, it lacks contextual information about session management (e.g., that querying requires an open log session via session_id), and the sibling tools imply a workflow that is not explained. This makes the description moderately complete but with notable gaps.

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 must compensate. It provides helpful hints like 'use table name frames' for query, max rows for limit, and 'Session identifier' for session_id, adding value beyond the schema. However, it does not explain how session_id relates to an open session or how to obtain it, leaving its semantics incomplete.

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: 'Execute SQL queries against CAN bus log data using lnav's SQL engine.' This is a specific verb (execute) and resource (CAN bus log data), and it distinguishes itself from siblings like open_can_log and extract_can_frames by emphasizing SQL-based querying.

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 for running SQL queries on CAN bus log data, but it does not explicitly state when to use this tool over alternatives like extract_can_frames or get_statistics, nor does it mention any exclusions. The context suggests SQL ad-hoc queries, but the guidance is only implied.

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. It discloses matching logic (consecutive bytes, binary representation, endianness), offset handling, and auto-calculated byte width. It lacks explicit mention of side effects, but the read-only nature is evident from the return of matching frames.

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 opening sentence is a concise summary, followed by well-structured Args and Returns sections. No fluff or redundancy exists; every line contributes to understanding the tool's operation.

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 covers all six parameters, matching behavior, and return format. Even though an output schema exists, the description adds useful context about what constitutes a match and the byte-width calculation. It is complete for a search tool with moderate 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?

The schema has zero descriptions for its properties, but the description's Args block thoroughly explains each parameter (byte_value, endianness, offsets, limit, session_id) with meanings and defaults. This adds significant value beyond the schema and fully compensates for the lack of property 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?

The description clearly states 'Scan CAN bus payload bytes for a specific decimal value', using a specific verb+resource. It adds details about binary representation and endianness, distinguishing it from sibling tools like query_can_messages or analyze_payload_noise.

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 usage is implied through the action description, but there is no explicit guidance on when to use this tool vs alternatives or when not to use it. No reference to sibling tools or exclusions is provided, so the context is clear but not explicitly guided.

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