Serena

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

Annotations indicate readOnlyHint=true and destructiveHint=false, which the description does not contradict. The description adds minimal behavioral context by implying activation of a project, but it doesn't elaborate on effects like environment changes or permissions needed. With annotations covering safety, the description provides some value but not rich 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 a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured for quick understanding.

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 moderate complexity (activation operation), high schema coverage, annotations, and the presence of an output schema, the description is reasonably complete. It covers the basic action but could benefit from more context on outcomes or integration with sibling tools, though the structured data reduces the burden on the description.

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 100% description coverage, clearly documenting the 'project' parameter. The description adds no additional meaning beyond the schema, such as examples or constraints, but since the schema is comprehensive, a baseline score of 3 is appropriate as the description doesn't compensate unnecessarily.

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 ('activates') and the resource ('the project with the given name or path'), making the purpose specific and understandable. However, it does not differentiate this tool from sibling tools like 'switch_modes' or 'get_current_config', which might relate to project state changes, so it doesn't fully distinguish from alternatives.

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 'switch_modes' or 'get_current_config', nor does it mention prerequisites like needing a registered project. It lacks explicit when/when-not instructions or named alternatives, 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?

Annotations indicate readOnlyHint=true and destructiveHint=false, which the description aligns with by implying a non-destructive check. The description adds value by specifying the tool's role in workflow sequencing (before work/after activation), but doesn't provide additional behavioral details like error handling or output interpretation beyond what annotations cover.

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 two sentences, front-loaded with the core purpose followed by usage guidelines. Every word serves a clear function, with no redundancy or unnecessary elaboration, making it highly 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 has 0 parameters, annotations covering safety (read-only, non-destructive), and an output schema (implied by context signals), the description is reasonably complete. It explains what the tool does and when to use it, though it could benefit from hinting at the output's meaning (e.g., boolean result or status details) to fully compensate for lack of output schema explanation.

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 no parameter documentation is needed. The description doesn't mention parameters, which is appropriate. A baseline of 4 is applied since no parameters exist, and the description focuses correctly on the tool's purpose and usage.

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: 'Checks whether project onboarding was already performed.' It specifies the verb ('checks') and resource ('project onboarding'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'onboarding' or 'activate_project', which might have overlapping contexts.

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 guidelines: 'You should always call this tool before beginning to actually work on the project/after activating a project.' This gives clear timing and context for when to use it, including a reference to the sibling tool 'activate_project' as a related action.

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?

Annotations already indicate destructiveHint=true and readOnlyHint=false, but the description adds valuable context by specifying that it can 'overwrite an existing file' and returns 'success or failure' messages. This clarifies the destructive nature beyond the annotation and provides outcome expectations, though it doesn't mention permissions, rate limits, or file encoding 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 consists of two tightly focused sentences that efficiently convey the core functionality and outcome. Every word serves a purpose with zero redundancy, and the information is front-loaded with the primary action stated immediately.

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 destructive nature indicated by annotations, the presence of an output schema, and 100% parameter coverage, the description provides adequate context. It covers the tool's primary behavior and outcome expectations, though it could benefit from mentioning encoding requirements or error scenarios for a more complete picture.

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 100% schema description coverage, the input schema fully documents both parameters. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline score of 3. No additional semantic context is provided for 'relative_path' or 'content' 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 clearly states the specific action ('Write a new file or overwrite an existing file') and resource ('file'), distinguishing it from sibling tools like 'read_file' or 'replace_content'. It precisely communicates both creation and overwrite capabilities in a single concise statement.

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 file creation/overwriting but provides no explicit guidance on when to use this tool versus alternatives like 'replace_content' or 'write_memory'. It mentions the tool's behavior but doesn't specify scenarios where it's preferred over other file manipulation tools in the sibling list.

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?

Annotations already indicate destructiveHint=true and readOnlyHint=false, which cover the core safety profile. The description adds valuable context beyond this by emphasizing the need for explicit user consent and providing rationale examples, which helps the agent understand the gravity of the operation. It doesn't detail error conditions or output behavior, but with annotations present, this is sufficient.

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 two sentences that are front-loaded with the core action and immediately followed by critical usage guidelines. Every word serves a purpose, with no redundancy or fluff, making it highly efficient and easy to parse for an AI agent.

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 destructive nature, the description effectively complements the annotations by stressing user consent and providing examples. With an output schema present, it doesn't need to explain return values. The combination of clear purpose, strong guidelines, and annotations makes this description sufficiently complete for safe agent use.

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% description coverage, with only one parameter ('memory_file_name') documented structurally. The description doesn't add any parameter-specific information, such as format examples or constraints. However, with a single parameter and the tool's clear purpose, the baseline of 3 is appropriate as the schema alone provides minimal but adequate 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 the action ('Delete') and resource ('a memory file'), making the purpose immediately understandable. It distinguishes from sibling tools like 'edit_memory', 'read_memory', and 'write_memory' by specifying deletion rather than modification or retrieval. However, it doesn't explicitly contrast with 'list_memories' or other file-related tools beyond the verb itself.

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 guidance on when to use this tool: 'only if a user asks for it explicitly', with concrete examples ('information retrieved from a memory file is no longer correct or no longer relevant for the project'). This clearly defines the appropriate context and helps the agent avoid misuse, especially given the destructive nature implied by the tool 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?

Annotations already declare readOnlyHint=false and destructiveHint=true, indicating this is a mutation tool with destructive potential. The description adds useful context about regex matching behavior (Python re module with DOTALL/MULTILINE flags) and the replacement being verbatim, which goes beyond annotations. However, it doesn't mention error conditions, side effects, or what happens when no match is found.

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, efficient sentence that front-loads the core functionality ('Replaces content matching a regular expression in a memory'). Every word earns its place with no redundancy or unnecessary elaboration.

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 (regex editing with destructive potential), the description provides adequate context when combined with rich annotations and a complete input schema. However, it could benefit from mentioning the existence of an output schema (which handles return values) and providing more behavioral context about edge cases. The combination of description, annotations, and schema is mostly 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?

With 100% schema description coverage, all parameters are well-documented in the schema itself. The description doesn't add significant semantic information beyond what's already in the parameter descriptions, which thoroughly explain memory_file_name, needle (with mode-specific behavior), repl, and mode. The baseline of 3 is appropriate when the schema does the heavy lifting.

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

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

The description clearly states the specific action ('Replaces content') on a specific resource ('in a memory') using a specific method ('matching a regular expression'). It distinguishes from siblings like 'replace_content' (general file replacement) and 'write_memory' (full overwrite) by specifying regex-based partial editing of memory files.

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 regex-based editing of memory content, but doesn't explicitly state when to use this vs alternatives like 'replace_content' for non-memory files or 'write_memory' for complete overwrites. It provides clear context about the operation type but lacks explicit exclusion 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?

Annotations already indicate destructiveHint=true and readOnlyHint=false, but the description adds valuable behavioral context beyond this: it warns against unsafe commands, specifies output truncation behavior via max_answer_chars, mentions checking memory first, and describes the JSON return structure. This provides important safety and operational guidance that annotations alone don't cover.

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, followed by important warnings and return format details. While some sentences could be more concise (e.g., the warning about long-running processes is slightly verbose), overall it's efficient with each sentence serving a clear 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?

Given the tool's complexity (destructive shell command execution), rich annotations (destructiveHint=true), complete schema coverage, and existence of an output schema, the description provides excellent contextual completeness. It covers safety warnings, usage constraints, memory integration, and output behavior, making it fully adequate for an AI agent to understand when and how to use 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?

With 100% schema description coverage, the input schema already fully documents all 4 parameters. The description doesn't add any parameter-specific semantics beyond what's in the schema descriptions, so it meets the baseline expectation without providing additional value about parameter usage or interactions.

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 ('execute a shell command and return its output') and distinguishes it from siblings by focusing on command execution rather than file operations, memory management, or project configuration. It goes beyond just restating the name/title by specifying the return format and behavioral constraints.

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 guidance on when NOT to use this tool (for long-running processes or processes requiring user interaction) and references checking memory for suggested commands first. However, it doesn't explicitly name alternative tools for those excluded use cases or differentiate from similar tools like list_dir for directory operations.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds useful behavioral context by specifying 'non-gitignored files' (exclusion behavior) and the return format ('JSON object with the list of matching files'), but does not mention potential limitations like recursion depth or performance 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 a single, efficient sentence that front-loads the core functionality and includes essential details (exclusion of gitignored files, return format) without any 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?

Given the tool's moderate complexity, rich annotations (readOnlyHint, destructiveHint), 100% schema coverage, and presence of an output schema, the description is complete enough. It covers purpose, key behavioral trait (non-gitignored), and return format, leaving detailed parameter and output documentation to the structured fields.

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%, with both parameters well-documented in the schema. The description adds minimal value beyond the schema by implying the search scope and exclusion of gitignored files, but does not provide additional syntax or format details for the 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 clearly states the specific action ('Finds'), resource ('non-gitignored files'), and scope ('matching the given file mask within the given relative path'), distinguishing it from siblings like 'list_dir' (which lists directory contents) and 'search_for_pattern' (which searches file content).

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 (searching for files by name/mask, excluding gitignored files), but does not explicitly state when not to use it or name alternatives like 'list_dir' for directory listing or 'search_for_pattern' for content search.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds useful behavioral context beyond annotations by specifying what the result contains (metadata about referencing symbols and short code snippets) and that it returns a list of JSON objects. However, it doesn't mention potential limitations like performance impacts or result size constraints.

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 in two sentences with zero waste. The first sentence states the core functionality and result format, while the second clarifies the return type. Every word contributes to understanding the tool's purpose and output.

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 presence of annotations (readOnlyHint, destructiveHint), 100% schema coverage, and an output schema (implied by 'Returns a list of JSON objects'), the description provides complete contextual information. It adequately explains what the tool does, what it returns, and references sibling tools where appropriate, making it sufficient for agent understanding.

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 100% schema description coverage, the input schema already documents all 5 parameters thoroughly, including references to the 'find_symbol' tool for parameter behavior. The description doesn't add significant semantic information beyond what's in the schema, maintaining the baseline score of 3 for adequate but not enhanced parameter 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's purpose with a specific verb ('Finds references') and resource ('the symbol at the given name_path'), and distinguishes it from sibling tools by specifying it returns referencing symbols rather than finding symbols themselves. It explicitly mentions what the result contains (metadata and code snippets), 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 implies usage context by mentioning the tool finds references to a symbol, suggesting it should be used when you need to know where a symbol is referenced. However, it doesn't explicitly state when to use this tool versus alternatives like 'find_symbol' or provide exclusion criteria, though the parameter descriptions reference 'find_symbol' for some parameters.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description adds valuable behavioral context beyond annotations: it explains that results can be used for edits, describes the matching logic (simple name, relative path, absolute path), mentions overload handling with indices, and notes performance considerations (using relative_path speeds up search). It does not contradict annotations.

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 detailed explanations of name paths and patterns. While comprehensive, it is appropriately sized for a complex tool with many parameters. Some sentences could be more concise (e.g., the name path explanation is lengthy), but overall it avoids unnecessary repetition.

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, 100% schema coverage, annotations, and an output schema), the description is complete. It covers purpose, usage examples, behavioral nuances (like overload handling and performance tips), and does not need to explain return values since an output schema exists. It adequately complements the structured data without 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 description coverage is 100%, so the schema already documents all 8 parameters thoroughly. The description adds some semantic context for name_path_pattern (explaining patterns and examples) and depth (linking it to retrieving children), but most parameter details are already in the schema. This meets the baseline of 3 for high 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 the tool's purpose with specific verbs ('retrieves information on all symbols/code entities') and distinguishes it from siblings by focusing on symbol lookup rather than file operations (find_file), pattern searching (search_for_pattern), or symbol editing (rename_symbol, replace_symbol_body). It explicitly mentions what the returned information can be used for ('for edits or further queries'), which helps differentiate its role.

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 (e.g., 'Specify `depth > 0` to also retrieve children/descendants') and implies alternatives through sibling tool names like find_file or search_for_pattern, but it does not explicitly state when not to use it or name specific alternatives. The guidance on using the relative_path parameter for speed and reduced results offers practical usage advice.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds valuable context by specifying what configuration components are included (projects, tools, contexts, modes), which isn't inferable from annotations alone. However, it doesn't mention output format details or potential limitations.

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, efficient sentence that front-loads the core action ('Print the current configuration') and then enumerates included components. Every word adds value with 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 (0 parameters, read-only, non-destructive), the description fully covers its purpose and scope. With annotations providing safety context and an output schema existing (so return values needn't be described), the description is complete for this low-complexity 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 parameters and 100% schema description coverage, the baseline is 4. The description appropriately doesn't discuss parameters since none exist, avoiding unnecessary detail while clearly indicating the tool operates without inputs.

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 ('Print') and the exact resource ('current configuration of the agent'), listing all included components (active/available projects, tools, contexts, modes). It distinguishes itself from siblings like 'get_symbols_overview' or 'list_memories' by focusing on overall agent configuration rather than specific data subsets.

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 needing to inspect the agent's configuration state, but provides no explicit guidance on when to use this versus alternatives like 'check_onboarding_performed' or 'switch_modes'. It doesn't specify prerequisites, exclusions, or comparative contexts with sibling 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds valuable context beyond this by specifying that it returns 'a JSON object containing info about top-level symbols in the file,' which clarifies the output format. However, it doesn't mention potential limitations like rate limits or error conditions, leaving some behavioral aspects uncovered.

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 in three sentences: the first states the purpose, the second provides usage guidelines, and the third describes the return format. Each sentence adds essential value without redundancy, making it front-loaded and appropriately concise for the tool's complexity.

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 moderate complexity, rich annotations (readOnlyHint, destructiveHint), 100% schema coverage, and the presence of an output schema, the description is complete enough. It covers purpose, usage context, and output format, leaving detailed parameter and return value documentation to the structured fields, which is appropriate for this setup.

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 fully documents all three parameters. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain 'relative_path' context or 'depth' implications further). This meets the baseline of 3 since the schema carries the full burden, but the description doesn't compensate with extra insights.

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 ('get a high-level understanding of the code symbols in a file') and resource ('file'), distinguishing it from sibling tools like 'find_symbol' or 'read_file' by focusing on symbol overview rather than searching or raw content. It explicitly positions this as the first tool for understanding new files, making its purpose distinct and 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 explicit guidance on when to use this tool ('first tool to call when you want to understand a new file') and when not to ('unless you already know what you are looking for'), effectively differentiating it from alternatives like 'find_symbol' for targeted searches. This clear contextual advice helps the agent choose appropriately 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds that it provides 'essential information' and is 'critical' to inform the agent, which adds context about importance. However, it doesn't specify format, length, or structure of the manual content beyond what annotations provide.

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 concise with two sentences that each serve distinct purposes: stating what the tool provides and giving critical usage instructions. It's front-loaded with the core purpose, though the second sentence could be slightly more streamlined.

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 0 parameters, annotations covering safety, and an output schema exists, the description provides adequate context about purpose and critical timing. It doesn't need to explain return values since output schema exists, but could optionally hint at manual content format for slightly better 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 parameters and 100% schema description coverage, the baseline is 4. The description appropriately doesn't discuss parameters since none exist, focusing instead on the tool's purpose and usage timing.

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 'provides the Serena Instructions Manual' which is a specific resource, though it doesn't specify the exact content or format of the manual. It distinguishes itself from siblings by being the only tool focused on providing essential instructions rather than performing project 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 explicit usage guidance: 'If you have not yet read the manual, call this tool immediately after you are given your task by the user, as it will critically inform you!' This clearly indicates when to use it (immediately after task assignment if manual not read) and implies it's foundational before using other 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?

Annotations already indicate destructiveHint=true and readOnlyHint=false, but the description adds valuable behavioral context: it specifies that insertion occurs 'after the end of the definition' and that 'the inserted code shall begin with the next line after the symbol.' This clarifies the exact positioning behavior beyond what annotations provide.

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: the first states the core functionality, the second provides a typical use case. Every word earns its place, and the most important information (what the tool does) 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 the presence of both annotations (destructiveHint=true, readOnlyHint=false) and an output schema (implied by context signals), the description provides complete contextual information. It covers the tool's purpose, typical usage, and behavioral specifics without needing to explain return values or safety characteristics that are already documented elsewhere.

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 100% schema description coverage, all parameters are already documented in the input schema. The description adds some context by mentioning 'symbol's location' and referencing 'find_symbol' for name_path, but doesn't provide significant additional semantic meaning beyond what's in the 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?

The description clearly states the specific action ('inserts') and target ('after the end of the definition of the given symbol'), with explicit mention of the content being inserted ('body/content'). It distinguishes from sibling 'insert_before_symbol' by specifying 'after' positioning, and from 'replace_symbol_body' by indicating insertion rather than replacement.

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 ('to insert a new class, function, method, field or variable assignment') and references the 'find_symbol' tool for determining symbol locations. However, it doesn't explicitly state when NOT to use it or directly compare with alternatives like 'insert_before_symbol' or 'replace_content'.

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?

Annotations indicate destructiveHint=true and readOnlyHint=false, which the description aligns with by describing an insertion operation that modifies files. The description adds valuable context beyond annotations by specifying that insertion occurs 'before the beginning of the definition' and via 'the symbol's location', and mentions typical use cases, which helps the agent understand the tool's behavior in practical scenarios.

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 in the first sentence, followed by a second sentence providing typical use cases. Both sentences earn their place by clarifying scope and practical applications without redundancy or unnecessary details.

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 moderate complexity (file modification with symbol-based positioning), the description provides sufficient context alongside annotations (destructive, not read-only) and a complete input schema. With an output schema present, the description does not need to explain return values, making it complete for agent usage.

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%, providing clear documentation for all three parameters (name_path, relative_path, body). The description adds minimal semantic value beyond the schema, only implying that 'body' is content to insert and referencing 'find_symbol' for name_path definitions. This meets the baseline of 3 when schema coverage is high.

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 ('inserts') and resource ('content before the beginning of the definition of the given symbol'), with specific examples of typical use cases (new class, function, method, field, variable assignment, or import statement). It distinguishes from sibling 'insert_after_symbol' by specifying 'before' rather than 'after'.

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 ('to insert a new class, function, method, field or variable assignment; or a new import statement before the first symbol in the file'), but does not explicitly state when not to use it or name alternatives beyond the implied sibling 'insert_after_symbol'. It lacks explicit exclusions or prerequisites.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds value by specifying the return format ('JSON object with names of directories and files') and hinting at recursion behavior, but does not disclose additional traits like rate limits, auth needs, or error conditions beyond what annotations provide.

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 in the first sentence and adds useful details in the second. Both sentences earn their place by clarifying functionality and output format without redundancy or unnecessary elaboration, making it efficient and well-structured.

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 moderate complexity, rich annotations (readOnlyHint, destructiveHint), and the presence of an output schema, the description is largely complete. It covers purpose, optional recursion, and return format, though it could benefit from more explicit usage guidelines or edge-case handling to be fully comprehensive.

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 parameters are fully documented in the schema. The description adds minimal semantics by mentioning recursion and the return format, but does not provide extra details on parameter usage or interactions beyond what the schema already covers, aligning with the baseline for high 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 the verb ('Lists') and resource ('files and directories'), specifies the scope ('in the given directory'), and mentions an optional feature ('with recursion'). It distinguishes itself from sibling tools like 'find_file' or 'search_for_pattern' by focusing on directory listing rather than searching or filtering.

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 directory listing but does not explicitly state when to use this tool versus alternatives like 'find_file' or 'search_for_pattern'. It mentions recursion as an option but lacks guidance on scenarios where recursion is preferred or when to avoid it, leaving usage context somewhat 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description adds no behavioral traits beyond this, such as pagination, sorting, or access constraints, relying entirely on annotations for safety disclosure.

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 with two sentences that are front-loaded and waste-free. Every word contributes to understanding the tool's purpose and usage, making it efficient and well-structured.

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 (0 parameters, read-only, non-destructive) and the presence of annotations and an output schema, the description is complete enough for basic use. It could benefit from more detail on output format or limitations, but the essentials are covered.

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 parameters and 100% schema description coverage, the schema fully documents the lack of inputs. The description doesn't need to add parameter details, and its mention of 'available memories' implies no filtering, which aligns with the empty schema. Baseline is 4 for zero 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 clearly states the tool's purpose with a specific verb ('List') and resource ('memories'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'read_memory' beyond mentioning it as a follow-up action, missing direct comparison.

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 by stating that listed memories can be read with 'read_memory', implying usage as a precursor to that tool. It doesn't specify when not to use it or alternatives, but the guidance is sufficient for basic navigation.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds context about the one-time-per-conversation constraint and that it returns instructions, which are useful behavioral details beyond the annotations. However, it doesn't describe error handling or what happens if called multiple times.

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 with two sentences: the first states when to call it, and the second specifies the call frequency and return value. Every sentence 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 the tool has 0 parameters, annotations covering safety, and an output schema (implied by context signals), the description is mostly complete. It covers purpose, usage guidelines, and behavioral constraints. However, it could briefly mention what the instructions entail or link to sibling tools for more context, but the output schema likely handles return values.

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 usage context. A baseline of 4 is applied since there are no parameters to document.

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 be called when onboarding hasn't been performed yet, and it returns instructions for creating onboarding information. It specifies the verb 'call' and the resource 'onboarding', but doesn't explicitly differentiate from sibling tools like 'check_onboarding_performed' or 'initial_instructions' beyond the conditional trigger.

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 guidelines: 'Call this tool if onboarding was not performed yet' and 'You will call this tool at most once per conversation.' This clearly defines when to use it (onboarding not done) and includes a usage constraint (once per conversation), though it doesn't name specific alternatives 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe, non-destructive operation. The description adds no behavioral context beyond what annotations provide, such as what 'preparing' entails or any side effects. However, it doesn't contradict annotations.

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 two short sentences with zero wasted words. It's appropriately sized and front-loaded, though the first sentence is uninformative. Every sentence serves a purpose: the first states the tool's name, and the second provides critical usage guidance.

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 zero parameters, annotations covering safety, and an output schema (which means return values are documented elsewhere), the description is minimally adequate. However, it fails to explain what 'preparing for a new conversation' actually means or what the tool does, leaving a significant gap in understanding its purpose.

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, and schema description coverage is 100%. With no parameters to document, the description doesn't need to compensate for any gaps. The baseline for zero parameters is 4, as there's nothing to explain beyond the empty 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 'Instructions for preparing for a new conversation' is a tautology that restates the tool's name/title without specifying what the tool actually does. It lacks a clear verb+resource combination and doesn't distinguish this tool from its many siblings.

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 'This tool should only be called on explicit user request,' providing clear when-to-use guidance. This is a strong, unambiguous usage rule that helps the agent avoid inappropriate invocations.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds valuable context beyond this: it explains that it can read 'a chunk' of a file (via start_line/end_line parameters) and warns about the max_answer_chars constraint ('no content will be returned' if exceeded). This enhances behavioral understanding without contradicting annotations.

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 in two sentences: the first states the core functionality and preferred alternatives, the second clarifies the return value. Every sentence serves a clear purpose with zero wasted words, making it easy to parse 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 moderate complexity (4 parameters, 1 required), 100% schema coverage, annotations covering safety, and an output schema (implied by 'Returns...'), the description is complete. It covers purpose, guidelines, and key behavioral aspects without needing to repeat schema details or explain return values extensively.

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 fully documents all four parameters. The description mentions 'chunk' reading and the max_answer_chars behavior, but these details are already covered in the schema descriptions for start_line, end_line, and max_answer_chars. It adds minimal semantic value beyond what the structured schema provides.

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 ('Reads') and resource ('the given file or a chunk of it'), distinguishing it from sibling tools like find_symbol or find_referencing_symbols. It explicitly mentions what it returns ('full text of the file at the given relative path'), making the purpose unambiguous and 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 explicit guidance on when to use alternatives: 'Generally, symbolic operations like find_symbol or find_referencing_symbols should be preferred if you know which symbols you are looking for.' This clearly indicates when not to use this tool and names specific sibling alternatives, offering strong contextual 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating this is a safe read operation. The description adds valuable behavioral context beyond annotations: it specifies relevance criteria (based on file name) and a usage constraint (no repeated reads in same conversation). However, it doesn't disclose other potential behaviors like error handling, response format, or performance characteristics.

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 in three sentences: the first states the core purpose, the second provides usage criteria, and the third adds a behavioral constraint. Every sentence adds value without redundancy, and it's front-loaded with the essential action. No wasted words or unnecessary elaboration.

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 moderate complexity (a read operation with relevance filtering), annotations cover safety (read-only, non-destructive), and an output schema exists (so return values needn't be described), the description is reasonably complete. It adds useful context like relevance criteria and usage limits, though it lacks parameter explanations and doesn't fully address sibling tool differentiation.

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 schema provides no parameter documentation. The description doesn't explain either parameter's semantics—it mentions 'memory file name' but doesn't clarify its format or source, and omits 'max_answer_chars' entirely. Since parameters are few (2) and one has a default, the baseline is 3, but the description fails to compensate for the coverage 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 the verb ('Read') and resource ('content of a memory file'), making the purpose unambiguous. It distinguishes this tool from siblings like 'list_memories' (which lists files) and 'write_memory' (which writes content). However, it doesn't explicitly contrast with 'read_file' (which reads general files), leaving some sibling differentiation incomplete.

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 guidance on when to use this tool ('if the information is relevant to the current task') and when not to use it ('should not read the same memory file multiple times in the same conversation'). It also implies alternatives by referencing the memory file name for relevance inference, though it doesn't name specific sibling tools like 'list_memories' for discovery.

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?

Annotations already indicate destructiveHint=true and readOnlyHint=false, but the description adds valuable context: it specifies the scope ('throughout the entire codebase'), mentions language-specific considerations (Java method overloading), and describes the return format ('result summary indicating success or failure'). This goes beyond what annotations provide.

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 sized at three sentences, front-loaded with the core purpose, followed by important implementation notes and return value information. Every sentence earns its place with 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?

Given the destructive nature (annotations), 3 parameters with full schema coverage, and the existence of an output schema, the description provides complete context. It covers purpose, scope, language considerations, and return format without needing to explain parameters or output details already documented elsewhere.

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 100% schema description coverage, the schema already documents all three parameters thoroughly. The description adds minimal extra context: it references 'find_symbol' tool for name_path definitions and mentions method signatures for overloading, but doesn't provide significant additional parameter semantics 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 verb ('renames') and resource ('symbol with the given name_path'), specifying scope ('throughout the entire codebase'). It distinguishes from siblings like 'replace_symbol_body' by focusing on renaming rather than content replacement.

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 (renaming symbols across codebases) and includes a note about method overloading in languages like Java. However, it doesn't explicitly state when NOT to use it or name specific alternatives 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?

Annotations indicate destructiveHint=true and readOnlyHint=false, which the description aligns with by describing a replacement operation. The description adds valuable behavioral context beyond annotations: it explains error handling when allow_multiple_occurrences is false, provides regex performance optimization tips, and mentions retry capabilities. However, it doesn't cover rate limits or specific 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 appropriately front-loaded with the core purpose, but contains some redundancy in advocating for regex mode (mentioned multiple times with similar points). The 'VERY IMPORTANT' section could be more streamlined, though all sentences contribute meaningful guidance about tool usage strategies.

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 (destructive file operation with regex capabilities), the description provides comprehensive context: it explains when to use this versus alternatives, offers detailed regex usage strategies, describes error behavior, and references sibling tools. With annotations covering safety aspects and an output schema presumably handling return values, the description fills all necessary contextual 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?

With 100% schema description coverage, the baseline is 3. The description adds meaningful context about parameter usage: it emphasizes regex mode advantages for large sections, explains wildcard strategies to avoid exact content specification, and clarifies the interaction between regex patterns and the allow_multiple_occurrences parameter. This provides practical guidance beyond the schema's technical specifications.

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 ('replaces one or more occurrences of a given pattern in a file with new content') and distinguishes it from sibling tools by mentioning 'symbol-level tools' as alternatives. It explicitly names the resource (file content) and operation (replacement).

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 guidance on when to use this tool ('preferred way to replace content... whenever the symbol-level tools are not appropriate') and offers detailed advice on regex mode usage versus literal mode. It also references sibling tools like 'replace_symbol_body' as alternatives for symbol-level operations.

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?

Annotations indicate destructiveHint=true and readOnlyHint=false, which the description aligns with by implying a mutation ('Replaces'). The description adds valuable context beyond annotations: it clarifies that the body excludes 'preceding docstrings/comments or imports,' specifies a prerequisite (previous retrieval via find_symbol), and warns about misuse if the body is unclear. This enhances behavioral understanding without contradicting annotations.

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 in the first sentence, followed by usage guidelines and a critical warning. Each sentence earns its place by providing essential information without redundancy, resulting in a well-structured and efficient text.

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 (destructive mutation with 3 required parameters), the description is complete: it covers purpose, usage context, prerequisites, and critical warnings. With annotations providing safety cues and an output schema present (implying return values are documented elsewhere), no additional information is needed for effective tool selection and 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%, providing detailed parameter documentation (e.g., 'body' includes the definition excluding docstrings). The description adds minimal semantics beyond the schema, such as linking 'name_path' to 'find_symbol' logic, but does not significantly enhance parameter understanding. With high schema coverage, a baseline score of 3 is appropriate.

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 ('Replaces the body of the symbol') and identifies the target resource ('symbol with the given name_path'). It distinguishes from siblings like 'rename_symbol' (which changes the name) and 'replace_content' (which replaces file content rather than symbol bodies), establishing a unique purpose.

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 guidance on when to use ('to replace symbol bodies that have been previously retrieved via find_symbol') and when not to use ('Do not use this tool if you do not know what exactly constitutes the body of the symbol'). It also references a specific alternative tool ('find_symbol') for preparation, offering clear context for usage.

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?

Annotations indicate readOnlyHint=true and destructiveHint=false, which the description aligns with by describing a search operation. The description adds significant behavioral context beyond annotations, detailing pattern matching logic (e.g., DOTALL compilation, line inclusion, greedy vs. non-greedy quantifiers) and file selection logic (e.g., glob patterns, restrictions), though it doesn't explicitly mention rate limits or auth needs, which are not contradictory.

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 ('Pattern Matching Logic', 'File Selection Logic') and front-loaded key information. It is appropriately sized, but some sentences could be more concise (e.g., the explanation of DOTALL and greedy quantifiers is slightly verbose), though overall it avoids waste and is easy to follow.

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 complexity of the tool (8 parameters, regex patterns, file restrictions) and the presence of annotations and an output schema (implied by 'Returns A mapping of file paths to lists of matched consecutive lines'), the description is complete. It covers usage scenarios, behavioral details, and parameter interactions without needing to explain return values, making it sufficient for an AI agent to use the tool 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 100%, so the schema already documents all parameters thoroughly. The description adds some value by explaining the purpose of parameters like 'restrict_search_to_code_files' and how glob patterns work relative to the project root, but it doesn't provide significant additional semantics beyond what's in the schema, warranting a baseline score 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 clearly states the tool's purpose: 'Offers a flexible search for arbitrary patterns in the codebase, including the possibility to search in non-code files.' It specifies the verb ('search'), resource ('patterns in the codebase'), and scope ('including non-code files'), and distinguishes it from sibling tools by explicitly mentioning alternatives like 'find_symbol' and 'find_referencing_symbols'.

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 guidance on when to use this tool versus alternatives: 'Generally, symbolic operations like find_symbol or find_referencing_symbols should be preferred if you know which symbols you are looking for.' It also advises on context, such as using 'restrict_search_to_code_files' for code symbols and setting it to 'False' for non-code files, offering clear alternatives and 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?

Annotations indicate readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe, non-destructive operation. The description adds minimal context by implying activation of modes, but doesn't disclose behavioral traits like what 'activation' entails (e.g., state changes, side effects, or interactions with other tools). It doesn't contradict annotations, but offers little beyond them.

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, efficient sentence that front-loads the purpose with examples. It avoids unnecessary words and gets straight to the point. However, it could be slightly more structured by explicitly stating the tool's role in the context of sibling tools, but as-is, it's concise and well-formed.

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), annotations covering safety, and high schema coverage, the description is minimally adequate. It explains the basic action but lacks context on what modes are, how they interact with other tools, or when to use this. For a tool that likely changes system state (despite readOnlyHint), more detail on behavior and usage 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?

Schema description coverage is 100%, with the parameter 'modes' fully documented in the schema. The description adds value by providing examples (e.g., ['editing', 'interactive']), which clarify the expected format and possible values beyond the schema's generic array of strings. However, it doesn't explain semantics like what modes are available or their effects, keeping it at the baseline for high 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 the verb ('Activates') and resource ('the desired modes'), making the purpose understandable. It provides specific examples like 'editing', 'interactive', 'planning', and 'one-shot' which help illustrate what modes might be. However, it doesn't explicitly differentiate from sibling tools like 'activate_project' or 'get_current_config', which could cause confusion about when to use this versus those alternatives.

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 prerequisites, context for activation, or exclusions. Given sibling tools like 'activate_project' and 'get_current_config', the lack of differentiation leaves the agent without clear usage rules, relying solely on the tool name and description which are vague about scope.

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?

Annotations indicate readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe, non-destructive operation. The description adds context about when to call it (after searching steps), which is useful behavioral guidance beyond the annotations. However, it doesn't disclose details like what the tool actually does (e.g., returns analysis, triggers internal processing) or any rate limits, leaving some behavioral aspects unclear.

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 two sentences that are front-loaded with the core purpose and followed by specific usage guidelines. Every sentence adds value without redundancy, making it highly concise and well-structured for quick understanding.

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 0 parameters, annotations cover safety (read-only, non-destructive), an output schema exists (so return values are documented elsewhere), and the description provides clear usage context, it's mostly complete. However, it could be more explicit about what the tool outputs or how it aids decision-making, slightly reducing 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?

The tool has 0 parameters, and schema description coverage is 100%, so there's no need for parameter details in the description. The description appropriately doesn't discuss parameters, which is efficient. A baseline of 4 is applied since no parameters exist, and the description doesn't introduce unnecessary complexity.

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 states the tool is for 'thinking about collected information' and assessing sufficiency/relevance, which gives a general purpose. However, it's somewhat vague about what specific action the tool performs (e.g., does it analyze, summarize, or just prompt reflection?) and doesn't clearly differentiate from sibling tools like 'think_about_task_adherence' or 'think_about_whether_you_are_done' beyond the information focus.

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 guidance: it states the tool 'should ALWAYS be called after you have completed a non-trivial sequence of searching steps' and lists examples like 'find_symbol, find_referencing_symbols, search_files_for_pattern, read_file, etc.' This clearly defines when to use it versus alternatives, making it highly actionable.

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?

Annotations indicate readOnlyHint=true and destructiveHint=false, which already convey that this is a safe, non-destructive operation. The description adds context about its role in ensuring task adherence before code modifications, which is useful behavioral insight beyond the annotations. However, it does not detail aspects like potential side effects, performance implications, or error handling.

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 front-loaded, with three sentences that directly address purpose and usage without unnecessary details. Each sentence adds value, such as the specific trigger conditions and mandatory usage before code changes, making it well-structured and efficient.

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 (low, with 0 parameters), rich annotations (readOnlyHint, destructiveHint), and the presence of an output schema, the description is complete enough. It explains the tool's role in task adherence and when to use it, which aligns with the structured data. However, it could slightly enhance completeness by mentioning what the output schema returns, though this is not strictly necessary.

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, and schema description coverage is 100%, so there is no need for parameter explanation in the description. The description appropriately does not discuss parameters, which is efficient, but since there are no parameters, a baseline of 4 is applied as it fully compensates for the lack of parameter 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 states the tool's purpose as 'Think about the task at hand and whether you are still on track,' which is a clear action but somewhat vague in scope. It does not specify what resources or data it operates on, and it does not distinguish itself from sibling tools like 'think_about_collected_information' or 'think_about_whether_you_are_done,' making it less specific than ideal.

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 guidelines: 'Especially important if the conversation has been going on for a while and there has been a lot of back and forth' and 'This tool should ALWAYS be called before you insert, replace, or delete code.' This gives clear context for when to use it, though it does not explicitly state when not to use it or compare it to alternatives like other 'think' 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?

Annotations indicate readOnlyHint=true and destructiveHint=false, which the description does not contradict. The description adds context by implying this is a self-assessment or decision-making tool, but it does not disclose additional behavioral traits like what triggers the 'done' state, any side effects, or how it interacts with other tools. With annotations covering safety, the description provides minimal extra value.

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, efficient sentence that directly states the tool's purpose and usage. It is front-loaded with the key information and contains no redundant or extraneous details, making it highly concise and well-structured for quick understanding.

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 0 parameters, annotations covering read-only and non-destructive behavior, and an output schema exists, the description is reasonably complete. It explains when to use the tool, which is the core need. However, it could be more detailed about what 'done' entails or how it integrates with other tools, leaving minor gaps in full 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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not add parameter details, which is appropriate. A baseline of 4 is applied since there are no parameters, and the description does not introduce unnecessary complexity.

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 states the tool's purpose as 'call this tool whenever you feel that you are done with what the user has asked for,' which is a clear action but vague in scope. It specifies a verb ('call') but lacks concrete details about what 'done' means or what resource it operates on, making it somewhat ambiguous compared to more specific sibling tools like 'create_text_file' or 'read_file'.

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 guidance on when to use the tool: 'whenever you feel that you are done with what the user has asked for.' This gives a clear context for invocation. However, it does not mention when not to use it or name alternatives, such as sibling tools like 'think_about_collected_information' or 'think_about_task_adherence,' which might be relevant for related decision-making processes.

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?

Annotations indicate destructiveHint=true and readOnlyHint=false, which the description aligns with by implying a write operation. The description adds valuable context beyond annotations: it specifies the memory is stored in markdown format and should have a meaningful name, which helps the agent understand behavioral expectations. No contradiction with annotations.

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 two concise sentences that front-load the core purpose and key requirements. Every word adds value: the first sentence covers action, content, format, and purpose; the second emphasizes naming quality. 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 a destructive tool with 3 parameters (0% schema coverage) and an output schema, the description adequately covers the purpose and format but lacks parameter details and behavioral nuances like error handling or idempotency. The output schema may help with return values, but the description doesn't fully compensate for the low parameter coverage.

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 mentions 'memory name should be meaningful' (hinting at memory_file_name) and 'information... to a memory' (hinting at content), but doesn't explain max_answer_chars or provide details on parameter formats, constraints, or interactions. This leaves significant 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 ('Write some information') and resource ('to a memory'), specifying the format ('md format') and encoding ('utf-8-encoded'). It distinguishes from siblings like 'read_memory' and 'edit_memory' by focusing on creation, but doesn't explicitly differentiate from 'create_text_file' which might have overlapping functionality.

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 context ('about this project', 'useful for future tasks'), suggesting when to use it for project documentation. However, it lacks explicit guidance on when to choose this over alternatives like 'create_text_file' or 'edit_memory', 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.