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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'analyze' and 'extract detailed information,' leaving unclear whether this is read-only, whether remote downloads occur, or what the response contains.

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 sentence with no redundancy and is appropriately front-loaded with the main action. The phrase 'detailed information' is vague, but the structure itself is concise and free of filler.

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

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

Given no annotations, no output schema, and a large sibling list, the description is too minimal to be complete. It omits output format, behavioral expectations, and distinctions from related extractor tools, leaving the agent to rely on the name and parameters alone.

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?

All six parameters are fully described in the input schema (100% coverage), so the description does not need to restate them. The description adds no extra meaning beyond what the schema already provides, which matches 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 states a clear verb-resource pair: 'analyze a specific jar file and extract detailed information.' However, it does not enumerate what information is extracted or distinguish itself from sibling tools like analyze_jar_structure and extract_class_info.

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

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

The description provides no guidance on when to use this tool versus the 16 related sibling tools. There is no mention of alternatives, exclusions, or typical use cases, so an agent gets no routing cues for selection.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Analyze', implying a read-only operation but never explicitly stating side effects, return format, or any constraints. It also does not mention how 'summarize_large_content' affects behavior, leaving the agent with minimal insight into what happens when invoked.

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, direct sentence with no fluff or redundancy. It front-loads the core action and resource, making it easy to scan. There is no unnecessary detail or repetition, achieving excellent conciseness.

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

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

The tool has moderate complexity with three required coordinates and an optional flag, yet the description provides no information about the output structure, return value, or whether the operation is safe. Since there is no output schema and no annotations, the description should compensate, but it does not. An agent would have to guess what 'structure and metadata' means in terms of the response.

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 explains all four parameters. The description adds no additional parameter context, so the baseline of 3 is appropriate. It neither clarifies nor detracts from the schema's meaning.

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

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

The description clearly states a verb ('Analyze') and a specific resource ('overall structure and metadata of a jar file'), making its purpose evident. However, it does not differentiate from the sibling tool 'analyze_jar', which likely serves a similar or broader role, so it misses the full 5-point bar that requires sibling distinction.

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

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

No guidance is provided on when to use this tool versus alternatives such as 'analyze_jar' or 'extract_class_info'. The description does not mention any conditions or contexts that would make this tool the preferred choice, leaving the agent without routing information.

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

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

No annotations are provided, so the description carries the full burden. It doesn't disclose whether the operation is read-only, what the output format is, or any side effects. The parameter 'compare_api' hints at an API diff but the description itself gives no 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, concise sentence that is front-loaded with the main action. It wastes no words and is 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?

The tool is simple and the parameters are clear, but the description doesn't mention what the comparison result looks like (e.g., diff, report, boolean). Given there is no output schema, this missing information leaves a gap in 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 coverage is 100% and each parameter has a brief description. The descriptions are self-explanatory for group_id, artifact_id, version1, and version2. However, the description adds no extra semantic value beyond the schema, so it stays at the baseline.

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 ('Compare') and the resource ('different versions of the same Maven artifact'), which is specific and unambiguous. It distinguishes the tool from siblings that list versions or analyze structures, though it doesn't explicitly name 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 implies usage: comparing two versions of an artifact. It doesn't explicitly state when not to use it, but the context is clear enough for a simple comparison tool. It could mention that it's for side-by-side version comparison, but the required parameters (version1, version2) make this obvious.

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?

The description discloses the primary side effect (populating the local cache) and mentions the 'latest' version behavior, but it does not elaborate on handling of cached artifacts, force behavior, or potential network dependency. With no annotations, more detail would be expected.

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 no fluff. It front-loads the primary action and purpose, and the 'latest' usage hint is relevant. Every word contributes to 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?

For a simple download operation with a side-effect cache, the description gives sufficient context about the tool's role in the broader workflow (enabling other tools). It lacks explicit return-value info but that is not critical for this type of 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?

Schema coverage is 100% with each parameter already described in the schema. The tool description adds only a redundant note about 'latest' which is already present in the version parameter. It does not provide additional semantic nuance beyond the parameter 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 action (download), the resource (artifact from remote repository), and the target (local analysis cache). It also explains the intent (so every other tool can inspect it), making the tool's purpose unmistakable.

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 does not explicitly contrast this tool with its siblings like search_maven_central or get_remote_versions. It implies this is a prerequisite for local inspection but provides no direct guidance on when to choose this over alternatives.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not mention pagination, defaults like summarize_large_content, output format, or whether the operation is read-only. The description is generic and adds little beyond the tool name.

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

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

The description is a single, front-loaded sentence with no redundant words. It is efficient, but it is also generic and could have included a brief mention of the Maven coordinate requirement without being verbose.

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

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

For a tool with 10 parameters, 3 required fields, no output schema, and no annotations, the description is too minimal. It leaves out context about expected return values, pagination behavior, and when to choose this tool among many overlapping siblings, making it hard for an agent to invoke it confidently.

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

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

Schema description coverage is 100%, so the input schema fully documents all 10 parameters. The description adds no extra meaning about parameters, interactions, or defaults, so the baseline score of 3 applies.

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

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

The description uses a specific verb ('Get') and identifies the resource ('detailed information about Java classes in a jar'). It is clear, but it does not differentiate among siblings like search_classes, analyze_jar_structure, or extract_method_info, so it is not a 5.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention exclusions, prerequisites (such as Maven coordinates), or that it might be better for detailed class inspection while other siblings handle searching or method extraction.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states only that text resources are extracted, without mentioning whether the operation is read-only, whether it downloads the jar, what happens for binary files, how max_bytes affects output, or what the response shape is. This is a significant gap for an extraction tool with no annotation safety signals.

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 with no filler; it front-loads the core action and resource, then enriches with three concrete examples. Every word earns its place, and the structure is appropriately scannable for an 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?

With 7 parameters, no output schema, and no annotations, the description needs to provide more operating context, but it does not explain return values, matching behavior, or the relationship between resource_path and resource_pattern. An agent still lacks key information needed to correctly invoke the tool, such as whether at least one path/pattern is required or what happens when no resources match.

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

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

The input schema already documents all 7 parameters with descriptions, so the schema coverage is 100% and the baseline is 3. The description adds only a general sense of what resource types are relevant; it does not add meaning beyond the schema for parameters like resource_path, resource_pattern, limit, or max_bytes.

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 a specific action (extract) and resource (text resources inside a jar), and gives concrete examples (.proto files, service descriptors, metadata). These examples clearly differentiate it from sibling tools like extract_class_info and extract_source_code, which target class binaries and source code rather than arbitrary text resources.

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 this tool is appropriate by enumerating text-resource types like .proto files and service descriptors, implying its niche among the sibling extraction tools. However, it does not explicitly name alternatives or state when not to use it, so the guidance is clear but not fully explicit.

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

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only says 'Extract specific method information' and does not reveal whether this downloads artifacts, accesses Maven Central, is read-only, handles missing classes, or what output format to expect. This is a significant transparency gap for a tool that likely performs network/resolution work.

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 short sentence with no redundant phrasing, no repetition of schema details, and the key action and resource are front-loaded. Every word serves a purpose.

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

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

With 7 parameters, 4 required Maven coordinates, no output schema, and no annotations, this bare description is not enough. It does not mention that the class is resolved via Maven coordinates, what 'method information' contains, how method_pattern and include_bytecode affect behavior, or what the return shape looks like. The schema helps, but the description leaves too much unstated.

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

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

Schema coverage is 100%, so the input schema already documents all parameters, including optional filters like method_pattern and include_bytecode. The description adds little beyond the word 'specific,' which loosely maps to the filtering parameters but provides no additional semantic detail. Baseline 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 states a specific verb ('Extract'), a resource ('method information'), and the source scope ('a Java class'). This clearly distinguishes it from related class-level or jar-level tools, even though it does not explicitly name the sibling it differs from.

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

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

The description implies use when method-level details are needed from a Java class, but it provides no explicit when-to-use guidance, no exclusions, and no pointers to alternative tools like extract_class_info or analyze_jar_structure. The agent must infer usage context from the tool name and schema.

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

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

With no annotations provided, the description carries the behavioral disclosure burden. It does disclose a key behavior: it prefers the source jar and falls back to decompilation. However, it omits other important behaviors such as summarization of large content, line limiting, and whether network/download operations are involved. These gaps matter given the absence of annotations and an output schema.

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 sentence with no filler; every word contributes to the core behavior. It is front-loaded with the action and resource. It is appropriately sized for a high-level summary, though it leaves behavioral detail to other dimensions.

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

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

This tool has 7 parameters, including flags like max_lines and summarize_large_content, yet the description explains none of their interaction. There is no output schema and no annotations, so the agent has no indication of return format, error conditions, decompilation limits, or network behavior. For an operation of this complexity, the description is too sparse.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds minor context by explaining the 'source jar vs decompile' tradeoff, which loosely aligns with prefer_sources, but it does not meaningfully enrich the meaning of the Maven coordinates, class_name, max_lines, or summarize_large_content beyond what the schema already states.

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

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

The description uses a specific action verb ('Extract') and a concrete resource ('source code'), and clarifies the two paths: extracting from a source jar or decompiling bytecode. This distinguishes it from siblings like extract_class_info and extract_method_info, which focus on metadata rather than source code, though it does not name those alternatives explicitly.

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

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

The description implies this tool is for obtaining source code when a Maven artifact is identified, and it conveys a fallback path (decompile bytecode if source jar is unavailable). However, it provides no explicit guidance on when to choose this over siblings like extract_class_info or extract_jar_resource, nor any 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?

No annotations are provided, so the description carries full behavioral burden. It only states the query intent and does not mention pagination behavior, result format, whether version is optional, or how dependent artifacts are scoped (direct vs transitive).

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, focused sentence with no filler. It front-loads the core purpose, but it is minimal enough that it lacks auxiliary context without becoming unnecessarily long.

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

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

With six parameters, no output schema, and no annotations, a one-sentence description is insufficient. It omits how pagination works, what the response contains, and how this tool relates to sibling dependency tools.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-level meaning; importantly, it does not clarify the redundant pagination parameters page, limit, and items_per_page, but the schema already documents each parameter.

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 a clear verb and resource: 'Find artifacts that depend on a specific artifact.' It communicates the reverse-dependency concept, though it does not explicitly distinguish itself from siblings like get_dependencies or get_dependency_tree.

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

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

The description gives no guidance on when to use this tool versus alternatives. With siblings like get_dependencies and get_dependency_tree, the agent must infer the opposite-direction semantics from the tool name and description rather than being told.

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

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

No annotations are present, so the description carries the full burden of explaining behavior. It states that the tool 'finds usage examples in test jars,' but it does not disclose whether this is a read-only operation, what the output looks like, how pagination behaves, or what happens when no examples are found. These behavioral gaps are notable for a tool with no output schema and no 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 a single, concise sentence that front-loads the core purpose. There is no redundant or filler content, and it is appropriately sized for what it communicates.

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 six parameters, no annotations, and no output schema, the description is too minimal to be fully actionable. It does not explain return values, pagination semantics, or how this tool fits among the sixteen listed siblings. An agent would likely need additional inference or experimentation to invoke it correctly for non-default cases.

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 each parameter clearly. The description adds little beyond mapping 'classes/methods' to class_name and method_name, and 'test jars' to search_tests. It does not clarify the relationship between page, limit, and items_per_page or their effective behavior.

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 a clear verb and resource: 'Find usage examples of classes/methods in test jars.' It is specific enough to distinguish this tool from siblings like extract_class_info or extract_method_info, which focus on structural details rather than usage examples. The scope 'test jars' further narrows the 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?

There is no guidance about when to use this tool versus the many sibling tools. The description does not mention alternatives, exclusions, or conditions that would help an agent choose between find_usage_examples and similar search/analysis tools. The only implied context is that test jars are the search target, but no explicit usage guidance is provided.

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

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

No annotations are provided, and the description does not disclose any behavioral aspects such as whether the operation is read-only, side effects, pagination limits, or error behavior. The full burden falls on the description, which is minimal and lacks any transparency about what happens when the tool is invoked.

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

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

The description is extremely concise and to the point, consisting of a single clear sentence. There is no redundant information or filler, and it effectively communicates the core function without unnecessary verbosity.

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

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

The description lacks context about the output format, return type, or any additional information an agent might need to interpret the results. Since there is no output schema and the tool appears simple, some explanation of what 'dependencies' entails (e.g., list of objects, fields) would improve completeness. Currently, the agent is left guessing about the response structure.

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

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

The schema provides full descriptions for all six parameters with 100% coverage, so the baseline is met. The tool description itself does not add any extra semantic meaning beyond what the schema already conveys, but no parameter is left undocumented.

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 ('Get'), the resource ('Maven dependencies'), and the source ('POM files'). It is specific and unambiguous, but it does not explicitly differentiate from the sibling tool 'get_dependency_tree', which could also return dependency information. Despite this, the purpose is clear.

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 over alternatives. It does not mention scenarios where this tool is preferred, nor does it contrast with siblings like 'get_dependency_tree' or 'find_dependents'. No usage conditions or prerequisites are stated.

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?

There are no annotations, so the description must carry the behavioral burden. It calls the tree 'complete' but the schema defaults max_depth to 3 and summarize_large_content to true, meaning results may be truncated or summarized. This tension is not addressed.

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

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

The description is a single front-loaded sentence with no filler. It is appropriately terse, though its brevity is achieved partly by omitting useful behavioral and comparative context.

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

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

With no output schema, no annotations, and a close sibling get_dependencies, this description is underspecified. It does not explain return shape, the effect of max_depth, summarization behavior, or when to choose this tool over alternatives.

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 parameters are already documented meaningfully. The description adds almost no parameter-level detail beyond naming the artifact; it does not explain how max_depth affects the 'complete' claim or what summarize_large_content does.

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?

States a clear verb and resource: 'Get complete dependency tree for an artifact'. The Maven coordinates are visible in the schema. It does not explicitly contrast with sibling get_dependencies, but 'tree' implies recursive structure versus a flat dependency list.

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

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

No when-to-use guidance is provided, and no alternative tools are mentioned. The agent is left to infer when this is preferable to get_dependencies or list_artifacts. The word 'complete' implies a full traversal, but that is not made explicit.

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

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

With no annotations, the description carries the behavioral transparency burden. It usefully discloses the remote scope and the inclusion of non-local versions. However, it claims to list 'all' versions while the schema includes a 'limit' parameter, creating a slight ambiguity about whether results are truly complete or capped.

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?

A single sentence that is immediately informative. The main action and key qualifier are front-loaded, with no filler or redundant detail. Every word contributes to 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?

For a simple list operation with fully documented parameters, this description is nearly complete. It conveys the remote-versus-local distinction, which is the main contextual nuance. The missing return-format details are less critical given the tool's straightforward name and behavior.

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 fully documents the three parameters. The description adds no additional parameter-level meaning, but the baseline of 3 is appropriate given the schema handles the explanation.

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 a specific verb ('List'), a resource ('versions of an artifact published on the remote repository'), and a key differentiator ('including versions that are not installed locally'). This distinguishes it from sibling tools like get_version_info and list_artifacts.

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

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

The description provides clear context for when to use the tool: when you need versions available on the remote repository, including those not installed locally. However, it does not explicitly name alternatives or state when not to use it, leaving some routing to inference.

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

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

With no annotations, the description must fully disclose behavioral traits. It only states a high-level read operation and the optional remote inclusion, but does not mention that by default only installed versions are returned, that results are paginated, or any repository-related behavior. The schema's include_remote description partially fills in default behavior, but the description itself is thin for a tool with no annotation safety profile.

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, front-loading the main action and resource. Every word contributes meaning, and it avoids redundant restating of the tool name or parameter 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?

The presence of six parameters, including two pagination-related parameters, and the absence of an output schema mean the description should provide more context about return values, pagination defaults, and the relationship between local and remote versions. It currently leaves an agent uncertain about what will be returned and how pagination parameters interact.

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 already well-documented. The description adds minimal extra meaning beyond the schema—mainly reinforcing the 'all versions' and 'optional remote' concepts already present in include_remote. It does not clarify the relationship between 'limit' and 'items_per_page', but the schema baseline of 3 applies.

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

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

The description uses a specific verb ('Get') and resource ('all available versions of an artifact'), and clarifies an optional scope ('including versions published remotely'). This clearly distinguishes it from siblings like list_artifacts (lists artifacts) and get_remote_versions (likely remote-only), while conveying the full retrieval behavior.

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 intended use is implied: use this tool when you need versions of a specific Maven artifact. However, the description gives no explicit guidance on when to prefer an alternative such as get_remote_versions or compare_versions, and does not state when remote inclusion would or would not be appropriate.

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

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

With no annotations provided, the description carries the full burden. It states the operation is a listing operation and clarifies the local scope and filtering capability. However, it does not disclose pagination behavior, output shape, or the fact that 'all' artifacts are likely returned in pages based on the limit/items_per_page parameters.

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

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

The description is a single, front-loaded sentence with no filler, making it easy to scan. It sacrifices some useful context (pagination, usage guidance) for brevity, but the wording itself is 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?

The description is adequate for a basic list-and-filter operation, especially because all parameters are described in the schema. Yet it has clear gaps: no output schema, no mention of pagination semantics, and no guidance on how this tool relates to the many sibling tools.

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

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

Schema description coverage is 100%, so the parameters themselves are already fully documented. The description adds only the generic notion of 'optional filtering', which does not meaningfully clarify the ambiguous relationship between 'limit' and 'items_per_page'.

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

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

The description uses a specific verb ('List') and identifies the exact resource ('Maven artifacts in the local repository') with a clear qualifier ('optional filtering'). This distinguishes it from sibling tools focused on remote search, analysis, extraction, and dependency resolution.

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 phrase 'in the local repository' provides clear context that this tool is for local artifact enumeration, in contrast to tools like search_maven_central or get_remote_versions. However, it does not explicitly mention when to prefer alternatives or describe exclusions.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It implies a read-only search operation but does not describe return values, output structure, potential breadth of the scan, or any side effects. The phrase 'across all jars' hints at a potentially broad operation, but the description does not elaborate.

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 clear sentence with no filler or repetition. It is concise and front-loaded, though slightly too sparse to fully support a six-parameter tool with no additional context.

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

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

Given six optional parameters, no output schema, and no annotations, the description is incomplete for safe tool selection and invocation. It does not clarify the relationship between 'page'/'limit' and 'items_per_page', explain the result format, or distinguish when this tool should be preferred over related siblings.

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

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

Schema description coverage is 100%, so the schema already documents each parameter. The tool description adds no additional semantic value beyond what the schema provides, which matches the 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 a specific action ('Search') and resource ('Java classes across all jars in the repository'), which is informative and distinct from most sibling tools like analyze_jar_structure or extract_class_info. However, it does not explicitly name or contrast any sibling, so full differentiation is left to inference.

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

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

There is no guidance about when to use this tool versus alternatives such as search_maven_central or extract_class_info. The description states the scope but provides no exclusions, prerequisites, or selection criteria.

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

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

No annotations are present, so the description carries the full behavioral burden. It does disclose meaningful context: the operation is a remote online search against the configured mirror and can return artifacts not installed locally. However, it never explicitly states a read-only safety profile and does not address failure modes such as network unavailability or mirror misconfiguration.

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

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

Two sentences with no waste: the first states the action and scope, the second the two primary use cases. The core purpose is front-loaded and every clause earns its place.

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

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

The 9 parameters are fully documented in the schema and the description anchors the two main use cases well. But with no annotations and no output schema, the result shape and the read-only safety profile are left implicit. Adequate for a conceptually simple search tool, yet not fully complete.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds modest selection guidance by mapping use cases to parameter groups: 'discover coordinates' implies query/group_id/artifact_id, while 'find which published artifact contains a class' implies class_name/fully_qualified_class. It doesn't explain filter combination or pagination semantics beyond what the schema already documents.

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

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

The description uses a specific verb ('Search') with a clear resource ('Maven Central or the configured mirror') and defines the scope ('online', 'including ones not installed locally'). It names two concrete use cases — discovering coordinates and finding which published artifact contains a class — which separates it from local tools like list_artifacts and search_classes in the sibling set.

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?

'Use this to discover coordinates or find which published artifact contains a class' gives explicit when-to-use scenarios, and 'including ones not installed locally' signals when the remote search is the right choice over local alternatives. It stops short of naming siblings or stating when-not-to-use, so it's clear context without explicit exclusions.

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