laravel13-livewire4.2.1-mcp

Server Quality Checklist

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Latest release: v3.1.0
Disambiguation2/5
Multiple tools have overlapping purposes: generate_policy and generate_full_policy are nearly identical, as are generate_middleware and generate_custom_middleware. security_audit, deep_scan_bugs, and scan_project_bugs all perform code scanning, making it unclear which to use.
Naming Consistency2/5
Naming conventions are inconsistent. Most tools use verb_noun (generate_*, convert_*), but several use prefix_noun_verb (gh_repo_create, git_commit), and a few are just verbs (memorize) or mix patterns (deep_scan_bugs). This makes it hard to predict tool names.
Tool Count1/5
With 75 tools, the server is massively over-scoped for a code generation assistant. Many tools are redundant (e.g., multiple bug scanners, multiple policy generators), and the count far exceeds the 15-20 tool range where coherence is typically manageable.
Completeness3/5
The tool set covers a broad swath of Laravel/Livewire development including code generation, git/GitHub integration, bug tracking, and project planning. However, obvious gaps exist: no migration or seeder generation, no tool to run tests or artisan commands, and no explicit delete operations for generated resources.
Average 3.1/5 across 73 of 75 tools scored. Lowest: 2.3/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It does not mention that this is a destructive/irreversible action, whether it requires special permissions, or what happens on merge failure/conflicts.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief, but it adds no information beyond the tool name. It is under-specified rather than concise, failing to provide context that earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with two parameters and no output schema, the description lacks critical details about return values, error handling, and side effects. It is not sufficient for an agent to use safely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the parameters. It fails to clarify that 'number' refers to the PR number or what the 'method' options (merge/squash/rebase) mean in practice.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (merge) and the resource (Pull Request). It differentiates from sibling tools like gh_pr_create and git_branch_merge by specifying the GitHub PR merge operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 or how it differs from alternatives like git_branch_merge. The description simply restates the function, offering no context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure. It only says 'for future reference,' which implies persistence but does not explain store/overwrite behavior, whether endpoints are unique by path/method, or how the memory is later retrieved.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no fluff and is front-loaded with the action. However, it is underspecified for a six-parameter tool, making it minimal rather than effectively concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has six parameters, no output schema, and no annotations, yet the description gives only a high-level intent. It omits invocation details, behavior, and expected return value, so the description is not complete enough for correct use without further inference.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description names no parameters. The required fields (path, method, controller, purpose) and optional fields (params, response) are completely unexplained, leaving the agent without semantic guidance beyond raw property names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb and resource: 'Memorize an API endpoint' for future reference. This clearly differentiates it from the broader sibling 'memorize' by specifying the object being memorized, though it does not explicitly contrast alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives like 'memorize' or 'recall_context'. It lacks exclusions or context for when this endpoint-specific memory is preferred over generic memory tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. While 'recall' implies read-only, it doesn't mention whether results are scoped to the current project, what happens when no matches are found, or if any session-specific memory is involved. This is minimal behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short, front-loaded sentence, which is concise and free of waste. However, it is so brief that it lacks structural components like usage notes or examples, making it only acceptable in this dimension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one parameter and no output schema, the description should at least mention what the return value looks like or typical usage scenarios. It does neither, leaving a basic retrieval tool under-specified and incomplete for an agent to invoke confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not explain the 'query' parameter beyond its string type. The phrase 'memorized endpoints and decisions' does not clarify whether the query is a search term, exact identifier, or natural language, leaving the agent without necessary semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'recall' and identifies the resource as 'memorized endpoints and decisions,' clearly indicating a retrieval operation. This distinguishes it from sibling tools like memorize_endpoint or generate_* tools, though it doesn't specify the search or filter behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 memorize_endpoint, or when not to use it. It only states what it does, omitting context, exclusions, or alternative references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure, but it only restates the operation. It does not mention side effects, permission requirements, or consequences of creating a PR, providing no value beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, but it is under-specified. It states the main purpose but omits valuable context, so it is concise at the expense of usefulness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a 5-parameter mutation tool with no annotations and no output schema. The description is far too minimal to cover required context, such as branch requirements, behavior for missing fields, or what the tool returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explanations for the five parameters (base, body, head, draft, title). The parameter names are self-explanatory, but the description itself adds no guidance beyond what the schema already shows.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Create a Pull Request' uses a specific verb and resource. It clearly distinguishes from sibling tools like gh_pr_list and gh_pr_merge, which have different actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives like git_commit, git_push, or gh_pr_merge. No prerequisites, exclusions, or context are mentioned, so the agent gets no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full transparency burden. It says 'production-ready' with validation/security, but does not disclose concrete behavior: file creation/overwrite side effects, prerequisites, expected output, or error handling. 'Production-ready' is a quality claim, not a behavioral description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the action verb 'Generate,' and contains no filler. It is appropriately short, but the brevity sacrifices explanatory detail; it is concise without being informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 12 parameters, no output schema, and no annotations, the description is far too sparse. It does not clarify the meaning of component 'type' options, the purpose of fields/layout/hasEdit/hasDelete options, or what 'production-ready' entails in generated code. The schema helps but leaves ambiguity, especially for nested field objects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 8% (only 'name' has a description). The description mentions validation and Laravel attributes but does not explain any of the 12 parameters, their relationships, or how fields/rules are structured. It fails to compensate for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it 'Generate[s] a production-ready Livewire v4.2+ component' with specific features like 'Laravel 13 attributes, validation, security, DRY patterns.' The verb and resource are specific, but it does not distinguish from sibling generators like generate_form_component or generate_crud_component, making scope ambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus the many similar siblings (e.g., generate_form_component, generate_data_table, generate_modal_component). There are no exclusions, prerequisites, or alternative recommendations; the intended use case is only vaguely implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden, but it only states 'Authenticate with GitHub CLI.' It does not disclose side effects, such as opening a web browser, storing credentials, or requiring interactive input, nor does it describe the output or potential errors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no filler words. However, it is so short that it sacrifices valuable context, yet for what it includes, it is well-structured and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This tool has side effects (authentication) and is likely a prerequisite for many sibling GitHub tools, but the description provides no context about when to use it, what happens after authentication, or how it integrates with other tools. The output is not described either.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%. The description does not explain the 'method' parameter or its enum values ('web' vs 'token'), leaving the agent to guess the implications of each choice. No additional meaning is provided beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (authenticate) and the resource (GitHub CLI). It is distinct from the sibling gh_auth_status, which checks authentication status, though it does not explicitly differentiate itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives, such as checking gh_auth_status first or using token-based vs web-based authentication. There is no mention of prerequisites or post-authentication steps.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure, but it only states 'Create a GitHub Issue.' No details about authentication, repo context, side effects, or return values.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no redundant words. It is front-loaded and appropriately short, though it lacks any structural breakdown of parameters or usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters and no annotations or output schema, the description is too minimal. It lacks context about repository selection, authentication requirements, or what happens after creation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema defines title, body, and labels, but the description adds no parameter semantics. With 0% schema description coverage, the description must compensate, and it fails to do so.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Create' and the resource 'GitHub Issue', which is specific and distinguishes it from sibling tools like gh_issue_list or gh_pr_create.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided—no indication of when to use this tool over alternatives, prerequisites, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'List GitHub Issues' and does not reveal whether it requires authentication, operates on the current repository, returns all issues by default, or any other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at just three words, but it is under-specified. It lacks crucial details like the existence of the 'state' parameter, making the conciseness insufficient rather than appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has one parameter, no output schema, and no annotations, so the description is expected to provide context. It fails to mention the filtering option, repository context, or return format, leaving significant gaps for such a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema includes a 'state' parameter with enum values and a default, but the description does not mention this filtering capability at all. Schema description coverage is 0%, so the description fails to compensate and adds no meaning beyond the structured schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List GitHub Issues.' clearly states a specific verb ('List') and resource ('GitHub Issues'), making the tool's purpose obvious. It does not explicitly distinguish it from sibling tools like gh_pr_list, but the resource itself is distinct enough to avoid confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 vs alternatives. The description simply states what it does without mentioning any context or exclusions, leaving the agent to infer usage from the name and siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It states the destructive action 'Delete' which implies irriversibility, but it does not disclose the existence of a 'force' parameter, the behavior when deletion fails (e.g., unmerged branch), or any side effects. The description is minimal but not misleading; however, it omits important destructive nuances.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no waste, which is concise. However, it is under-specified: for a delete tool with a force flag and safety implications, one sentence is too sparse to be considered appropriately sized. It is efficient but incomplete, balancing conciseness against lost information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, plus a destructive operation with a force flag, the description is far from complete. It does not mention the 'force' parameter, typical failure cases, or any behavior beyond the core action. The tool's context among git siblings is not leveraged to provide additional guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain either parameter. 'name' is inferred as the branch name, but 'force' is completely undefined—its purpose (force-deleting unmerged branches) is not stated. The description adds zero meaning beyond the schema's field names, which are not self-sufficient for a destructive operation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description is a clear imperative verb+resource: 'Delete a git branch.' It precisely identifies the operation (delete) and the target (git branch), distinguishing it from sibling tools like git_branch_create, git_branch_list, and git_branch_merge. No ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 prerequisites (e.g., cannot delete the current branch), safety conditions (e.g., merged state), or when to use the 'force' option. A tool like git_branch_merge or git_branch_create is implicitly different, but no explicit comparison or usage context is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It omits whether the operation is destructive, irreversible, creates a backup, or requires specific permissions. The verb 'restore' implies mutation but no safety details are given.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no redundancy, but it is too terse to be fully helpful. It gets a 4 for efficiency, though it sacrifices necessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a potentially destructive action, the description is significantly under-specified. It lacks information about side effects, rollback behavior, and input format, even though the tool's simple schema leaves room for such clarification.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not explain the 'version' parameter. It leaves unclear what format the version string should take (e.g., ID, timestamp, number) or how to obtain valid values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Restore project to a previous version' clearly states the tool's action (restore) and its target (project to a previous version), distinguishing it from siblings like create_version and list_versions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It does not mention prerequisites, safe usage context, or suggest list_versions to pick a version first.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only says 'scan' without stating whether the tool modifies files, requires permissions, or what happens to identified bugs. This significant gap makes the tool's behavior unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. It is appropriately concise for the simple purpose, though it could be considered under-specified for the required behavioral context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (one optional param, no output schema), the description still fails to explain return values or side effects. It also does not clarify how it relates to deep_scan_bugs or fix_bugs, leaving the contextual picture incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention the 'directory' parameter or its default value. The agent is left with only the schema definition, which lacks semantic explanation about how the parameter controls the scan.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool scans the entire project directory for common bugs in all files, giving a specific verb and resource. However, it does not distinguish this from sibling tools like deep_scan_bugs or security_audit, so it lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives such as deep_scan_bugs or security_audit. No exclusions or alternative suggestions are provided, leaving the agent without clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for disclosing side effects, permissions, or state changes. It only states the action without any behavioral detail—no mention of whether it modifies files, requires authentication, or what the outcome is.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence with no wasted words. It is front-loaded and efficient, but lacks substance in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and minimal schema information, the description should provide more context. It does not explain when to use it, what 'last interrupted session' refers to, or how it interacts with other tools, making it incomplete for an agent selecting the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The schema provides no additional meaning, and the description does not need to explain parameter semantics. It appropriately remains silent on parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Continue from last interrupted session' gives a clear verb and resource (project/session), but it is vague about what 'continue' entails. It goes slightly beyond the name by specifying 'last interrupted session', but does not clarify what state is restored or what operations are performed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 get_project_status or git_sync. There is no mention of prerequisites, typical use cases, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states the conversion action without revealing side effects (e.g., whether it creates files, fetches a URL, or modifies existing code). This is a significant gap for a mutation-like operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, but it is under-specified. For a tool with three parameters and no other documentation, this brevity is insufficient and reflects underspecification rather than effective conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, output schema, and parameter descriptions, this one-sentence description is completely inadequate. It fails to explain the conversion process, expected input format, output location, or any side effects, leaving the agent without the information needed to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 3 parameters with 0% description coverage, and the description provides no explanation for stitchUrl, componentName, or layout. The agent receives zero guidance on how to populate these fields, making correct invocation highly uncertain.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'convert' and names both source ('Google Stitch design') and target ('Livewire component'), clearly distinguishing it from sibling conversion tools like convert_figma_to_livewire and convert_html_to_livewire. The resource and outcome are unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for Google Stitch designs but does not explicitly address when to choose it over alternatives like convert_figma_to_livewire, nor does it mention exclusions or prerequisites. It provides minimal contextual guidance beyond the obvious source type.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It mentions only that it generates a file but does not disclose whether it overwrites existing files, where the file is created, or any other side effects. This lacks transparency for a file-generation action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence and highly concise. However, the parenthetical list introduces ambiguity (e.g., 'error' vs the error codes), preventing a perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has two parameters and no output schema, the description is too sparse. It fails to explain the 'name' parameter, the relationship between name and layoutType, or the actual output file behavior, making it incomplete for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 lists some layoutType values (base, app, guest, etc.) but omits error403, error404, error500, and includes a vague 'error' not in the enum. It also provides no explanation for the 'name' parameter, leaving its purpose unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a Laravel 13 Blade layout file, with a specific verb and resource. It lists several layout types, which helps distinguish it from other generate tools, but it does not explicitly contrast with siblings or note the missing error variants.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool or when to prefer an alternative. The description offers no context about prerequisites, alternatives, or scenarios where generating a layout is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, but it only restates the core purpose. It does not disclose whether existing files are overwritten, what 'all CRUD' includes, naming conventions, or any side effects, which is a significant gap for a generation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that is front-loaded with the core 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given four parameters, no annotations, and no output schema, the description is too minimal to be complete. It does not indicate required inputs, behavior around file generation, or what the resulting class contains beyond 'all CRUD'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 25% (only 'model' is described). The description does not explain 'modelClass', 'userClass', or 'extraMethods', so the agent must guess their meaning. The tool description adds no value to the sparse parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: generating a Laravel policy class with all CRUD authorization methods. It uses a specific verb and resource, but does not differentiate from the similar sibling tool 'generate_full_policy', preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like 'generate_full_policy' or other generation tools. There is no mention of scenarios, prerequisites, or exclusions, leaving the agent without clear selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only describes the output type without mentioning side effects, prerequisites (e.g., existing Livewire project), or whether it creates/overwrites files. The term 'generate' implies file creation but nothing is explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence with no fluff; it's as concise as possible. However, the conciseness comes at the expense of necessary information, affecting other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 6 parameters and no output schema, yet the description omits any details about how to configure the widget, the meaning of widgetType enums, or how metrics are structured. This is insufficient for an AI agent to select appropriate arguments.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description needed to compensate. It only vaguely references 'stats' and 'real-time updates' which hint at metrics and refreshInterval, but it doesn't explain any parameter semantics, shapes, or how to choose widgetType.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a Livewire dashboard chart/widget component with stats, charts, and real-time updates, which distinguishes it from general component generators like generate_livewire_component. The verb 'generate' and the specific resource are clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 siblings such as generate_livewire_component, generate_crud_component, or generate_data_table. No alternative tools are mentioned, and no context is given for when a chart widget is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure. It states only the high-level conversion action, but does not reveal side effects (e.g., file creation, overwrites), authentication requirements (e.g., Figma token), or any limitations. The agent has little insight into what occurs beyond the literal meaning of 'convert.'
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with zero fluff and immediately states the core action. While it is brief, it is efficiently worded and front-loaded, though it lacks any structural elements like prerequisites or parameter highlights.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, no output schema, no annotations), the description is severely incomplete. It does not explain what the conversion produces, whether it modifies files, how to handle authentication, or what the expected outcome is. The absence of behavioral and parameter details makes it inadequate for an agent to use reliably.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 25%, so the description must compensate by explaining parameters. It does not mention figmaUrl, figmaToken, componentName, or layout, leaving the agent with no guidance on how to supply the necessary inputs. The schema itself only documents the optional token, so most parameters remain completely unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert Figma design to Livewire component' uses a specific verb (Convert) and identifies both the input (Figma design) and output (Livewire component), clearly distinguishing it from sibling tools like convert_html_to_livewire or convert_image_to_livewire. The purpose is unambiguous and immediately actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: when you have a Figma design and want a Livewire component. However, it does not explicitly state when to use this tool over alternatives, nor does it mention prerequisites like having a Figma URL or token. No exclusions or alternative tool references are provided, leaving selection partly inferred from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full burden. It mentions that the output includes wire directives, validation, and security, but it does not disclose side effects such as whether files are created, modified, or whether any destructive actions occur. The 'v4.2+' version constraint is the only additional behavioral detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The one-sentence description is front-loaded and free of redundant content. The word 'proper' is slightly vague, but the sentence is otherwise efficient. It could arguably be longer given the tool's complexity, but as a standalone purpose statement it is concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 6 parameters, no annotations, no output schema, and low schema coverage, the description is insufficient for an agent to fully understand the tool's behavior, parameters, or expected outputs. The description only states the high-level purpose and mentions validation/security, but lacks critical operational details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 17% (only 'html' is described), and the description does not elaborate on any of the six parameters. It does not explain the role of layout, hasForm, hasList, hasModal, or componentName, leaving the agent to guess their semantics from names and defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts static HTML to a Livewire v4.2+ component, with a specific verb and resource. It distinguishes itself from sibling conversion tools like convert_image_to_livewire and convert_figma_to_livewire by specifying the input type (static HTML).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when the user has static HTML to convert, but it does not explicitly mention when to use this tool over alternatives such as generate_livewire_component or the other convert_* tools. There are no exclusions or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It describes what the tool analyzes but does not state whether it is read-only, whether it modifies files, how findings are reported, or if there are any side effects. The read-only nature of a scanner is implied but never explicitly stated, leaving the agent to infer safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the tool's purpose and key coverage areas. It is appropriately sized, though the trailing 'and more' adds minor unnecessary vagueness without earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a moderately complex interface with three parameters, no annotations, and no output schema. The bare-bones description does not explain return values, pagination of results, or how scanMode affects output, leaving the agent to infer behavior from the schema and enums. This is inadequate for a tool with no structured annotations to lean on.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With only 33% schema description coverage, the description adds some semantic value by listing categories (tables, lists, security, types) that map to scanMode enum values, giving meaning to that parameter. However, it does not explain the fileType parameter's role or how scanMode interacts with fileType, leaving gaps for two of three parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a comprehensive bug scanner for Livewire/Laravel and enumerates specific coverage areas (tables, lists, pagination, validation, security, types), which helps distinguish it from sibling tools like security_audit (which focuses only on security) and scan_project_bugs (which implies project-level scanning). However, it doesn't explicitly state that it scans a provided code snippet versus a whole project, creating slight ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives. It lists capabilities but does not state conditions for selection, exclusions, or mention that security_audit or scan_project_bugs might be better suited for specific scenarios. The 'and more' is vague and doesn't help an agent decide between this and other scanning/fixing tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 what the generated middleware contains but does not explain side effects such as file creation location, whether existing files are overwritten, artisan command execution, or validation behavior. The phrase 'security checks' is vague about what actually happens.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with all five words earning their place: verb, framework version, resource type, and feature highlights. No filler, no repetition of schema information, highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 5 parameters, no output schema, and no annotations, the description is too thin. It conveys the tool's purpose but fails to explain operational context: what the generated middleware looks like, where it is placed, what 'custom logic' execution means, or how to choose between this and the sibling generate_middleware. The 80% schema coverage partially compensates for invocation, but not for behavioral and selection context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 80%, so the schema already documents rateLimit, redirectTo, customLogic, and middlewareName with meaningful descriptions. The description adds marginal context by mapping its feature list ('auth, rate limiting, CSRF') to the 'type' enum values, but it does not add per-parameter syntax or format details beyond what the schema provides, which is consistent with the baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') and a specific resource ('Laravel 13 middleware') and lists key capabilities (auth, rate limiting, CSRF, security checks), making the core purpose clear. However, it does not differentiate from the sibling tool 'generate_middleware', which appears to be a close alternative.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like generate_middleware, generate_policy, or security_audit. No when/when-not conditions or prerequisite context are given, leaving the agent to infer selection from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for disclosing behavior. It only lists features (CRUD, Gates, injection) without mentioning side effects like file creation, overwriting existing files, or required permissions. The tool's actual operational impact is undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence without fluff. It effectively communicates the core purpose in an efficient manner, though it omits beneficial details that could fit without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 4 parameters and a nested 'conditions' object with no output schema, the description provides minimal context. It lacks usage guidelines, side-effect disclosure, and parameter semantics, making it insufficient for an agent to fully understand the tool's scope and behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 50% (only modelClass and usePolicyInjection have descriptions). The description does not clarify the 'methods' array, 'conditions' nested objects, or how parameters map to the output. 'conditions' is particularly opaque and deserves explanation, which is absent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 ('Generate') and resource ('Laravel authorization policy'). It distinguishes itself from the sibling 'generate_policy' by emphasizing 'comprehensive', 'all CRUD methods', 'Gates', and 'policy injection', which differentiates it as the full-featured version.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like 'generate_policy'. The description does not mention scenarios where the basic policy generator would suffice or any exclusions, leaving the agent without decision-making context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden of disclosing behavioral traits. It does not explicitly state that this is a read-only operation, nor does it mention any side effects, response format, or behavior when no fixed bugs exist. The verb 'Get' implies read-only, but this is not disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, succinct sentence that front-loads the core purpose without any redundant information. It is appropriately concise for a simple listing tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple, the description lacks essential context for an agent to invoke it correctly. It does not explain the filter parameter, when to choose this over similar tools, or what to expect in the output. The absence of this information makes it incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention the 'filter' parameter at all. The agent receives no semantic guidance about how severity levels (critical, high, etc.) relate to the list, leaving the parameter's purpose unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a list of fixed bugs, using a specific verb and resource. It distinguishes itself from sibling tools like 'get_open_bugs' by explicitly mentioning 'fixed' rather than 'open'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'get_open_bugs' or 'scan_project_bugs'. The description does not mention exclusions, alternatives, or any conditional context for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. 'List Pull Requests' only indicates a read operation but doesn't mention authentication requirements, pagination, repository scope, or what data is returned. This is a minimal statement with no added context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, direct sentence with no filler. Every word contributes to the meaning, making it extremely concise and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one optional parameter, no output schema), but the description is sparse. It doesn't provide context about the repository or how the list is scoped. Given the low complexity, a minimal description is acceptable, but it leaves room for more helpful details like 'lists PRs for the current GitHub repository'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the description does not mention the 'state' parameter or its values. Although the schema defines the enum and default, the description should compensate for the lack of textual documentation but fails to do so, leaving the agent to rely solely on the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List Pull Requests' uses a specific verb and resource, clearly indicating the tool's function. It distinguishes from sibling tools like gh_pr_create and gh_pr_merge, which write/modify, though it doesn't mention any unique filtering or scope like repository context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. It doesn't mention that it's for read-only listing, nor does it distinguish from other listing tools like gh_issue_list or git_branch_list. The agent is left to infer usage from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only says 'toggle' without explaining side effects, persistence, or current state visibility, offering no additional transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no superfluous words. It is front-loaded and every word earns its place, effectively communicating the core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple toggle tool with no output schema, the description lacks complete context. It does not clarify the effect of toggling (on/off state), how it affects task completion, or how the state can be observed, leaving notable gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema is empty with 100% coverage. Baseline for 0-parameter tools is 4, and there is nothing about parameters needing elucidation; the description adds no param info, which is acceptable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's action (toggle) and resource (auto-sync), with context (on task completion). It is specific enough to distinguish from sibling git tools like git_sync or git_full_setup, though it does not elaborate on what auto-sync entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives, nor any prerequisites or exclusions. The description merely states the action, leaving the agent to infer appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description must carry the full burden of behavioral disclosure. 'Merge a branch into current' describes the action but does not mention potential side effects such as creating a merge commit, modifying the working tree, or failing due to conflicts. It adds minimal value 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that is front-loaded and easy to read. While it is terse, it contains no filler and is appropriately sized for a simple tool, though it could include more context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a mutation tool with no annotations, no output schema, and an undocumented parameter, the description is notably incomplete. It does not explain the result of the operation, error behavior, or any side effects, making it insufficient for an agent to fully anticipate outcomes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and only one parameter ('branch'), the description does not explicitly explain the parameter's meaning or format. The phrase 'a branch' hints that 'branch' is the source branch, but it lacks explicit definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Merge a branch into current' clearly identifies the action (merging), the object (a branch), and the target (the current branch). It distinguishes this tool from siblings like git_branch_create, git_branch_delete, and gh_pr_merge.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It does not mention prerequisites (e.g., clean working tree), when not to use it, or compare with related operations like git_pull or gh_pr_merge.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits, but it only says 'fix bugs automatically', which implies code modification without explaining whether changes are destructive, whether they require user review, or what the output will be. The absence of any safety or scope details is a significant gap for a potentially mutating operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that immediately communicates the tool's core function. It contains no redundant words or filler, making it maximally concise for its content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that performs automatic code modification with multiple input parameters and no output schema, this description is severely underspecified. It lacks details on input semantics, expected behavior, error cases, or what the agent should do with the result. The complexity of the operation demands far more context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention any of the three parameters: code, fileType, or bugDescription. It fails to explain the meaning of fileType's enum values (php, blade, component, model) or that bugDescription is optional. The description provides no value beyond what is trivially inferable from the schema names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs 'Analyze and fix' with a clear resource ('bugs in Livewire/Laravel code'), distinguishing it from sibling tools like scan_project_bugs or get_open_bugs, which only detect or report bugs. The purpose is unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when bugs need fixing, and the existence of scan_project_bugs suggests a complementary tool, but there is no explicit when-to-use or when-not-to-use guidance. It does not name alternatives or state that this tool modifies code, so the agent must infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states that a notification is generated, but does not disclose what files are created, whether existing files are modified, any side effects, or the output format. This is a significant gap for a generation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the key action and resource. It contains no unnecessary words or repetition, making it highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, no output schema, no annotations), the description is too sparse. It does not explain the expected behavior, what the generated notification looks like, how the properties parameter works, or any post-generation steps, leaving the agent under-informed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%: notificationName and markdown have descriptions, while channels and properties do not. The description adds little meaning beyond the schema — it restates channel options that are already in the enum and fails to explain the `properties` parameter, which is a complex array of name/type objects.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's purpose: generating a Laravel notification and listing the main channels involved (mail, database, broadcast, SMS). This distinguishes it from sibling tools like generate_mail or generate_job, though it omits the slack channel present in the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: when you need a Laravel notification. However, it provides no explicit guidance on when to choose this tool over alternatives, such as generate_mail or generate_job, nor does it state 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosure. It does reveal the sequence of operations, which is useful, but omits important behavioral details: it does not specify whether all changes are committed, what happens if the repo already exists, or whether authentication is required and how failures are handled. The description adds context about the workflow but not enough for a safe, informed invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence with a clear, sequential arrow notation. It is front-loaded with the core purpose ('Complete git workflow') and every element contributes to understanding the tool's scope. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is complex (multi-step) with no output schema and no annotations, yet the description only provides a high-level sequence. It lacks context about prerequisites (e.g., authenticated GitHub CLI), what gets committed, how visibility is applied, return values, error handling, and interactions with existing repositories. An agent would have many unanswered questions before invoking this tool safely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 for parameter documentation. It does not mention any parameters (repoName, visibility, description) or clarify their roles in the workflow. The schema itself provides basic names and defaults, but the description adds no additional meaning or context for how these parameters affect the setup process.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a complete git workflow with a specific sequence: auth check -> init -> create repo -> commit -> push -> tag. This identifies the tool's purpose as a multi-step orchestration, distinguishing it from sibling tools that handle individual steps. However, it does not explicitly differentiate from alternatives like git_sync.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus the granular sibling tools (e.g., git_commit, git_push) or git_sync. It implies usage through the name 'full_setup' and the workflow sequence, but lacks clear context about appropriate scenarios or prerequisites such as authentication state.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It states it commits and pushes, which implies remote mutations, but does not explain nuances like how the commit message is determined, what repository state is required, or whether changes are staged automatically. The lack of detail on side effects is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently conveys the action. It avoids filler but is arguably too terse; a bit more context about the sync behavior would improve clarity without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of annotations, output schema, and parameters, the description is the sole source of context. Yet it omits critical operational details such as commit message handling, staging behavior, branch/submodule assumptions, and any prerequisites. This makes the tool's practical usage under-specified for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, as indicated by the empty input schema. Per the baseline for parameterless tools, the description need not add parameter details. It gains no knowledge from parameters, so the description's lack of parameter info is acceptable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs a manual sync consisting of commit, push, and optional tagging. This distinguishes it from siblings like git_commit, git_push, and git_tag_create by explicitly bundling those operations. However, the phrase 'if needed' introduces slight ambiguity about when tagging occurs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 executing git_commit, git_push, and git_tag_create individually. The description does not mention alternatives or exclusions, leaving the agent to infer usage from the terse phrase 'Manual sync'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries the full burden of behavioral disclosure. It only states the conversion action and does not mention side effects, file creation locations, overwriting behavior, or other runtime impacts. The phrase 'matching design' is vague and does not clarify what the generated component will contain or how it integrates with the project.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no unnecessary words. It is front-loaded with the action and delivers the core message efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has three parameters, no output schema, and no annotations. The description is too brief to provide sufficient context for correct usage. It does not explain the workflow, expected input format for 'imageDescription', or what the generated component looks like. This is incomplete for a tool that generates code.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is low (33%) and the description does not compensate. While 'imageDescription' is explained in the schema ('Describe the layout and components visible in the image'), the description adds nothing about 'layout' or 'componentName'. The tool's description does not clarify the meaning or purpose of these parameters, leaving the agent to guess.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Convert an image/mockup description to a Livewire component with matching design.' It uses a specific verb ('Convert') and resource ('Livewire component'), and the phrase 'image/mockup description' distinguishes it from sibling converters like convert_html_to_livewire and convert_figma_to_livewire.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. The description does not mention any prerequisites, context, or exclusions. Given the presence of sibling conversion tools (HTML, Figma, Stitch), this lack of differentiation criteria is a clear gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 fails to disclose whether the operation is destructive, whether it overwrites existing snapshots, what the response is, or how the optional files parameter affects the snapshot. 'Snapshot' implies a safe capture, but the mutation and side effects are unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It states the action and object succinctly, ideal for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool has only 2 params, the description leaves critical context unexplained: what does 'snapshot' mean for the file list, does the required description serve as a label, and how does this interact with version storage? With no output schema and no annotations, the description is insufficiently complete for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no explanation for the parameters (files, description). The agent cannot infer what 'files' or 'description' mean from the text, so the description provides zero added value beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Create') and resource ('version snapshot'), and clearly scopes it to 'the current project state.' This distinguishes it from siblings like list_versions and restore_version.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intent is implied through the phrase 'current project state,' but there is no explicit when-to-use or alternative guidance. It does not mention when to choose this over list_versions/restore_version, but the verb 'Create' makes the use case somewhat obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. It states what the tool generates (phases and task groups) but does not mention potential side effects, whether it writes to disk, or how the output is returned. For a generation tool, this lack of clarity about behavior is a notable gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the primary purpose and includes the key scope. There is no unnecessary repetition or filler, and it is well-structured for quick reading.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple with only two parameters, and the description covers the core output (plan with phases and task groups). However, since there is no output schema and no annotations, the description does not fully explain what a plan contains or how the custom parameter integrates. Given the breadth of sibling tools, additional context on how this fits into a development workflow would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 for parameter understanding. It indirectly lists the keyword enum values by mentioning SaaS, Enterprise, E-Commerce, and Portfolio, but it fails to mention the 'custom' parameter at all, leaving its purpose unclear. The description does not add meaningful detail for either parameter beyond what the schema bare enum shows.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a full-stack development plan with phases and task groups, and specifies the supported project types (SaaS, Enterprise, E-Commerce, Portfolio). This is a specific verb and resource, distinguishing it from other generate_* tools. However, it doesn't explicitly differentiate itself from sibling tools like generate_project_structure, leaving the distinction to inference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a full-stack development plan is needed for the listed project types, but it does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention any alternatives. For example, it doesn't say to use generate_project_structure for directory layout instead. This is implied usage rather than clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure, but it only states the base action. It does not mention side effects (e.g., does it checkout the new branch?), the meaning of 'from', or any potential failure modes. This is a minimal disclosure for a mutating operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the action, and contains zero extraneous words. It is as concise as possible while conveying the primary purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple but the description is underspecified. No output schema exists, and there are no annotations. The description does not explain return values, success/failure behavior, or the optional 'from' parameter. For a mutation tool, this is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does not explain 'name' or 'from' beyond what the schema shows. The 'from' parameter is especially unclear—does it specify a base branch or a different repository? The description adds no parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Create a new git branch' uses a specific verb and resource, clearly distinguishing it from sibling tools like git_branch_list, git_branch_merge, and git_branch_delete. It unambiguously states the action and target.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. The description does not mention context, prerequisites, or exclusions. While the purpose is obvious, the description lacks any explicit or implicit usage direction beyond the literal action.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure, but it only states the obvious operation. It doesn't mention what happens if there are no commits, whether it pushes to the current branch, or any prerequisites.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is immediately understandable and contains no redundant information. It is appropriately brief for the operation name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has two optional parameters and no output schema, the description should provide more operational context, such as defaults for branch and remote, or behavior when parameters are omitted. It falls short of being complete, though it's understandable for a standard git operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has two parameters (branch and remote) with no descriptions, and schema coverage is 0%. The description mentions 'remote repository' but doesn't explain the branch parameter or defaults, adding minimal value beyond parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool pushes commits to a remote repository, using a specific verb and resource. It differentiates from sibling tools like git_commit and git_pull by focusing on the push action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like git_sync or git_auto_sync_toggle. No exclusions or alternative references are given, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the literal action without disclosing side effects, whether the tag is pushed, error conditions for existing tags, or any other behavioral traits. This is a minimal disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, well-structured sentence that is front-loaded with the verb and resource. Every word earns its place; no unnecessary filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool, this is adequate but minimal. It lacks usage context, alternatives, and edge-case behavior, though the simplicity of the operation partially compensates. It is not misleading but leaves room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate. It clarifies the 'description' parameter via 'with description' but leaves 'version' undocumented. Though 'version' is fairly self-explanatory, the description adds only partial parameter context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (create) and the resource (annotated git tag), and the phrase 'with description' hints at the description parameter. It distinguishes from sibling git_tag_list by the creation action, though it doesn't mention the version parameter explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 create_version or git_tag_list. There are no exclusions, prerequisites, or context that would help an agent choose this tool appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states the tool 'generates commands', which implies it does not execute them, but it does not disclose whether it modifies files, what output format to expect, or any side effects. This is insufficient behavioral transparency for a tool that might be expected to execute installation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, information-dense sentence. It is front-loaded with the core action ('Generate Laravel 13 installation commands') and immediately specifies key details (PHP 8.4, Livewire). No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only two parameters and no output schema, but the description omits essential operational details: the expected output format (command list? script?), whether it writes files, and the role of projectName. The description is not complete enough for an agent to reliably invoke the tool without further assumptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 Livewire setup, which partially clarifies the 'features' parameter, but it does not explain the required 'projectName' parameter or the meaning of other potential feature values. The description adds some value but leaves major gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: generating Laravel 13 installation commands, with specific details about PHP 8.4 upgrade and Livewire setup. This distinguishes it from the many generate_* sibling tools, as it is the only one focused on installation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives. While it is implicitly for initial Laravel installation, the description does not mention any exclusions, prerequisites, or when a different tool (e.g., generate_livewire_component) would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries the full burden of behavioral disclosure. It reveals the generated artifact and its detail content, but does not disclose side effects (e.g., file creation, overwriting), required permissions, or return behavior. This is a significant gap for a code-generation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, front-loaded with the action and artifact, contains no redundant words; every phrase contributes meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is too sparse for a generation tool. It doesn't state whether the handler is written to disk, returned as code, what the column/index details look like, or how the optional customMessage is used.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents modelName and fields (67% coverage), but customMessage is left unexplained. The description adds only 'column/index details,' which loosely connects to the fields parameter, but doesn't clarify parameter roles or how customMessage affects output.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') and names the exact artifact: a Laravel UniqueConstraintViolationException handler with column/index details. This clearly differentiates it from sibling generate_* tools by product type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus the many sibling generation tools, nor any exclusions or alternatives. The only clue is the tool name and description, which imply code-generation use but don't state context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior, but it does not mention side effects (e.g., file creation/modification, overwrites), prerequisites (e.g., existing Laravel 13.2 project), or the generated endpoint's structure. The phrase 'generate' implies code output, but the exact behavior is opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the main action ('Generate a Laravel 13.2 API endpoint') and lists key features. It is concise with no irrelevant words, though the brevity contributes to the lack of behavioral detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 7 parameters, no output schema, and no annotations, so the description is the primary source of context. It fails to explain the tool's impact on the project (e.g., files written, routes registered) or the format of the generated code. For a code-generation tool with moderate complexity, the description is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 57%, and the description does not compensate for the gap. It does not explicitly explain any of the seven parameters, only loosely referencing rate limiting and auth, which vaguely map to rateLimit and requireAuth. The description adds little meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as generating a Laravel 13.2 API endpoint with specific features (rate limiting, auth, validation, throttling middleware). It distinguishes itself from sibling tools like generate_routes by emphasizing the rate-limiting and middleware aspects, 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.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (i.e., when you need a Laravel endpoint with rate limiting and auth) but does not explicitly state alternatives or exclusions, such as using generate_routes for non-rate-limited endpoints. The usage context is only hinted at rather than clearly defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states 'Generate' without revealing side effects such as created files, modified configurations, registered routes, or authentication requirements. There is no indication of what the agent should expect after invocation, leaving an important transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler or repetition. It efficiently conveys the core action and object type. However, it is arguably too terse overall, but from a pure conciseness standpoint it is appropriately sized given the limited intent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 5 parameters, no output schema, and no annotations, the description should provide additional context such as what the generated channel includes, whether it creates the channel class, event classes, or route registrations, and any setup steps. The single sentence covers only the high-level purpose, leaving the tool under-specified for practical invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 20% (only channelName has a description), so the description must compensate for the other four parameters. It vaguely references 'presence and private channels' which partially maps to the type parameter but does not explain auth, events, or presenceEvents semantics. The description adds minimal value beyond the schema, and the bulk of parameter meaning remains undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') and resource ('Laravel Reverb WebSocket channel') with a clear purpose ('real-time broadcasting'). It distinguishes itself from sibling generator tools by naming the exact type of channel. 'Presence and private channels' adds scope, making the tool's intent unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for real-time broadcasting and channel generation, which is a clear context. However, it provides no explicit 'use when' or 'use instead of' guidance and does not distinguish when this tool should be chosen over other generator siblings. The usage context is implied but not explicitly stated with alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It does not state whether the tool writes to a file, appends to an existing routes file, or simply outputs code. It also omits prerequisites like requiring Livewire installation or the impact on existing project structure. The description only reveals the output syntax, not the behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with essential information: the action, target, and key features. It avoids filler and is appropriately sized for the task. However, it could be slightly more structured to lead with the most critical details, but it remains concise and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (two array parameters with nested objects) and the absence of annotations and output schema, the description is incomplete. It does not explain what the tool returns, whether it modifies files, or how the parameters should be structured. The description needs additional context about side effects and parameter usage to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 'middleware' and 'groups' as features, but does not explain that the 'routes' parameter requires 'path' and 'component', or that 'groups' contains a nested 'routes' array. The description adds marginal value over the schema and fails to clarify parameter structure and relationships.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Generate' and the resource 'Laravel 13 routes' with specific technical details (Livewire Route::livewire() syntax, middleware, and groups). It distinguishes itself from sibling generate_* tools by focusing exclusively on routes, leaving no ambiguity about the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for generating route definitions in Laravel projects, which is a clear context. However, it does not explicitly state when to use it over alternatives or mention exclusions, such as when not to use it (e.g., for manually editing routes). Given that many sibling tools exist, more explicit guidance would be beneficial.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states 'Create a GitHub Release,' without mentioning side effects, requirements (e.g., tag must exist), publishing behavior, or permissions. This leaves significant uncertainty about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with zero wasted words. It is concise while still conveying the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple creation tool with three parameters and no output schema, the description is minimally viable. However, the absence of annotations and behavioral details (e.g., whether the tag is created automatically or must pre-exist) leaves gaps that a more complete description could fill.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description adds no parameter explanations. While parameter names (tag, title, notes) are somewhat self-explanatory, the description does not clarify details like the tag format or whether notes support Markdown, leaving room for misinterpretation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Create a GitHub Release' uses a specific verb and resource, clearly distinguishing it from siblings like gh_repo_create and gh_pr_create. It is unambiguous about the action performed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, nor any prerequisites or exclusions. The one-line description gives no context for selection among related release/tag/PR tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description bears the full burden of disclosing behavior. It fails to mention potential side effects like merge conflicts, whether it updates the working tree, or if local changes could be overwritten. The phrase 'pull latest changes' implies a fetch and merge but lacks specifics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no unnecessary words. It conveys the core purpose instantly and efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only two optional parameters and no output schema, so completeness expectations are moderate. The description covers the basic purpose but lacks behavioral and parameter details, leaving it minimally viable rather than fully informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 for parameter meaning. It does not mention either 'branch' or 'remote', nor explain their defaults or how they affect the pull operation. The parameters remain underspecified despite being intuitively named.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: pulling latest changes from a remote repository. It uses a specific verb ('Pull') and identifies the resource ('remote repository'), effectively distinguishing it from sibling tools like git_push and git_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 git_sync or git_full_setup. The description simply states what it does without any context about appropriate usage scenarios or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosure. It only says 'store' without explaining behavior like whether an existing key is overwritten, persistence scope, or any side effects. This is a mutation tool, and zero behavioral detail makes it insufficient for the agent to anticipate outcomes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that is direct and front-loaded. Every word earns its place, and there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a simple key-value store, but the description lacks essential context: no mention of overwrite behavior, persistence, potential return values, or how the memory relates to the project lifecycle. Since there is no output schema and no annotations, the description alone is insufficient for an agent to fully understand the consequences of calling this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 minimally relates 'key-value' to the parameters, implying the key is the identifier and the value is the stored content. However, it adds no detail on format, constraints, or valid values, leaving the schema types as the only real documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action ('Store') on a specific resource ('key-value memory for the project'). It distinguishes itself from siblings like 'recall_context' (which presumably retrieves memory) and generation tools by indicating a write operation for project memory.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'memorize_endpoint' or 'recall_context'. It neither states prerequisites nor when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only reveals that it updates status and syncs to git. It does not disclose whether the operation is reversible, what permissions are needed, what happens if the git sync fails, or if there are any transition restrictions between statuses.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that states the core action and the git sync behavior without unnecessary words. Every word contributes to understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 3-parameter tool with no output schema, the description gives the main functionality and the git sync side-effect. However, it omits context about preconditions (e.g., git repo, task existence), error handling, and what 'auto-sync' concretely does (e.g., commit/push).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description does not explain the meaning of 'phaseIndex' and 'taskIndex' or how they identify a task. The enum values are already in the schema, so the description's mention of statuses adds no new meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Update a task status', specifies the allowed statuses (pending, in_progress, complete), and adds a distinctive side-effect: 'auto-sync to git'. This distinguishes it from sibling tools which are mostly generation, git, or bug-related.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, no prerequisites, and no mention of typical contexts such as 'after completing a task' or 'when a phase/task progresses'. Usage is only implied by the tool's name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It lists generated features but omits crucial side effects such as file creation/overwriting, assumptions about model existence, reversibility, or error conditions. This lack of transparency could lead to incorrect usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that directly states the tool's purpose and core features with no fluff. It is appropriately sized and front-loaded, meeting the conciseness criterion.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex code-generation tool with six parameters and no output schema or annotations, the description is too short. It does not explain the return value, file operations, how parameters map to the generated component, or expected outcomes, leaving the agent without sufficient context to use it reliably.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 33% (only model and modelClass are described). The description does not explain the remaining parameters (fields, layout, authorize, softDeletes) and only indirectly hints at authorization and validation. It fails to compensate for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a complete CRUD Livewire component and lists key features (index, create, edit, delete, validation, authorization, pagination). This specific verb+resource targeting distinguishes it from sibling tools like generate_form_component or generate_livewire_component.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for complete CRUD generation but does not explicitly state when to use this tool over alternatives, nor provide exclusions or prerequisite conditions. The agent must infer usage from the name and feature list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions helper methods but does not state side effects like file creation, overwriting behavior, or required authentication. This is a significant gap for a generator tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with the verb 'Generate' leading. It contains no filler words and directly states the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The core purpose is conveyed, but the description lacks usage context, output details, and behavioral caveats. With no output schema and no annotations, the description does not fully explain what the generated enum looks like or where it is placed, leaving the completeness at a minimally viable level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 33% (only enumName is described). The description adds meaning by mentioning labels, colors, and helper methods, which partially explains the 'values' parameter structure, but it does not clarify 'type' or the full expected format of values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates a Laravel 13 backed enum, specifying the value types (string/int) and features (labels, colors, helper methods). This distinguishes it from sibling code generators like generate_policy or generate_eloquent_model.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 other generate_* siblings. The description only states what it does, not the context or criteria for selecting it over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full burden of behavioral disclosure. It lists component features but does not describe side effects, such as creating files in the project, prerequisites like an existing Livewire setup, or whether existing files are overwritten. This is a significant gap for a code-generation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the primary purpose, and contains no filler. Every word adds value, listing the key features in a compact manner.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 parameters, no schema descriptions, no annotations, and no output schema, the description is too brief. It does not explain what 'validation' or 'progress' entails, what the generated component looks like, or how to use it. The feature list provides a high-level overview but is insufficient for a tool with this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the description only loosely maps to a few parameters (preview to hasPreview, multiple to multiple). It does not explain the meaning or relationship of other parameters like model, modelClass, maxSize, or acceptedTypes. The description adds minimal value beyond listing some feature names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's function: generating a Livewire file upload component. It lists specific features (preview, validation, progress, multiple files, drag-drop) that distinguish it from siblings like generate_form_component or generate_livewire_component.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied through the description and name, but there is no explicit statement about when to use this tool versus alternatives like generate_form_component or generate_crud_component. The feature list helps, but no alternatives or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavioral disclosure. It does not explain side effects, whether it creates or overwrites files, or how it integrates with the project. It only mentions dark mode support as a feature, which is not enough behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 purpose and a key feature, making it appropriately sized and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 6 parameters, no annotations, and no output schema, the description is too sparse. It omits the available fluxType choices, variant semantics, and behavioral context, making it insufficient for correct invocation in many cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only 33% of parameters have schema descriptions (componentName and content), and the description does not elaborate on fluxType, variant, size, or slots. The user must infer meaning from enum names, leaving ambiguity (e.g., slots).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Generate' with the resource 'Livewire Flux UI component' and specifies the official Flux library and dark mode support. This clearly distinguishes it from the sibling generate_livewire_component and other component generators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for creating Flux components but does not state when to choose this tool over alternatives like generate_livewire_component or convert_html_to_livewire. It also does not mention exclusions, so usage context is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 lists capabilities but does not state side effects (e.g., file creation, overwriting), permissions, or project modifications. The agent is left without critical information about what invoking this tool actually does to the project.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently conveys the tool's purpose and key features. Every word adds meaning, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 only 20% schema description coverage, the description is insufficient for an agent to fully understand the tool. It does not explain how to specify relationships, dynamic fields, or file uploads via the schema, nor what the generated component looks like or how it integrates into the project.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is low (only 'model' has a description). The description's list of features (relationships, file uploads, etc.) gives a vague hint about the 'fields' array, but it does not explain the other parameters like 'layout', 'authorize', or 'modelClass'. The description fails to compensate for the schema's sparse parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's verb ('Generate') and resource ('Livewire form component'), and enumerates specific capabilities (relationships, nested data, validation, file uploads, dynamic fields) that distinguish it from sibling tools like generate_livewire_component or generate_modal_component.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used when creating a Livewire form component with advanced features, but it provides no explicit when-to-use, when-not-to-use, or alternative guidance. With many sibling generators, this lack of explicit direction leaves the agent to infer the appropriate context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full burden of disclosing behavior. It only states what the tool does (generates an observer) but does not mention side effects such as file creation, overwriting existing files, naming conventions, or whether it requires existing models. It also doesn't clarify the output format or whether it modifies the Laravel project structure. This lack of behavioral context is a significant gap for a code generation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately communicates the tool's purpose. It contains no fluff, repetition, or unrelated details, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has three parameters, no output schema, and no annotations. The description only provides a high-level purpose without elaborating on parameter semantics, expected behavior, or return values. This is insufficient for an agent to confidently invoke the tool correctly, especially given the complexity of configuring event handlers and model class references.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the three parameters (model, events, modelClass). It only mentions event types ('creating, updating, deleting, etc.'), which loosely aligns with the events parameter, but it fails to clarify the distinction between 'model' and 'modelClass', the structure of the events array, or the meaning of 'action'. The description adds minimal value beyond the raw schema, leaving parameter usage ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate a Laravel model observer for handling model events.' It specifies the resource (model observer) and the exact action (generate), and it differentiates from sibling tools like generate_eloquent_model (which creates models) and generate_policy (which handles authorization). The mention of specific events (creating, updating, deleting) adds concrete scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it: when a Laravel model observer is needed to handle model events. However, it provides no explicit guidance on when not to use it or how it compares to alternative tools (e.g., using events directly, policies, or model boot methods). No context is given about prerequisites or scenarios where this tool is the best choice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral context. It states the outputs (files, configs, routes) but does not disclose whether it overwrites existing files, requires a pre-existing Laravel installation, or has side effects. This is a significant gap for a scaffolding tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that conveys the core purpose without unnecessary filler. Every word adds value, and the structure is front-loaded with the action and scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool of this complexity (generating an entire project structure), the description is far too sparse. It lacks information about return values, side effects, prerequisites, or what specific files and routes are included. The absence of an output schema and annotations makes this gap more damaging.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%; the description does not explain projectName or features. It partially clarifies the 'type' parameter by listing enterprise/SaaS/API values, but does not provide enough semantic guidance for the required projectName or the features array.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') and clearly specifies the resource: a complete enterprise/SaaS/API Laravel 13 + Livewire project structure including files, configs, and routes. This distinguishes it well from sibling tools that generate individual components or policies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a full project scaffold is needed, but does not explicitly state when to use this versus alternatives like generate_layout or install_laravel. There are no clear exclusion criteria or cross-references to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, but it only states the action of generating a class. It does not disclose side effects like file creation, overwriting, need for existing directories, or return values. This lack of behavioral detail could lead to unexpected consequences.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant or filler words. It delivers the core purpose quickly and is easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and incomplete parameter documentation, the description should provide more context. It lacks guidance on the methods parameter, expected file placement, or what constitutes a valid service class. This is insufficient for users to use the tool confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema describes serviceName, but methods is completely undocumented. The description does not mention methods at all, leaving half the parameters without meaning. The description's examples hint at naming conventions but do not explain how to define methods or their parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a Laravel service class for business logic, with concrete examples (BillingService, NotificationService). This verb+resource combination is specific and distinguishes it from sibling generators like generate_policy or generate_enum.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for business logic' and the examples imply when to use this tool, but there is no explicit 'use this when' or any alternatives/exclusions. It relies on the user's inferential ability rather than providing direct guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. The verb 'Get' implies a read-only operation, but the description does not explicitly confirm non-destructive behavior, mention output format, or describe any side effects. It provides minimal transparency beyond the tool's name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no wasted words. It front-loads the purpose and is easy to parse. It earns its place as a clear, crisp definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one optional parameter, no annotations, no output schema), the description is still incomplete. It omits any mention of the filter parameter, does not clarify relationship to sibling get_fixed_bugs, and provides no information about return values. It lacks the full context needed for an agent to use it confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% (no parameter descriptions). The description does not mention the 'filter' parameter, its enum values, or the 'all' default. Although the schema provides an enum and default, the description fails to compensate for the lack of schema descriptions. The parameter semantics are not communicated at all.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'list of all open (unfixed) bugs.' It explicitly specifies 'unfixed,' which distinguishes it from the sibling tool get_fixed_bugs. This is a specific, non-tautological statement of purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'open (unfixed) bugs,' which suggests it is not for fixed bugs. However, it does not explicitly name alternatives like get_fixed_bugs or state when to use this tool over other bug-related tools. Guidance is implied, not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states the action ('create') and 'set up remote' without detailing authentication requirements, default visibility (private), potential to override existing remotes, or error handling if the repo already exists. These are significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of eight words, front-loading the essential information and containing no wasteful language. It is appropriately concise for the simplicity of the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple, but given the absence of annotations, output schema, and parameter descriptions, the description is incomplete. It omits what the tool returns (e.g., repo URL), prerequisites like GitHub authentication, and behavioral details such as default visibility. This is insufficient for an agent to confidently invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not compensate by explaining the parameters 'name', 'visibility', or 'description'. It mentions neither defaults (e.g., visibility defaults to private) nor how the parameters map to the operation. The parameter names are self-explanatory, but the description adds no extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Create' and the resource 'a new GitHub repository', and adds the specific action 'and set up remote'. This distinguishes it from sibling tools like gh_pr_create or git_commit, which handle different GitHub operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for creating a new repository and setting up a remote, but provides no explicit when-to-use or when-not-to-use guidance. It does not reference alternatives such as git_full_setup, so the reader must infer the appropriate context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full behavioral burden. It simply states the action without disclosing side effects (e.g., whether the change is permanent, if it requires permissions, or what happens if the bug ID is invalid). It does not mention whether it is idempotent or what response to expect.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no unnecessary words. It is front-loaded with the verb and object, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool, the description is minimally adequate, but it omits any note about return values, error handling, or the relationship to get_open_bugs/get_fixed_bugs. A more complete description would state the effect and expected outcome.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'by bug ID' which maps directly to the single bugId parameter, providing context that the string refers to the bug's identifier. However, it does not explain the format, validation, or typical usage (e.g., obtaining the ID from a list of open bugs).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific action 'Mark a bug as fixed' with the resource 'bug' and identifies the key parameter (bug ID). It clearly distinguishes from siblings like fix_bugs (which actually fixes code) or get_open_bugs (which lists bugs).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like fix_bugs or update_task_status. It does not mention prerequisites, whether the bug must exist, or whether this is the manual status update after running fix_bugs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions generation attributes but does not describe side effects such as file creation, directory placement, overwriting behavior, or required Laravel project context. The phrase 'Generate a ... job' implies a file be created, but the absence of details about the generation process or potential prerequisites is a notable gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the core purpose and key distinguishing features. Every phrase earns its place—'Laravel 13.2 queued job' sets the artifact type, and the attribute list and feature mentions provide essential context without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 8 parameters and no output schema, the description is very brief and does not explain what happens after generation (e.g., file output, location, or follow-up actions). It lacks critical context for a generator tool, such as whether it writes to a specific directory or how 'enum support' affects the generated code. The high schema coverage mitigates parameter ambiguity, but the overall description is insufficient for a tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is high (88%), so the schema already documents most parameters (jobName, queue, tries, etc.). The description adds context about Laravel 13.2 attributes and enum support, but does not detail specific parameter syntax or relationships beyond what the schema provides. Thus, it meets the baseline but does not significantly enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a Laravel 13.2 queued job, specifying key attributes (#[Queue], #[Connection], #[Backoff]) and features like enum support and retry handling. This distinguishes it from sibling generators (e.g., generate_eloquent_model, generate_policy) by naming the exact artifact type. The verb 'Generate' and resource 'Laravel 13.2 queued job' make 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.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used when creating a queued job, but it does not explicitly state when to use it over alternatives or provide exclusions. There is no mention of when not to use this tool or which sibling tools might be more appropriate for other scenarios. However, the context is clear enough for an agent to infer the primary use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must convey behavioral traits, but it only says 'Generate' without disclosing whether it writes files, requires an existing model, or modifies the project. There is no mention of side effects, permissions, or outputs, leaving significant behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that clearly states the action and scope. It is concise with no filler, and every word contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 6 parameters, no annotations, and no output schema, but the description is only one sentence. It does not explain prerequisites, generated file structure, or how parameters like modelClass and layout affect output. The description is too sparse to be contextually complete for a complex generator.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions multi-field filters, date range, sorting, and pagination, which partially maps to the filters, sortOptions, and searchFields parameters. However, the core parameters model, modelClass, and layout are not semantically explained, and with 0% schema coverage, the description only partially 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a Livewire search and filter component with specific features (multi-field filters, date range, sorting, pagination). This specific verb+resource combination distinguishes it from sibling tools like generate_crud_component or generate_form_component.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when building search/filter UI but does not explicitly state when to use this tool over alternatives like generate_data_table or generate_crud_component. It lacks any when-not or alternative guidance, so it only provides implied usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral details on its own. It only states the generation action and lists trait names, but omits critical behaviors such as whether it creates a file, overwrites existing files, or requires an existing Laravel project. No side-effect information is given.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the action, and the parenthetical adds useful detail without bloat. Every word contributes to understanding the tool's core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description needs to cover behavioral and parameter semantics fully. It fails to clarify the 'description' parameter's purpose, file output expectations, or project prerequisites, making it insufficient for a non-trivial code generation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description lists the enum values for traitName in parentheses, which adds meaning beyond the bare schema enum. However, the optional 'description' parameter is not explained at all, leaving a gap given the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Generate' and identifies the resource as 'a reusable PHP trait for Laravel models', listing the exact available trait names. This distinguishes it clearly from sibling generation tools like generate_policy or generate_eloquent_model.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (when you need a trait for Laravel models) but provides no explicit guidance on when to choose this tool versus alternatives, nor any exclusions. The parenthetical list of trait names hints at scope, but no 'use this instead of X' statement is present.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the main action (staging and committing) but does not explain side effects like creating a commit object, behavior when the files list is empty, or failure conditions. For a mutating operation, this is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no redundancy. It is front-loaded with the action and resource, making it highly concise and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a git commit tool with no output schema and no annotations, the description omits key operational details: what happens if files is empty, what 'conventional commit' format is used, and how message and autoGenerate interact. This makes it incomplete for robust agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions are absent (0% coverage), so the description must compensate. It adds meaning by indicating that 'files' are the targets of staging/committing and that messages are auto-generated. However, it does not clarify the 'message' parameter or how it interacts with 'autoGenerate', leaving ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Stage and commit' with a clear resource ('files') and mentions the unique behavior of auto-generating a conventional commit message. This clearly distinguishes it from sibling tools like git_push, git_pull, and git_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage is implied: it is for staging and committing files locally. However, the description does not explicitly state when to prefer this tool over alternatives, nor does it mention exclusions or prerequisites (e.g., that a git repository must exist).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 says 'Generate' but does not disclose side effects like file creation, overwriting behavior, prerequisites, or output details. This is a significant gap for a scaffolding tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with the main purpose, and every word adds value. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex generator with 7 parameters, no output schema, and no behavioral context, the description is too thin. It does not explain what files are created, how parameters map to output, or any prerequisites, leaving the agent under-informed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 29% (model and modelClass). The description lists features but does not explain how parameters like columns, filters, layout, or enableExport influence the generated component, failing to compensate for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the verb 'Generate', the target resource 'Livewire data table component', and enumerates concrete features (sorting, filtering, search, pagination, bulk actions, export). This distinguishes it from sibling tools like generate_livewire_component and generate_crud_component.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context: use this tool when you need a data table component. It does not explicitly mention alternatives or exclusions, but the purpose is clear enough that an agent can infer when to select it over other component generators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose what the tool actually produces (e.g., files, code snippets), whether it modifies existing files, or any prerequisites. 'Generate' implies creation but offers no behavioral detail beyond that.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the action and object, with no unnecessary words. It is concise and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given six parameters, no output schema, and no annotations, this minimal description is insufficient. It does not explain parameter defaults, how the generated modal behaves, or what the output looks like, leaving significant gaps for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only hints at the modalType values by listing 'confirmations, delete actions, forms, alerts'. It does not explain title, fields, message, actionName, or modelClass, so it fails to compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Generate' and the resource 'reusable Livewire modal component', and specifies the use cases (confirmations, delete actions, forms, alerts). This distinguishes it from sibling tools like generate_livewire_component and generate_form_component.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear context by naming the specific modal use cases (confirmations, delete actions, forms, alerts), so an agent knows when to choose it. However, it does not explicitly mention exclusions or alternatives, such as using generate_form_component for standalone forms.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 disclosing side effects. It fails to mention that the tool likely creates or modifies files, any prerequisite directory structure, whether existing files are overwritten, or what the generated output looks like. The description only states the purpose without 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that conveys purpose, version, and attribute with no redundant words. It is front-loaded and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
A code generator with 4 parameters, no annotations, and no output schema needs more contextual detail. The description omits key facts: what files are generated, whether the component is registered automatically, any dependencies, and the expected return value. This leaves the agent underinformed for successful invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 50% (name and events are described, methods and hasModal are not). The description adds no information about any parameters, so it does not compensate for the undocumented ones. An agent parsing only the description would be unaware of events, methods, and hasModal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') and resource ('Livewire 4.2.1 renderless component') with the distinctive '#[Renderless] attribute' and 'logic-only components' scope. This clearly distinguishes it from sibling tools like generate_livewire_component or generate_form_component.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for logic-only components' provides clear context for when to use this tool, differentiating it from view-based generators. However, it does not explicitly state when not to use it or name alternatives, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full behavioral disclosure burden. It states 'comprehensive' and lists assertion types, but gives no information about side effects: whether it writes files, overwrites existing tests, requires an existing component, or outputs code vs. saving it. This lack of behavioral detail is a significant gap for a generation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that directly communicates the tool's purpose and key capabilities without any filler. Every word contributes to understanding what the tool does, making it a model of conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 params, nested objects, no output schema, no annotations), the description is far too sparse. It does not explain the expected input structure for 'fields', the role of 'modelClass', or what the generated test output looks like. An agent would likely struggle to provide valid arguments for all parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 14% (only componentName described). The description partially maps to auth/validation parameters ('hasAuth', 'hasValidation') and database assertions (via 'modelClass'), but it does not explain the complex 'fields' parameter structure (name, testValue, invalidValue) or clarify the meaning of 'hasEdit'/'hasDelete'. The description does not sufficiently compensate for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') with a concrete resource ('Pest tests for Livewire components') and adds qualifying details (auth, validation, database assertions). It clearly distinguishes itself from sibling generation tools like generate_policy or generate_enum, which target different artifacts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly establishes when to use the tool: when Pest tests for Livewire components are needed. It clearly states the use case and component type, but does not explicitly mention exclusions or alternatives. Since no other sibling tool generates tests, the context is sufficiently clear for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 does not mention side effects (e.g., whether it overwrites existing CI configs, creates new files, or requires GitHub authentication). For a setup tool that likely modifies the project, this lack of transparency is a notable gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is immediately clear and front-loaded. Every word earns its place, with no unnecessary filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the zero-parameter schema and lack of annotations/output schema, the description is minimally complete for selection but lacks behavioral context. It doesn't explain what 'setup' entails (e.g., whether it creates a workflow file, requires repo permissions, or affects existing CI). This is adequate for a simple tool but not fully informative for an agent anticipating consequences.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema is empty, so there is no parameter semantics to add. Baseline for 0 params is 4; the description does not need to compensate for any missing parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Setup') on a specific resource ('GitHub Actions CI') with a clear scope ('for Laravel'). This distinguishes it from sibling tools like git_full_setup or gh_repo_create, which focus on different aspects of project/repo management.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. The usage context is only implied by the tool's name and one-line purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It does list the vulnerability types covered, which adds meaningful context about what the audit checks. However, it does not state whether the tool modifies code, its output format, limitations, or side effects. 'Audit' implies read-only, but this is not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence. It front-loads the verb and resource, then compresses the vulnerability list efficiently. Every word adds value, and there is no redundant or filler text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (security auditor) and lack of annotations/output schema, the description is incomplete. It omits the return format (e.g., list of findings with severity), whether the tool is safe/read-only, and any limitations (e.g., static analysis only, false positives, version-specific checks). The user gets enough to select the tool but not to predict its full behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%; code is described as 'Code to audit' and fileType has an enum with no description. The tool description does not explain the fileType options (php, blade, model, component, routes) or how they affect the audit. It adds context about vulnerability categories but not about the parameters themselves.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific verb ('Audit') and resource ('Livewire 4.2.1/Laravel 13.2 code'), then enumerates precise vulnerability categories (XSS, SQL injection, mass assignment, etc.). This clearly distinguishes it from sibling bug-scanning tools like scan_project_bugs or deep_scan_bugs by focusing specifically on security vulnerabilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool: when you need a security audit of Livewire/Laravel code. However, it provides no explicit guidance about alternatives, exclusions (e.g., non-security issues, other framework versions), or when not to use it. The context is present but implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses the included features (attributes, relationships, scopes, casts, observers, v13.2 features), but does not mention file creation location, overwrite behavior, or prerequisites. This is a moderate level of transparency for a code generator.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the key action and feature list. It is efficient but somewhat of a run-on; a little more structure could improve readability without adding length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a complex tool with 13 parameters, no annotations, and no output schema. The description only scratches the surface by listing features, and fails to convey the generation workflow, prerequisites, or how parameters map to output, making it inadequate for full understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 31%, and the description does not explain the many undocumented parameters. It loosely references categories like relationships and casts, but leaves table, fields, timestamps, softDeletes, and other parameters without additional meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates a Laravel 13.2 Eloquent model and lists distinguishing features (PHP 8.3 attributes, relationships, scopes, casts, observers, v13.2 features). This separates it from sibling tools like generate_observer or generate_policy, making its purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool: when you need an Eloquent model. It does not explicitly name alternatives or when-not conditions, but the context is clear enough that users can distinguish it from related generators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only states 'Generate' without elaborating on side effects such as file creation, whether it overwrites existing classes, or whether it requires an existing Laravel project. It also doesn't explain what the output will be beyond the class itself, leaving the agent uncertain about the tool's operational impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the main purpose and includes only meaningful details. It is economical and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no output schema, no annotations, and 6 parameters, the description is too brief. It fails to mention what the tool returns or creates (e.g., file path), prerequisites like a Laravel project, or potential conflicts. It also omits any guidance on the recipient parameter, making the description incomplete for an agent to safely invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds context to the schema by naming the feature areas that the boolean flags (hasAttachment, hasQueue, markdownTemplate) control, which supplements the bare schema defaults. However, it does not explain the 'recipient' parameter or provide details on how these features are implemented, leaving some parameters with only schema-level descriptions. With 50% schema coverage, the description partially compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Generate' paired with the resource 'Laravel 13 Mailable class' and enumerates distinct features (markdown templates, attachments, queue support), which clearly differentiates it from sibling generators like generate_notification or generate_job.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for creating a Mailable but provides no explicit guidance on when to prefer it over alternatives, nor any exclusions or context. It doesn't mention alternatives such as generate_notification for email-related classes, leaving the agent to infer usage from the purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description adds no behavioral details beyond the action. It doesn't disclose whether it lists local or remote branches, whether it requires an initialized git repository, or its safety profile (e.g., read-only nature is implied but not explicitly stated).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence: 'List all git branches.' It contains no redundant words and is easily parsed, meriting a perfect score for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity—no parameters, no output schema—the description is mostly adequate. It could be improved by clarifying the scope (local vs. remote branches) or typical usage, but for a basic list operation, it covers the essential information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema is trivially complete. With no parameters to document, the description doesn't need to elaborate, yielding a baseline of 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'list' and resource 'git branches', clearly distinguishing from sibling tools like git_branch_create or git_branch_delete. There is no ambiguity about the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It only states what it does, with no mention of typical scenarios (e.g., before merging or deleting) or exclusions, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 reveals that the generated resource includes relationships, meta, pagination, and conditional loading, but it does not disclose side effects such as where the file is written, whether it overwrites existing files, or any prerequisites. The features are named, but behavioral details are thin.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence that efficiently communicates the tool's purpose and main features. No redundant or extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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, the description is too brief to be fully self-sufficient. It does not explain parameter relationships, the meaning of 'conditional loading', output behavior, or file placement. An agent would need to rely on the schema and infer important details, making it incomplete for a tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is low (33%), so the description must compensate. It mentions relationships, meta, pagination, and conditional loading, which relate to some parameters (relationships, withMeta, withPagination, fields), but it does not map each parameter explicitly. The term 'conditional loading' is ambiguous without further explanation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Generate' and the specific resource 'Laravel 13 API Resource', and lists key features (relationships, meta, pagination, conditional loading). It distinguishes this tool from sibling generators like generate_eloquent_model or generate_policy.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (when creating an API resource) and the context is clear. However, it does not explicitly mention exclusions or contrast with alternative sibling tools, so it misses a point for full usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It implies a read-only operation via 'Get', but does not disclose whether data is real-time, cached, or whether it requires an active project context. Basic behavior is clear, but additional traits are not covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with no filler. It contains all necessary information in the minimal space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple no-parameter read tool, the description is sufficient. It names the key output areas (progress, phases, task status) without requiring an output schema. However, it could benefit from stating whether it returns a summary or detailed list, but this is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description correctly implies no input is needed, and there are no parameter meanings to elaborate on.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Get' and names concrete resources 'project progress, phases, and task status', uniquely distinguishing it from sibling tools like update_task_status or get_open_bugs. It clearly states what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It does not mention that it provides a high-level overview or that detailed task updates should use update_task_status. Absence of any context leaves the agent without selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for disclosing behavioral traits. It merely states 'Check GitHub CLI authentication status,' which implies a read-only operation but does not explicitly confirm it is non-destructive, does not describe what happens when unauthenticated, or mention any network calls or side effects. This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that directly states the tool's action and target. Every word earns its place, with no redundancy or irrelevant details. This is appropriately concise for a simple status-check tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's trivial complexity (zero parameters, no output schema, no annotations), the description is nearly complete. It clearly communicates the tool's function. However, it could be slightly improved by noting that it reports the current authentication state (e.g., 'returns the current status') or that it is safe to run, but the existing text suffices for this simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema already covers this fully. According to the rubric, a baseline of 4 applies for 0 parameters, since no additional parameter semantics are needed. The description adds no parameter information, but none is required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Check') and a clear resource ('GitHub CLI authentication status'). It directly states the tool's purpose and distinguishes it from the sibling tool gh_auth_login, which performs authentication rather than checking it.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage context is implied by the description: one would use this tool when needing to verify GitHub CLI authentication. However, it does not explicitly state when to use it versus alternatives, nor does it provide any exclusions or prerequisites. Given the simplicity of the tool, this is acceptable but minimal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It implies a read-only operation via 'List' but does not disclose response format, ordering, side-effect safety, or any other behavioral traits. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence: 'List all project versions.' Every word is necessary, and no waste exists.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, no-output-schema tool, the description fully states the core function. It is complete for the simplicity of the operation, though it does not explicitly mention return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so there are no parameter semantics to explain. The baseline of 4 applies, and the description adds no unnecessary parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' with resource 'project versions', clearly distinguishing it from sibling tools like create_version and restore_version. It precisely states what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use guidance or alternatives are provided. The usage is implied by the verb 'List', but there is no context on when to prefer this over other tools or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of disclosing behavior. It states the core action ('show') but does not reveal details like output format, whether it includes untracked files, or that it performs a read-only operation. It is not misleading, just minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no filler or redundancy. It is appropriately front-loaded, stating exactly what the tool does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no parameters and no output schema, the description provides sufficient information to understand the tool's purpose and behavior. The absence of output schema means the description need not explain return values, and the one-liner covers the essential context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the input schema fully covers the parameter space. The description adds no parameter semantics, but the baseline for zero parameters is 4, and nothing is missing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Show current git status' uses a specific verb ('show') and resource ('git status'), clearly stating what the tool does. It distinguishes itself from sibling git tools (like git_commit, git_push) by focusing on the status operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: the user must want to see the current repository status. However, it provides no explicit guidance on when to prefer this over other git tools or any prerequisites (e.g., being in a git repository), leaving context to be inferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It accurately indicates a code-generation action and lists the middleware class options. However, it doesn't disclose details like whether the generated file overwrites existing files, the expected file path convention, or whether namespace/registration steps are included. This is a moderate level of transparency for a generation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that states the action, the target (Laravel HTTP middleware class), and the complete set of options in parentheses. Every word earns its place; there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple: one parameter, no output schema, and a clear generation action. The description fully specifies the parameter domain, making the tool usable for an agent to invoke correctly. The only slight gap is the lack of behavioral information about the generation side effects, but for a simple generator, the description is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema describes the single parameter (middlewareName) with an enum of all six valid values, which provides complete shape information. The description's list of middleware names exactly matches the enum and adds meaningful context about what each preset represents, going slightly beyond the raw schema. With one parameter at 0% schema description coverage, the description compensates well by listing options.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Generate a Laravel HTTP middleware class' with a specific verb and resource. It lists the exact middleware names (Admin, Tenant, VerifyEmail, RateLimit, CheckSubscription, MaintenanceMode), which not only clarifies scope but also aligns perfectly with the sibling tool generate_custom_middleware, distinguishing this as the preset-based generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly scopes the tool to generating one of the six listed Laravel HTTP middleware classes, which implicitly tells the agent when to use it. While it doesn't name generate_custom_middleware as the alternative for custom middleware, the sibling context and the enumerated list strongly imply the distinction, giving 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.
Behavior3/5
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 states the core read-only behavior but does not disclose details such as output format, ordering, or whether local vs remote tags are listed. For a simple list operation, this is minimally sufficient but not enriched.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clean sentence that is front-loaded and contains no wasted words. It is a model of brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema), the description is complete enough for an agent to understand its purpose and invoke it correctly. It could mention output characteristics, but that is not critical for such a basic list operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The schema is empty and description adds no parameter detail, but there is nothing to add. This is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List all git tags' uses a specific verb and resource, clearly distinguishing it from sibling tools like git_tag_create. It is unambiguous and directly states the function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use the tool (when you need to see all git tags), but does not explicitly mention alternatives or exclusions. Given the simplicity of the operation, this is adequate but lacks explicit comparison to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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