MCP SAPUI5 Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation3/5
The tools cover distinct functional areas like analysis, generation, validation, and project management, but there is significant overlap in purpose within categories. For example, multiple analysis tools (analyze_current_file, analyze_ui5_project, analyze_odata_metadata) could confuse an agent about which to use for a specific analysis task, and tools like apply_project_patch and write_project_file_preview both handle file modifications with subtle differences.
Naming Consistency4/5
Most tools follow a consistent verb_noun pattern (e.g., analyze_current_file, generate_ui5_controller, validate_ui5_code), which aids readability. However, there are minor deviations such as mcp_health_report (noun_verb) and tools with longer, compound names (e.g., build_ai_context_index) that slightly break the pattern but remain understandable.
Tool Count2/5
With 51 tools, the count is excessive for a single server, making it overwhelming and difficult for agents to navigate efficiently. While the domain (SAPUI5 development and project management) is broad, the tools could be better organized or consolidated into fewer, more generalized tools to reduce complexity and improve usability.
Completeness5/5
The tool set provides comprehensive coverage for SAPUI5 development, including analysis, code generation, validation, security, performance, project management, and integration with AI/agent workflows. It supports full lifecycle management from legacy project intake to quality gates and patches, with no obvious gaps in the domain's core operations.
Average 3/5 across 51 of 51 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
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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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

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 'safe preview/apply flow' and 'growth-ready feedback artifacts', hinting at non-destructive previews and feedback generation, but lacks details on permissions, side effects, error handling, or output format. For a tool with 12 parameters and no annotations, this is insufficient to guide safe and effective use.
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, relatively concise sentence that front-loads the main purpose. However, it could be more structured by separating key features or adding brief clarifications, but it avoids unnecessary verbosity.
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 complexity (12 parameters, no annotations, but has an output schema), the description is incomplete. It lacks parameter explanations, behavioral details, and usage context, making it inadequate for a tool of this scope. The output schema may help with return values, but the overall guidance is minimal.
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%, meaning none of the 12 parameters have descriptions in the schema. The tool description does not mention any parameters or their purposes, failing to compensate for the lack of schema documentation. This leaves all parameters undocumented and ambiguous for the agent.
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 states the tool 'scaffold[s] and manage[s] project skills catalog' with some features mentioned, which gives a general purpose. However, it's somewhat vague about what 'scaffold' and 'manage' entail specifically, and it doesn't clearly differentiate from sibling tools like 'scaffold_project_agents' or 'validate_project_skills' beyond mentioning 'skills'.
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 mentions 'safe preview/apply flow' and 'growth-ready feedback artifacts', which imply some context for usage, but provides no explicit guidance on when to use this tool versus alternatives like 'scaffold_project_agents' or 'rank_project_skills'. There's no mention of prerequisites, dependencies, or specific scenarios for invocation.
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 'persist' which implies data storage/writing, but doesn't clarify what exactly gets persisted, where, or with what permanence. It doesn't address authentication needs, rate limits, side effects, or what happens in 'dryRun' mode. The description adds minimal behavioral context beyond the basic purpose statement.
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, reasonably concise sentence that states the purpose and intended benefit. It's front-loaded with the core action ('collect and persist') and avoids unnecessary elaboration. However, given the complexity of the tool (16 parameters), one could argue it's overly terse and could benefit from slightly more detail to justify its existence among many sibling tools.
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 tool with 16 parameters, no annotations, and 0% schema description coverage, the description is severely inadequate. While an output schema exists (which helps with return values), the description doesn't explain what 'contextual intake' means, what gets persisted, when to use this tool, or how it relates to the many sibling tools. The agent would struggle to understand when and how to invoke this tool 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?
With 16 parameters and 0% schema description coverage, the description provides no information about any parameters. It doesn't explain what 'intakePath' refers to, what 'dryRun' does, what 'reason' is for, or the meaning of any other parameters. The description fails to compensate for the complete lack of schema documentation, leaving all parameters semantically undefined.
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 states the tool 'collects and persists legacy-project contextual intake' which provides a verb ('collect and persist') and resource ('legacy-project contextual intake'), but it's somewhat vague about what exactly constitutes 'contextual intake'. It distinguishes from siblings by mentioning 'improve AI guidance quality while minimizing repeated prompts/tokens', but doesn't clearly differentiate from tools like 'prepare_legacy_project_for_ai' or 'refresh_project_context_docs' that might have overlapping purposes.
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. While it mentions the purpose of 'improving AI guidance quality', it doesn't specify prerequisites, timing, or when to choose this over sibling tools like 'prepare_legacy_project_for_ai' or 'refresh_project_context_docs'. The agent must infer usage from the tool name and parameters 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 provided, the description carries the full burden of behavioral disclosure. It mentions 'orchestrating' steps but doesn't explain what this entails operationally—e.g., whether it modifies files, requires specific permissions, has side effects like overwriting data, or handles errors. Terms like 'prepare' are ambiguous, failing to clarify if this is a read-only or mutative operation, which is critical for a tool with 11 parameters.
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 purpose. It avoids unnecessary words, but it could be more structured by explicitly listing key actions or outcomes. Given the complexity of the tool, a bit more detail might be warranted, but it's appropriately concise for its 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?
Given the tool's high complexity (11 parameters, no annotations, 0% schema coverage) and the presence of an output schema, the description is incomplete. It doesn't explain what 'preparing' involves, how parameters interact, or what the orchestration results in, leaving significant gaps for the agent to infer behavior. The output schema helps with return values, but the description fails to provide necessary context for safe and effective use.
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 by explaining parameters. It mentions 'ensure, intake, baseline, and context index steps,' which loosely relate to some parameters (e.g., 'runEnsureProjectMcp', 'refreshBaseline'), but doesn't define what these steps do or how parameters like 'sourceDir', 'autoApply', or 'maxDiffLines' affect them. This leaves most of the 11 parameters undocumented and their purposes unclear.
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 states the tool 'prepare[s] a legacy/existing project for high-quality AI delivery' and mentions it orchestrates 'ensure, intake, baseline, and context index steps,' which gives a general sense of its function. However, it's vague about what 'preparing' entails specifically (e.g., what changes are made) and doesn't clearly differentiate from sibling tools like 'ensure_project_mcp_current' or 'build_ai_context_index,' which might handle similar steps individually.
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 doesn't mention prerequisites, timing, or exclusions, such as whether it's for new vs. existing projects or how it relates to sibling tools like 'analyze_legacy_project_baseline' or 'collect_legacy_project_intake.' This leaves the agent without clear direction on appropriate usage contexts.
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 mentions 'incrementally' and 'deterministic output,' which adds some context about the refresh process, but it doesn't cover critical aspects like whether this is a read-only or mutating operation, potential side effects, error handling, or performance implications. For a tool with 8 parameters and no annotation coverage, this is insufficient.
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, compact sentence that efficiently conveys the core action and method. It's front-loaded with the main purpose and avoids unnecessary words. However, it could be slightly more structured by separating key concepts, but overall, it earns its place without waste.
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 complexity (8 parameters, no annotations, but with an output schema), the description is incomplete. It doesn't explain the parameters or their interactions, and while the output schema might cover return values, the description lacks context on the refresh process's scope, limitations, or integration with sibling tools. For a tool with significant input complexity, this leaves gaps in 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 0%, meaning none of the 8 parameters have descriptions in the schema. The tool description doesn't explain any parameters, such as 'sourceDir,' 'docsDir,' or 'maxFiles,' leaving their purposes and relationships unclear. With low coverage, the description fails to compensate, providing no semantic value beyond the schema.
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 states the tool 'refresh docs/mcp context files incrementally using workspace snapshot diff with deterministic output,' which provides a specific verb ('refresh') and resource ('docs/mcp context files'). However, it's somewhat vague about the exact mechanism ('workspace snapshot diff') and doesn't clearly distinguish this tool from siblings like 'analyze_current_file' or 'build_ai_context_index,' which might involve similar context management. It avoids tautology but 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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, exclusions, or specific scenarios for invocation. Given the many sibling tools related to project analysis and context management, this omission leaves the agent without clear usage cues, relying solely on the tool name and parameters.
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. While it mentions building a baseline and the goal of AI integration, it lacks critical details: what the tool actually does (e.g., analyzes files, generates reports), whether it modifies data or is read-only, what permissions are needed, error handling, or output format. For a tool with 9 parameters and no annotations, this is a significant gap in transparency.
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, well-structured sentence that efficiently conveys the core purpose without unnecessary words. It's front-loaded with the main action and goal, making it easy to parse. However, given the tool's complexity (9 parameters, no annotations), it might be overly concise, potentially omitting needed 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 tool's complexity (9 parameters, no annotations, but with an output schema), the description is incomplete. It lacks parameter explanations, behavioral details, and usage guidelines. While the output schema may cover return values, the description doesn't address what the tool does, how it interacts with inputs, or its operational context, making it inadequate for effective agent use.
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%, meaning none of the 9 parameters have descriptions in the schema. The tool description provides no information about any parameters—it doesn't mention sourceDir, intakePath, baselinePath, or other inputs. This leaves all parameters completely undocumented, failing to compensate for the schema's lack of 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 the tool's purpose: 'Build a technical baseline for legacy projects to guide high-quality AI integration with minimal context waste.' It specifies the action (build), resource (technical baseline for legacy projects), and goal (guide AI integration). However, it doesn't explicitly differentiate from sibling tools like 'prepare_legacy_project_for_ai' or 'collect_legacy_project_intake', which appear related to legacy project preparation.
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 mentions the goal of 'minimal context waste' but doesn't specify prerequisites, appropriate scenarios, or when other tools (e.g., 'prepare_legacy_project_for_ai') might be more suitable. This leaves the agent with insufficient context for decision-making.
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 mentions using 'local feedback metrics' and prioritizing for 'future recommendations,' which hints at a read-only analysis function, but fails to detail critical aspects like whether this operation is safe, requires specific permissions, affects data, has rate limits, or what the output entails. For a tool with 8 parameters and no annotations, this is a significant gap in transparency.
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 directly states the tool's purpose without unnecessary words. It is front-loaded with the core action ('rank project skills') and avoids redundancy, making it appropriately concise for its content.
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 tool's complexity (8 parameters, no annotations, but with an output schema), the description is minimally adequate. It clarifies the tool's purpose but lacks details on parameter usage, behavioral traits, and integration with siblings. The presence of an output schema mitigates the need to explain return values, but overall, the description is incomplete for effective agent use without additional context.
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%, meaning none of the 8 parameters are documented in the schema. The description does not mention any parameters, such as 'catalogPath' or 'metricsPath,' nor does it explain their roles, formats, or interactions. It adds no semantic value beyond the schema, failing to compensate for the low coverage, which is inadequate for a tool with this many inputs.
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 states the tool 'rank[s] project skills using local feedback metrics to prioritize reliable skills in future recommendations,' which provides a clear verb ('rank') and resource ('project skills') with a purpose ('prioritize reliable skills'). However, it does not explicitly differentiate this from sibling tools like 'rank_agent_packs' or 'recommend_project_agents,' leaving some ambiguity in its specific role within the toolset.
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 offers no guidance on when to use this tool versus alternatives, such as 'rank_agent_packs' or 'recommend_project_agents,' nor does it mention prerequisites, exclusions, or specific contexts. It implies usage for ranking based on feedback metrics but lacks explicit when/when-not instructions or named 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 carries full burden but offers minimal behavioral insight. It mentions generating artifacts and optional MCP config, but doesn't disclose critical traits like whether this is a read-only or destructive operation, permission requirements, rate limits, or what 'materialize' entails (e.g., file creation, configuration changes). The term 'materialize' suggests a write action, but specifics are lacking.
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 core purpose. It avoids redundancy and wastes no words, though it could be more informative given the tool's complexity. The structure is clear but under-specified.
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 tool with 34 parameters, 0% schema coverage, no annotations, and an output schema (which helps but isn't described), the description is inadequate. It doesn't explain the tool's behavior, parameter meanings, or interaction with siblings like 'recommend_project_agents'. The presence of an output schema mitigates some gaps, but the description fails to provide necessary context for effective use.
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% for 34 parameters, placing high burden on the description to explain them. The description mentions 'recommendations' and implies artifact generation, but doesn't clarify any parameters (e.g., what 'sourceDir', 'maxFiles', or boolean flags like 'includePackCatalog' mean). It adds minimal semantic value beyond the schema's structure.
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 ('materialize') and the target ('recommended agents'), specifying that it generates 'blueprint/guide/prompt and optional MCP config' as project artifacts. It distinguishes from siblings like 'recommend_project_agents' (which likely provides recommendations) and 'scaffold_project_agents' (which might create basic structures), but doesn't explicitly contrast with them.
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 explicit guidance on when to use this tool versus alternatives is provided. The description implies it follows recommendations (possibly from 'recommend_project_agents'), but doesn't state prerequisites, when to choose it over 'scaffold_project_agents' or 'apply_agent_pack', or any exclusions. Usage context 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions analysis and recommendation but lacks details on what 'project signals' entail, how recommendations are generated, whether this is a read-only or write operation, performance characteristics, or error handling. For a complex tool with 22 parameters, this is a significant gap in transparency.
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 core purpose. It avoids unnecessary words and gets straight to the point. However, given the tool's complexity and 22 undocumented parameters, this brevity might be insufficient rather than optimally 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 high complexity (22 parameters, 0% schema coverage, no annotations) and the presence of an output schema, the description is incomplete. It does not explain what 'project signals' are, how recommendations are structured, or the role of parameters. While the output schema may cover return values, the description lacks context for understanding the tool's operation and inputs, making it inadequate for such a multifaceted 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%, meaning none of the 22 parameters have descriptions in the schema. The tool description does not mention any parameters, their purposes, or how they influence the analysis and recommendations. It fails to compensate for the lack of schema documentation, leaving parameters like 'sourceDir', 'maxFiles', and various boolean flags unexplained.
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 purpose: 'Analyze project signals and recommend agent definitions with materialization-ready arguments.' It specifies the action (analyze and recommend) and the output (agent definitions with arguments). However, it doesn't explicitly differentiate from sibling tools like 'materialize_recommended_agents' or 'scaffold_project_agents', which appear related but have different functions.
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. With many sibling tools (e.g., 'materialize_recommended_agents', 'scaffold_project_agents', 'rank_agent_packs'), there is no indication of how this tool fits into the workflow or what scenarios warrant its use over others. Usage is implied only 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 provided, the description carries full burden. It mentions 'dry-run, preview, and rollback-safe patching' which gives some behavioral context about safety features, but doesn't disclose critical details like required permissions, whether this is a destructive operation, rate limits, or what happens to existing artifacts. For a complex upgrade tool with 15 parameters, this is insufficient.
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 core purpose. Every word contributes meaning, though it could potentially benefit from slightly more detail given 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?
For a complex upgrade tool with 15 parameters, no annotations, and 0% schema description coverage, the description is inadequate. While an output schema exists (which helps with return values), the description doesn't provide enough context about the tool's behavior, parameter usage, or relationship to sibling tools to enable effective agent selection and 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?
With 0% schema description coverage for 15 parameters, the description must compensate but provides no parameter information whatsoever. It doesn't explain what any of the 15 parameters mean, their relationships, or how they affect the upgrade process. The description mentions general capabilities ('dry-run, preview') but doesn't map them to specific 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 states the verb ('upgrade') and resource ('MCP-managed project artifacts') with specific scope ('to the latest layout version'). It doesn't explicitly differentiate from sibling tools like 'apply_project_patch' or 'rollback_project_patch', but the focus on 'layout version' provides some distinction.
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 mentions 'dry-run, preview, and rollback-safe patching' which implies usage contexts, but provides no explicit guidance on when to use this tool versus alternatives like 'apply_project_patch' or 'ensure_project_mcp_current'. No prerequisites, exclusions, or comparison to sibling tools are stated.
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 auditing and producing a migration plan but doesn't specify whether this is a read-only analysis, what permissions are required, if it modifies any data, or the format of the output. For a tool with potential migration implications, this is a significant gap in transparency.
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 core purpose. It avoids unnecessary words and gets straight to the point, though it could potentially benefit from slightly more detail given the complexity of the task.
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 tool's complexity (auditing and migration planning), the lack of annotations, and 0% schema description coverage, the description is incomplete. However, the presence of an output schema means the description doesn't need to explain return values, which slightly mitigates the gap. It adequately states the purpose but misses key behavioral and parameter details.
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, so the two parameters ('statePath' and 'includeLegacyScan') are undocumented in the schema. The description provides no information about these parameters—what they represent, their expected formats, or how they affect the audit. This leaves the agent guessing about parameter usage.
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 purpose with specific verbs ('audit', 'produce') and resources ('MCP project artifacts/layout version', 'migration plan'), making it easy to understand what the tool does. It distinguishes itself from siblings like 'upgrade_project_mcp' or 'ensure_project_mcp_current' by focusing on auditing and planning rather than execution, though it doesn't explicitly name these 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?
The description provides no guidance on when to use this tool versus alternatives like 'upgrade_project_mcp' or 'ensure_project_mcp_current', nor does it mention prerequisites or exclusions. It implies usage for migration planning but lacks explicit context for tool 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 full burden but offers limited behavioral insight. It hints at efficiency and quality but doesn't disclose critical traits like whether it's read-only or destructive, permission requirements, rate limits, or output format. The mention of 'token-efficient' and 'minimize redundant prompts' adds some context but is insufficient 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, well-structured sentence that efficiently conveys the core purpose without redundancy. It's front-loaded with key attributes and avoids unnecessary words, 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 high complexity (13 parameters, no annotations, but with output schema), the description is incomplete. It lacks parameter explanations, behavioral details, and usage context, though the output schema may cover return values. For a tool with many parameters and no annotations, more comprehensive guidance is needed.
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 but provides no parameter information. It doesn't explain the purpose of any of the 13 parameters (e.g., sourceDir, baselinePath, dryRun), leaving their semantics undocumented. This fails to add value beyond the bare 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 ('Build') and the resource ('context index for legacy projects'), with specific attributes like 'token-efficient' and 'quality-aware'. It distinguishes from siblings by focusing on indexing rather than analysis, generation, or validation, but doesn't explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance, mentioning 'legacy projects' and 'minimize redundant prompts' as context, but lacks explicit when-to-use rules, prerequisites, or comparisons to sibling tools like 'prepare_legacy_project_for_ai' or 'refresh_project_context_docs'. No exclusions or alternatives are specified.
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 full burden but offers limited behavioral insight. It mentions 'audit and upgrade' which implies read and write operations, but doesn't disclose critical traits like whether it's destructive, requires specific permissions, has side effects, or handles errors. The phrase 'automatically' hints at conditional execution, but lacks detail on triggers or 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?
The description is a single, well-constructed sentence that efficiently conveys the core purpose without redundancy. It's front-loaded with the main action and appropriately sized, with every word serving a clear function in explaining the tool's 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?
For a complex tool with 16 parameters, no annotations, and 0% schema description coverage, the description is inadequate. While an output schema exists, the description doesn't address the behavioral complexity, parameter meanings, or usage context needed for effective tool selection and invocation, given the lack of supporting structured data.
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 16 parameters and 0% schema description coverage, the description fails to compensate by explaining any parameters. It doesn't mention what 'autoApply', 'force', 'sourceDir', or other parameters mean, leaving all semantics undocumented. This is a significant gap given the high parameter count and lack of schema descriptions.
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 purpose with specific verbs ('audit and upgrade') and resources ('MCP project artifacts'), and specifies the target ('current managed layout'). It doesn't explicitly differentiate from sibling tools like 'upgrade_project_mcp' or 'audit_project_mcp_state', but the focus on automatic conditional execution ('when needed') provides some distinction.
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 minimal guidance with 'when needed', which is vague and doesn't specify conditions or alternatives. There's no mention of when to use this versus similar tools like 'upgrade_project_mcp' or 'audit_project_mcp_state', nor any prerequisites or exclusions, leaving the agent with little practical 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 provided, the description carries the full burden of behavioral disclosure. It mentions 'dry-run support' which hints at a preview capability, but doesn't explain what happens in dry-run versus actual execution, whether files are created/modified, what permissions are needed, or what the output looks like. For a complex scaffolding tool with 12 parameters that likely creates files, this is insufficient 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 extremely concise - a single sentence that efficiently communicates the core functionality. It's front-loaded with the main purpose and includes the key feature (dry-run support). There's no wasted verbiage or unnecessary elaboration.
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 (12 parameters with nested objects, no annotations, but has output schema), the description is inadequate. While the output schema may document return values, the description doesn't explain the tool's behavior, parameter meanings, or usage context. For a scaffolding tool that likely creates/modifies project files, more guidance is needed about its effects and appropriate use.
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 for 12 parameters (many with nested objects), the description provides almost no parameter guidance. It mentions 'dry-run support' which corresponds to the 'dryRun' parameter, but doesn't explain the other 11 parameters like 'featureName', 'namespace', 'manifestPath', 'allowOverwrite', or the complex 'routing' and 'i18n' objects. The description fails to compensate for the complete lack of schema descriptions.
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 purpose: 'Generate an end-to-end UI5 feature scaffold (view/controller/fragment/routing/i18n) with dry-run support.' It specifies the verb ('Generate'), resource ('UI5 feature scaffold'), and scope ('end-to-end' covering multiple components). However, it doesn't explicitly differentiate from sibling tools like generate_ui5_controller or generate_ui5_view_logic, which appear to handle individual components rather than comprehensive scaffolding.
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 mentions 'dry-run support' but doesn't explain when to use dry-run mode versus actual generation, or when this comprehensive scaffolding tool should be chosen over the more specific sibling tools (e.g., generate_ui5_controller for just a controller). There's no mention of prerequisites, dependencies, or typical use cases.
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 full burden for behavioral disclosure. While it mentions updating aggregate metrics, it doesn't describe whether this is a write operation (implied by 'record' and 'update'), what permissions might be required, whether changes are reversible, or how the update affects system state. For a tool with 17 parameters that appears to modify data, 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 extremely concise with a single sentence that efficiently communicates the core purpose. Every word earns its place, and there's no redundant or unnecessary information. The structure is front-loaded with the essential action and 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?
For a complex tool with 17 parameters, no annotations, and what appears to be a write operation that updates metrics, the description is insufficiently complete. While an output schema exists (which reduces the need to describe return values), the description doesn't address critical context like when this tool should be used, what the feedback impacts, or how it differs from the agent feedback sibling 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?
With 0% schema description coverage for 17 parameters, the description provides no information about any parameters beyond what's in the schema. The description doesn't explain what 'skillId' refers to, what the different 'outcome' values mean, how 'qualityGatePass' relates to execution, or the purpose of the many path parameters. This leaves substantial semantic gaps for the agent to interpret parameter meanings.
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 purpose with specific verbs ('record', 'update') and resources ('structured execution feedback for project skills', 'aggregate metrics'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from its sibling 'record_agent_execution_feedback', which appears to serve a similar feedback-recording function for agents rather than skills.
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. With a sibling tool 'record_agent_execution_feedback' that likely serves a parallel purpose for agents, the absence of any differentiation or usage context leaves the agent without clear decision criteria for selecting between these feedback-recording 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 provided, the description carries the full burden of behavioral disclosure. It mentions 'strict validation and fingerprinting', hinting at quality checks and uniqueness, but doesn't describe critical behaviors like whether it's a write operation (implied by 'save'), permission requirements, error handling, or what 'dryRun' and 'allowOverwrite' parameters do. For a tool with 11 parameters and no annotations, this is insufficient.
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 that front-loads the core action and key features ('strict validation and fingerprinting'). There is no wasted wording, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 (11 parameters, no annotations, but with an output schema), the description is incomplete. It doesn't explain parameter meanings, behavioral details like mutation effects or error cases, or how validation/fingerprinting work. The output schema helps with return values, but the description lacks sufficient context for safe and effective use.
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 undocumented parameters. It only vaguely references 'validation and fingerprinting', which might relate to some parameters like 'maxDiffLines' or 'reason', but doesn't explain any of the 11 parameters' purposes, such as 'blueprintPath' or 'packCatalogPath'. The description adds minimal value beyond 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 clearly states the action ('save') and resource ('generated agent artifacts into a reusable pack catalog'), specifying the purpose as saving artifacts with validation and fingerprinting. It distinguishes from siblings like 'list_agent_packs' or 'apply_agent_pack' by focusing on saving, but doesn't explicitly differentiate from 'promote_agent_pack' or 'scaffold_project_agents' in terms of when to use each.
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 'promote_agent_pack' or 'apply_agent_pack', nor does it mention prerequisites such as needing generated artifacts ready. The description implies usage for saving validated packs but lacks explicit 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 provided, the description carries full burden. It mentions 'safe' and 'preview' which implies non-destructive behavior, but doesn't disclose important details like permission requirements, rate limits, what makes it 'safe', or the actual behavioral impact. The description is too vague about the tool's operational characteristics.
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 communicates the core purpose. It's appropriately sized and front-loaded with the main action. However, it could be slightly more structured by separating purpose from output details.
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 tool with 3 parameters, no annotations, and an output schema, the description is minimally adequate. The presence of an output schema means return values don't need explanation, but the description should do more to explain parameter usage and behavioral context given the mutation-like nature of a 'write preview' 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?
With 0% schema description coverage for 3 parameters, the description adds minimal value. It mentions 'hashes, line summary, and textual diff preview' which hints at outputs but doesn't explain what 'path', 'content', or 'maxDiffLines' parameters mean or how they affect the preview. The description fails to compensate for the schema's lack of 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 purpose: 'Preview a safe workspace file write' with specific outputs (hashes, line summary, textual diff preview). It distinguishes from sibling 'read_project_file' by focusing on write preview rather than reading, though it doesn't explicitly differentiate from other write-related tools.
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 mentions 'safe workspace file write' but doesn't specify prerequisites, when to use this preview versus actual write operations, or how it relates to other file manipulation tools in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral context. It mentions 'actionable recommendations' which suggests the tool provides guidance rather than just diagnostics, but doesn't cover important aspects like whether it modifies files, requires specific permissions, has rate limits, or what the output format looks like (though an output schema exists).
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 that clearly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded with the core functionality.
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 3-parameter analysis tool with no annotations but with an output schema, the description provides basic purpose but lacks parameter guidance and behavioral context. The existence of an output schema reduces the need to describe return values, but the description should still address when to use this tool versus siblings and provide more parameter context given the 0% schema coverage.
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 for 3 parameters, the description provides no information about what 'sourceDir', 'maxFiles', or 'maxFindings' mean or how they affect the analysis. The description doesn't compensate for the complete lack of parameter documentation in 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 clearly states the tool analyzes UI5 XML/JS files with performance-focused rules and provides actionable recommendations. It specifies the resource (UI5 XML/JS files) and the focus (performance), but doesn't explicitly differentiate from sibling tools like 'analyze_ui5_project' or 'validate_ui5_code' which might have overlapping scopes.
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. With many sibling tools like 'analyze_ui5_project', 'validate_ui5_code', and 'run_project_quality_gate', there's no indication of when performance analysis is preferred over other types of analysis or validation.
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 'safe workspace file changes' and 'create rollback metadata', hinting at mutation with safety features, but lacks details on permissions, error handling, rate limits, or what 'safe' entails. This is inadequate for a mutation tool with zero 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, efficient sentence that front-loads the core action ('Apply one or more safe workspace file changes') and adds value with the rollback feature. There is no wasted verbiage, making it highly concise and well-structured.
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 tool's complexity (mutation with rollback), no annotations, and 0% schema coverage, the description is incomplete—it lacks behavioral details and parameter explanations. However, the presence of an output schema (implied by 'Has output schema: true') mitigates some gaps by likely documenting return values, keeping it at a baseline level.
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 by explaining parameters. It vaguely references 'changes' and 'rollback metadata', but doesn't clarify the structure of 'changes' (e.g., path, content, expectedOldHash) or the purpose of 'reason'. This leaves key semantics undocumented.
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 purpose with specific verbs ('apply', 'create') and resources ('workspace file changes', 'rollback metadata'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'write_project_file_preview' or 'rollback_project_patch', which would require a 5.
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 'write_project_file_preview' or 'rollback_project_patch', nor does it mention prerequisites or exclusions. It only states what the tool does, not when it should be selected.
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 but offers minimal information. It states what is generated but doesn't cover critical aspects like whether this creates new files, modifies existing ones, requires specific permissions, or has side effects. For a generation tool with zero annotation coverage, this is a significant gap in 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, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly, though it could benefit from additional context.
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 complexity of generating code modules, the lack of annotations, and the presence of an output schema (which may cover return values), the description is incomplete. It specifies the output type but misses details on behavior, parameters, and usage context. However, the output schema might mitigate some gaps, keeping it from being entirely inadequate.
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%, meaning the schema provides no descriptions for the two parameters. The tool description adds no parameter information beyond what's in the schema, failing to explain what 'formatterName' or 'functions' represent, their expected formats, or how they influence the output. This leaves parameters largely undocumented.
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 ('Generate') and the resource ('a formatter module that follows SAPUI5 module structure'), which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'generate_ui5_controller' or 'generate_ui5_view_logic' beyond the module type, leaving some ambiguity about when to choose this over other UI5 generation tools.
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 lacks context about prerequisites, such as needing an existing UI5 project, or comparisons to sibling tools like 'generate_ui5_controller' or 'generate_ui5_feature'. This leaves the agent without clear direction on appropriate usage scenarios.
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 the tool generates a 'skeleton' with 'proper namespaces,' implying a creation operation, but does not specify if this writes to a file, requires project context, or has any side effects. It lacks details on output format, error handling, or dependencies, leaving significant gaps for a tool that likely modifies project files.
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 that is front-loaded with the core purpose. There is no wasted wording, and it directly communicates the tool's function without unnecessary elaboration.
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 that an output schema exists, the description does not need to explain return values. However, with no annotations, 0% schema coverage, and 2 parameters, the description is too minimal for a tool that likely creates UI5 artifacts. It lacks context on integration with the project, behavioral traits, and parameter meanings, making it incomplete for effective use.
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%, meaning parameters are undocumented in the schema. The description does not mention any parameters or their semantics. It does not explain what 'fragmentName' or 'controls' represent, their expected formats, or how they influence the generated fragment. With 2 parameters and no schema descriptions, the description fails to compensate for this gap.
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 purpose: 'Generate an XML SAPUI5 fragment skeleton with proper namespaces.' It specifies the verb ('Generate'), resource ('XML SAPUI5 fragment skeleton'), and key constraint ('with proper namespaces'). However, it does not explicitly differentiate from sibling tools like 'generate_ui5_controller' or 'generate_ui5_view_logic', which likely generate different UI5 artifacts, so it misses full sibling distinction.
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 any prerequisites, context (e.g., when developing UI5 apps), or exclusions. Given sibling tools like 'generate_ui5_controller' and 'generate_ui5_view_logic', there is no explicit comparison or usage context provided.
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 the tool generates logic methods but does not explain what this entails—e.g., whether it creates new files, modifies existing ones, requires specific permissions, or handles errors. For a generation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and 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, efficient sentence that front-loads the core purpose without unnecessary words. It is appropriately sized for a straightforward tool, with zero waste or redundancy, making it easy to parse quickly.
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 that an output schema exists, the description does not need to explain return values. However, with no annotations, low parameter coverage, and a generation task that could involve file modifications, the description is incomplete. It lacks details on behavior, parameters, and usage context, though the output schema mitigates some gaps.
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%, meaning parameters are undocumented in the schema. The description does not mention any parameters or their semantics, such as what 'viewName' and 'events' represent or how they should be formatted. With two parameters and no compensation in the description, this is inadequate for guiding usage.
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 purpose: 'Generate UI5 view-controller event logic methods for XML views.' It specifies the verb ('Generate'), resource ('UI5 view-controller event logic methods'), and target ('XML views'), making it easy to understand. However, it does not explicitly differentiate from sibling tools like 'generate_ui5_controller' or 'generate_ui5_feature', which might have overlapping or related functions.
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 lacks context on prerequisites, such as needing an existing UI5 project or XML view, and does not mention sibling tools like 'generate_ui5_controller' or 'generate_ui5_feature' that might be relevant for similar tasks. Usage is implied but not explicitly stated.
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 mentions ranking based on 'execution feedback metrics' but doesn't disclose behavioral traits like whether this is a read-only operation, what permissions are needed, how ranking is calculated, whether it's resource-intensive, or what the output format looks like. For a tool with 9 parameters and no annotation coverage, this 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that efficiently conveys core purpose without waste. Every word earns its place, and the structure is front-loaded with the main action and resource.
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 tool's complexity (9 parameters, no annotations, but has output schema), the description is incomplete. The output schema existence means return values don't need explanation, but the description fails to address parameter meanings, behavioral context, or usage guidelines. It's minimally adequate for purpose but leaves critical gaps for proper tool selection and 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 for all 9 undocumented parameters. The description only vaguely references 'execution feedback metrics' and 'current context', which doesn't explain parameters like packCatalogPath, metricsPath, policyPath, respectPolicy, projectType, minExecutions, maxResults, includeUnscored, or includeDeprecated. It adds minimal semantic value beyond the bare 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 ('rank') and resource ('saved agent packs') with the mechanism ('using execution feedback metrics') and goal ('to prioritize recommendations for the current context'). It distinguishes from siblings like 'list_agent_packs' by emphasizing ranking rather than listing, but doesn't explicitly contrast with 'recommend_project_agents' which might have overlapping purpose.
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 explicit guidance on when to use this tool versus alternatives like 'recommend_project_agents' or 'materialize_recommended_agents'. The description mentions 'current context' but doesn't specify what contexts trigger usage or prerequisites. Usage is implied rather than explicitly 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 full burden for behavioral disclosure. It mentions 'safely with project-root sandboxing' which hints at security boundaries, but doesn't describe what 'safely' entails, whether there are rate limits, authentication requirements, file size constraints beyond maxChars, or what happens with invalid paths. The description provides minimal behavioral context for a file reading 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 extremely concise at just 8 words, front-loading the core purpose ('Read a workspace file') and adding one qualifying phrase ('safely with project-root sandboxing'). Every word serves a purpose with zero redundancy or unnecessary elaboration.
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 that there's an output schema (which should document return values), no annotations, and only 2 parameters, the description provides basic context about the operation's safety boundaries. However, for a file reading tool with completely undocumented parameters, it should ideally explain path semantics and character limit implications 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?
With 0% schema description coverage for both parameters, the description provides no information about what 'path' or 'maxChars' mean. It doesn't explain path format (relative/absolute), what 'maxChars' controls, or default behaviors. The description fails to compensate for the complete lack of schema 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 action ('Read') and resource ('workspace file'), making the purpose immediately understandable. It distinguishes this tool from siblings like 'write_project_file_preview' by focusing on reading rather than writing, but doesn't explicitly differentiate from 'search_project_files' which might also involve reading operations.
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 mentions 'safely with project-root sandboxing' which provides some context about security boundaries, but offers no explicit guidance on when to use this tool versus alternatives like 'search_project_files' or 'analyze_current_file'. There's no mention of prerequisites, limitations, or specific scenarios where this tool is preferred.
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 logging to 'local JSONL log' and updating 'aggregate pack metrics', which gives some context about data persistence and aggregation. However, it lacks details on permissions needed, rate limits, error handling, or whether this is a write operation (implied but not 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, efficient sentence that front-loads the core purpose ('Record agent execution feedback') and adds necessary context about the dual actions (logging and metrics). Every word earns its place with no 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?
Given the high complexity (20 parameters, 0% schema coverage) and no annotations, the description is incomplete. It lacks parameter explanations, behavioral details (e.g., side effects, error cases), and while an output schema exists, the description doesn't address the tool's overall context adequately for such a parameter-rich tool.
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 description provides no information about any of the 20 parameters, despite 0% schema description coverage. It doesn't explain what 'packSlug', 'outcome', 'dryRun', or other parameters mean, leaving the agent to rely solely on the schema's structural definitions without semantic context.
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 specific action ('Record') and resource ('agent execution feedback'), and distinguishes it from sibling tools by specifying it's for logging and metrics updates. It's not a tautology of the name/title as it adds context about the purpose ('for future ranking and promotion').
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 doesn't mention prerequisites, timing, or differentiate from similar tools like 'record_skill_execution_feedback' in the sibling list. The context is implied but 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool searches MDN documentation but doesn't describe how results are returned (e.g., format, pagination), error handling, rate limits, or authentication needs. For a search tool with complex parameters like cache settings and timeout, this 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to understand at a glance.
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 tool's moderate complexity (4 parameters with nested objects) and the presence of an output schema, the description is minimally adequate. The output schema likely covers return values, reducing the need for description details. However, with no annotations and 0% schema description coverage, the description should do more to explain parameter usage and behavioral context.
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 schema provides no parameter descriptions. The tool description mentions none of the 4 parameters (query, maxResults, timeoutMs, cache), leaving their purposes and usage completely undocumented. The description doesn't compensate for the schema's lack of 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 purpose: 'Search MDN documentation for JavaScript and web platform references.' It specifies the action (search), target resource (MDN documentation), and scope (JavaScript and web platform references). However, it doesn't explicitly differentiate from sibling tools like 'search_project_files' or 'search_ui5_sdk', which search different resources.
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 doesn't mention any prerequisites, exclusions, or comparisons with sibling tools like 'search_project_files' or 'search_ui5_sdk'. The agent must infer usage from the description 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?
No annotations are provided, so the description carries full burden. It mentions returning 'summaries with examples' which gives some behavioral context, but doesn't disclose important traits like whether this is a read-only operation, potential rate limits, authentication requirements, or how results are structured. The description is minimal and lacks 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, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized and front-loaded with the essential information about what the tool does.
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 tool has an output schema (which reduces the need to describe return values) but no annotations and poor schema description coverage, the description is incomplete. It covers the basic purpose but lacks parameter guidance, behavioral context, and sibling differentiation needed for a search tool with complex 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?
With 0% schema description coverage and 4 parameters (including a complex nested cache object), the description provides no parameter information. It doesn't mention the query parameter, maxResults, timeoutMs, or cache options, leaving all parameter semantics undocumented in both schema and description.
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 searches SAPUI5 SDK metadata and returns API/topic summaries with examples. It specifies the resource (SAPUI5 SDK metadata) and the action (search), but doesn't differentiate from sibling tools like search_mdn or search_project_files beyond the target resource.
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 search_mdn or search_project_files. The description implies usage for SAPUI5-specific searches but doesn't explicitly state when this tool is preferred over other search 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. It states the tool validates for 'consistency, tool coverage, and MCP integration readiness,' which implies a read-only analysis, but doesn't disclose behavioral traits like whether it modifies files, requires specific permissions, has side effects, or provides detailed error reporting. For a validation tool with 5 parameters, this is insufficient to inform safe and effective use.
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 that front-loads the core purpose without fluff. Every word contributes directly to explaining what the tool does, making it appropriately sized and well-structured for quick comprehension.
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 tool's complexity (5 parameters, validation focus) and the presence of an output schema (which handles return values), the description is minimally adequate but incomplete. It lacks parameter details, usage context, and behavioral disclosures, which are critical for a validation tool in a server with many siblings. The output schema mitigates some gaps, but overall completeness is limited.
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%, meaning none of the 5 parameters have descriptions in the schema. The tool description adds no parameter semantics—it doesn't explain what 'blueprintPath', 'agentsGuidePath', etc., represent, their formats, or how they interact. This leaves parameters undocumented, failing to compensate for the schema gap.
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 purpose: 'Validate generated agent blueprint and guardrail artifacts for consistency, tool coverage, and MCP integration readiness.' It specifies the verb ('validate') and the resources ('agent blueprint and guardrail artifacts'), and outlines the validation criteria. However, it doesn't explicitly differentiate from sibling tools like 'validate_project_skills' or 'validate_ui5_code', which reduces clarity in a crowded toolset.
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 doesn't mention prerequisites, timing (e.g., after generation steps), or exclusions. With many sibling tools for validation and analysis, the lack of contextual usage hints leaves the agent guessing about appropriate scenarios.
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. While 'validate' implies a read-only check, the description doesn't clarify whether this tool makes changes, requires specific permissions, has side effects, or what happens on validation failure. It mentions three validation aspects but doesn't explain what 'integrity', 'references', or 'consistency' entail behaviorally. For a tool with zero annotation coverage, this leaves significant gaps.
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 that front-loads the core purpose without unnecessary words. Every phrase ('validate project skill catalog integrity, official references, and file layout consistency') directly contributes to understanding the tool's scope. There's zero waste or redundancy.
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 that an output schema exists, the description doesn't need to explain return values. However, with 2 parameters, 0% schema coverage, and no annotations, the description is incomplete—it doesn't address parameter meanings, behavioral details, or usage context. The presence of an output schema slightly mitigates this, but the overall context remains under-specified for a validation tool with 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 0%, meaning neither parameter (catalogPath, strict) is documented in the schema. The description adds no parameter information—it doesn't explain what catalogPath refers to, what 'strict' mode does, or how these parameters affect validation. With 2 parameters and no schema descriptions, the description fails to compensate, leaving parameters semantically 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's purpose as validating three specific aspects of a project skill catalog: integrity, official references, and file layout consistency. It uses the specific verb 'validate' with the resource 'project skill catalog', making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'validate_project_agents' or 'validate_ui5_code', which would be needed for 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?
The description provides no guidance on when to use this tool versus alternatives. With multiple validation-related sibling tools (e.g., validate_project_agents, validate_ui5_code), there's no indication of the specific context for this validation tool, nor any prerequisites or exclusions mentioned. The agent must infer usage from the tool 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool validates but doesn't describe behavioral traits like whether it's read-only (implied by 'validate'), what the output contains, error handling, performance implications, or any side effects. For a validation tool with zero annotation coverage, this leaves significant gaps in understanding how it operates.
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 that front-loads the core purpose without unnecessary words. Every part ('Validate SAPUI5 code for...') directly contributes to understanding the tool's function, making it appropriately sized and well-structured for quick comprehension.
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 tool's complexity (validating multiple UI5 aspects), no annotations, and an output schema (which exists but isn't provided here), the description is minimally complete. It specifies what is validated but lacks details on behavior, parameters, and usage context. The output schema might cover return values, but the description doesn't bridge other gaps, making it adequate but with clear room for improvement.
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 schema provides no parameter documentation. The description adds no information about parameters beyond what's inferred from the tool name (e.g., 'code' is likely the UI5 code to validate). It doesn't explain the purpose of 'expectedControllerName' or 'sourceType', their formats, or how they affect validation. With 3 parameters and no schema descriptions, the description fails to compensate adequately.
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 purpose: 'Validate SAPUI5 code for sap.ui.define usage, dependency order, naming, and MVC separation.' It specifies the verb (validate) and resource (SAPUI5 code) with concrete validation aspects. However, it doesn't explicitly distinguish from siblings like 'validate_ui5_odata_usage' or 'validate_ui5_version_compatibility', which focus on different validation aspects.
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 doesn't mention when validation is needed (e.g., during development, before deployment), prerequisites, or how it differs from siblings like 'lint_javascript_code' or 'security_check_ui5_app'. Without such context, users must infer usage from the tool name alone.
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 provided, the description carries the full burden of behavioral disclosure. It mentions 'idempotent updates' (a valuable behavioral trait) and 'optional dry-run' (indicating a testing mode), which helps understand the tool's behavior. However, it doesn't cover important aspects like required permissions, whether changes are destructive, error handling, rate limits, or what the synchronization actually entails beyond the high-level mention.
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 extremely concise - a single sentence that efficiently communicates the core purpose and key features. Every word earns its place: 'synchronize' (action), 'manifest.json models, routes, and targets' (scope), 'idempotent updates' (behavioral trait), and 'optional dry-run' (feature). There's no wasted verbiage or redundant 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?
For a complex mutation tool with 5 parameters (including nested objects), 0% schema description coverage, and no annotations, the description is insufficient. While an output schema exists (which helps), the description doesn't adequately explain what synchronization entails, what the parameters mean, or the behavioral implications of this write operation. Given the complexity and lack of structured documentation, the description should provide more context about what gets updated and how.
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 5 parameters (including a complex nested 'changes' object), the description provides almost no parameter information. It mentions 'optional dry-run' which corresponds to the 'dryRun' parameter, but doesn't explain the purpose of 'manifestPath', 'reason', 'maxDiffLines', or the structure and semantics of the 'changes' object. The description fails to compensate for the complete lack of schema descriptions.
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 ('synchronize') and target ('manifest.json models, routes, and targets'), making the purpose understandable. It distinguishes from siblings by focusing on manifest synchronization rather than analysis, generation, or validation tasks. However, it doesn't explicitly differentiate from potential similar tools like 'upgrade_project_mcp' or 'ensure_project_mcp_current' that might also involve manifest updates.
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 doesn't mention prerequisites, when not to use it, or how it relates to sibling tools like 'upgrade_project_mcp', 'ensure_project_mcp_current', or 'apply_project_patch' that might involve similar operations. The mention of 'optional dry-run' hints at testing scenarios but doesn't constitute proper usage guidelines.
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 states the analysis scope but doesn't disclose behavioral traits such as whether it's read-only (likely, but not confirmed), what happens if the file doesn't exist, if there are rate limits, or what the output format is. The description adds minimal context beyond the basic action, leaving key operational details unspecified.
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 that front-loads the core action ('analyze the current file') and specifies key aspects without waste. Every word contributes to understanding the tool's purpose, making it appropriately sized and well-structured for quick comprehension.
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 1 parameter with no schema descriptions and an output schema present, the description is minimally adequate. It covers the analysis scope but lacks details on behavioral traits (e.g., error handling) and parameter usage. The output schema mitigates the need to explain return values, but for a tool with no annotations and incomplete parameter documentation, more context would improve completeness.
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 input schema has 1 parameter with 0% description coverage, so the description must compensate. It mentions 'current file' but doesn't explain the 'path' parameter's semantics (e.g., relative vs. absolute path, file type expectations). The description adds some meaning by implying file analysis, but it doesn't fully clarify parameter usage, resulting in a baseline score due to incomplete compensation.
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 verb 'analyze' and the resource 'current file', specifying what aspects are analyzed: imports, class structure, and controller methods. It distinguishes from siblings like 'analyze_ui5_performance' or 'analyze_legacy_project_baseline' by focusing on file-level structural analysis rather than performance or project-wide analysis. However, it doesn't explicitly contrast with 'read_project_file' or 'validate_ui5_code', which slightly limits 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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., file must exist), exclusions (e.g., not for non-code files), or comparisons to siblings like 'read_project_file' (for raw content) or 'validate_ui5_code' (for validation). Usage is implied from the name and description but not explicitly stated.
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 full burden for behavioral disclosure. It mentions ES2022 standard and JSDoc inclusion, which are useful behavioral details. However, it doesn't address critical aspects like: whether this creates new files or returns code strings, what permissions are needed, error handling behavior, or any rate limits. For a code generation tool with zero annotation coverage, this leaves significant gaps.
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 extremely concise - a single sentence that efficiently communicates the core functionality. Every word earns its place: 'Generate' (action), 'ES2022 JavaScript or TypeScript function' (what), 'with JSDoc' (additional feature), 'for browser or Node runtime' (context). There's no wasted verbiage or redundancy.
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 tool has an output schema (which presumably documents the return format), the description doesn't need to explain return values. However, for a code generation tool with 3 parameters and no annotations, the description is somewhat minimal. It covers the basic purpose and runtime context but lacks information about behavioral constraints, error conditions, or detailed parameter guidance that would make it more complete.
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 schema provides no parameter documentation. The description doesn't mention any of the three parameters (description, runtime, typescript) explicitly. However, it implies the 'runtime' parameter by mentioning 'browser or Node runtime' and hints at 'typescript' by including TypeScript in the scope. This provides some semantic context but doesn't fully compensate for the complete lack of parameter documentation in 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 clearly states the tool's purpose: generating JavaScript/TypeScript functions with JSDoc for specific runtimes. It specifies the verb 'generate' and resource 'function', and distinguishes from siblings like 'refactor_javascript_code' or 'lint_javascript_code' by focusing on creation rather than modification or analysis. However, it doesn't explicitly differentiate from other generate_* tools like 'generate_ui5_controller', leaving some 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 minimal usage guidance. It mentions 'browser or Node runtime' which gives some context, but offers no explicit guidance on when to use this tool versus alternatives like 'refactor_javascript_code' for modifying existing code or 'generate_ui5_controller' for UI5-specific generation. There are no when-not-to-use statements or prerequisite information.
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 mentions generating a 'skeleton' but doesn't disclose behavioral traits like whether this creates a new file, overwrites existing ones, requires specific project setup, or handles errors. For a generation tool with zero annotation coverage, this is insufficient.
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 that front-loads the key action and resource. It avoids redundancy and wastes no words, making it highly concise and well-structured for quick comprehension.
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 tool's moderate complexity (generation with 2 parameters), no annotations, and an output schema (which handles return values), the description is minimally complete. It states what is generated but lacks details on behavior, parameters, and usage context, making it adequate but with clear gaps.
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 schema provides no parameter details. The description doesn't explain the parameters 'controllerName' or 'methods', leaving their semantics unclear. However, with only 2 parameters and a baseline expectation, it minimally meets adequacy without adding meaningful context beyond 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 clearly states the action ('Generate') and the resource ('SAPUI5 controller skeleton with lifecycle hooks and JSDoc'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'generate_ui5_view_logic' or 'generate_ui5_fragment', which might also generate UI5 components, so it misses full sibling distinction.
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 other 'generate_ui5_' siblings or related tools like 'scaffold_ui5_odata_feature'. It lacks context on prerequisites, typical scenarios, or exclusions, leaving the agent without 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool performs 'ESLint-style static checks' and returns 'warnings plus suggested fixes', which implies a read-only analysis operation. However, it doesn't disclose critical behavioral traits such as whether it modifies the input code, requires specific configurations, has rate limits, or handles errors. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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, well-structured sentence: 'Run ESLint-style static checks and return warnings plus suggested fixes.' It efficiently conveys the core functionality without unnecessary details. Every word earns its place, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (static analysis with 1 parameter), no annotations, and an output schema (which should document return values), the description is minimally adequate. It states what the tool does but lacks details on behavioral traits, parameter semantics, and usage guidelines. The presence of an output schema reduces the need to explain return values, but other gaps remain, making it incomplete for optimal agent understanding.
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 input schema has 1 parameter ('code') with 0% description coverage, meaning the schema provides no semantic context. The description doesn't add any parameter-specific information beyond implying the tool analyzes JavaScript code. It doesn't explain the 'code' parameter's expected format, constraints, or examples. With low schema coverage, the description fails to compensate adequately, resulting in a baseline score.
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 purpose: 'Run ESLint-style static checks and return warnings plus suggested fixes.' It specifies the action ('Run... static checks'), the target ('javascript code'), and the output format ('warnings plus suggested fixes'). However, it doesn't explicitly differentiate from sibling tools like 'validate_javascript_code' or 'security_check_javascript' that might also analyze JavaScript code.
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 doesn't mention sibling tools like 'validate_javascript_code' or 'security_check_javascript', nor does it specify prerequisites, appropriate contexts, or exclusions. The agent must infer usage from the tool name and description 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 provided, the description carries the full burden of behavioral disclosure. It states 'List saved reusable agent packs from catalog,' which implies a read-only operation but doesn't confirm safety, permissions required, pagination, rate limits, or what 'saved' entails. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
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 zero waste—'List saved reusable agent packs from catalog.' It's front-loaded with the core action and resource, making it easy to parse quickly without unnecessary details.
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 tool's low complexity (1 parameter, no annotations, but has an output schema), the description is minimally adequate. The output schema likely covers return values, so the description doesn't need to explain those. However, for a listing tool with no behavioral context or parameter guidance, it leaves the agent with incomplete information, scoring as the minimum 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?
The input schema has 1 parameter with 0% description coverage, and the tool description adds no information about parameters. Since schema_description_coverage is low (<50%), the description fails to compensate by explaining 'packCatalogPath' or its role. With 0 parameters documented in the description, the baseline is 4, but the lack of any parameter context reduces it to 3, as it doesn't add value beyond 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 clearly states the verb ('List') and resource ('saved reusable agent packs from catalog'), making the purpose immediately understandable. It distinguishes itself from siblings like 'rank_agent_packs' or 'apply_agent_pack' by focusing on listing rather than ranking or applying. However, it doesn't specify the scope (e.g., all packs vs. filtered) or format, keeping it from 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 'rank_agent_packs' or 'materialize_recommended_agents'. The description implies usage for viewing saved packs but doesn't mention prerequisites, context, or exclusions, leaving the agent to infer based on tool names 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 provided, the description carries the full burden of behavioral disclosure. It mentions the diagnostic components but lacks details on permissions, side effects, rate limits, or output format. While it implies a read-only operation ('Return'), it doesn't confirm safety or describe potential impacts, leaving significant gaps for a tool with 12 parameters.
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 that front-loads the core purpose and enumerates key components without waste. Every word contributes to understanding the tool's scope, making it appropriately sized and well-structured for quick comprehension.
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 tool's complexity (12 parameters, no annotations, but with an output schema), the description is minimally adequate. It outlines the diagnostic scope but lacks details on behavior, parameter usage, or integration with siblings. The output schema may cover return values, but the description doesn't address operational context or error handling, leaving 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?
Schema description coverage is 0%, so the description must compensate. It lists diagnostic components (e.g., tool exposure, docs alignment) that map to some parameters (like includeToolNames, includeDocChecks), adding meaning beyond the bare schema. However, it doesn't cover all 12 parameters (e.g., referenceDocPath, examplesDocPath) or explain their relationships, providing partial but incomplete semantic 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 tool's purpose with a specific verb ('Return') and resource ('MCP server/runtime health diagnostics'), listing the diagnostic components (tool exposure, docs alignment, contract snapshot, managed artifact status). It distinguishes from most sibling tools focused on analysis, generation, or project management, though not explicitly contrasting with any specific health-related 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, prerequisites, or typical scenarios. It merely states what the tool does without indicating context like troubleshooting, monitoring, or setup verification, leaving the agent to infer usage from the purpose 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?
No annotations are provided, so the description carries the full burden. It mentions the action ('refactor') and goals ('modern syntax', 'preserving readability') but lacks critical behavioral details: it doesn't specify if this is a read-only or mutating operation, what permissions are needed, how errors are handled, or any rate limits. For a code transformation tool with zero annotation coverage, this is a significant gap in 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, efficient sentence that front-loads the core action ('refactor JavaScript code') and adds qualifying goals without waste. Every word earns its place, making it easy to parse quickly.
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 tool's complexity (code refactoring), lack of annotations, and an output schema (which covers return values), the description is minimally adequate. It states what the tool does but misses key contextual details like behavioral traits, parameter explanations, and usage guidelines. The output schema mitigates some gaps, but overall completeness is limited.
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 input schema has 1 parameter with 0% description coverage, so the schema provides no semantic context. The description doesn't mention the 'code' parameter at all, failing to compensate for the schema gap. However, with only one parameter, the baseline is higher; the tool's purpose implies the parameter is JavaScript code to refactor, but this is inferred rather than explicitly stated.
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 verb ('refactor') and resource ('JavaScript code') with specific goals ('using modern syntax while preserving readability'). It distinguishes from siblings like 'lint_javascript_code' (which likely focuses on style/errors) and 'generate_javascript_function' (which creates new code). However, it doesn't explicitly differentiate from all siblings, such as 'validate_javascript_code' which might overlap in scope.
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 explicit guidance on when to use this tool versus alternatives like 'lint_javascript_code' or 'validate_javascript_code' is provided. The description implies usage for modernizing code but doesn't specify prerequisites, constraints, or exclusions. This leaves the agent to infer context from sibling names 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?
No annotations are provided, so the description carries full burden. It states the tool uses 'stored backup metadata,' hinting at data retrieval, but doesn't disclose critical behavioral traits: whether this is destructive (likely yes, as rollbacks typically modify state), permission requirements, error conditions, or side effects. The description is minimal and leaves key operational aspects unspecified.
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 zero wasted words. It front-loads the core action and resource, making it immediately understandable. Every element ('rollback,' 'previously applied patch,' 'stored backup metadata') earns its place by contributing essential context without redundancy.
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 tool's complexity (a mutation operation with no annotations) and the presence of an output schema (which may cover return values), the description is minimally adequate. It specifies the action and hints at mechanism but lacks details on behavior, safety, or integration with siblings. It meets a basic threshold but has clear gaps in guidance and transparency.
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%, with one parameter ('patchId') undocumented in the schema. The description adds minimal semantics by implying 'patchId' refers to a 'previously applied patch,' but doesn't clarify format, source, or constraints. It partially compensates for the coverage gap but remains vague, aligning with the baseline expectation when schema provides little detail.
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 ('rollback') and target resource ('a previously applied patch') using specific verbs and nouns. It distinguishes from siblings like 'apply_project_patch' by indicating reversal rather than application. However, it doesn't explicitly contrast with other potential rollback or patch-related tools beyond the obvious sibling.
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 doesn't mention prerequisites (e.g., needing a stored backup), exclusions, or contextual triggers. While 'previously applied patch' implies a prior action, it lacks explicit usage criteria or comparisons to other tools in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 states the tool searches files but doesn't disclose behavioral traits like whether it searches content or metadata, performance characteristics, pagination (implied by maxResults but not explained), authentication needs, or error conditions. This leaves significant gaps for a search 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, efficient sentence that front-loads the core purpose ('Search workspace files') and adds key details ('by text query with optional extension filtering'). There is no wasted verbiage, 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, no annotations), the description is minimally adequate but has clear gaps. It covers the basic purpose and hints at parameters, but lacks behavioral details and usage context. The presence of an output schema helps, but the description doesn't fully compensate for missing annotations and low schema coverage.
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 schema provides no parameter descriptions. The description adds minimal semantics by mentioning 'text query' (mapping to 'query') and 'optional extension filtering' (mapping to 'extensions'), but doesn't explain 'maxResults' or provide details like query syntax or extension format. It partially compensates but not fully.
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 ('search') and resource ('workspace files'), with specific filtering capabilities ('by text query with optional extension filtering'). However, it doesn't explicitly differentiate from sibling tools like 'read_project_file' or 'search_mdn', which reduces it from 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. The description mentions 'optional extension filtering' but doesn't specify when this is useful or compare it to other search or file-access tools in the sibling list, leaving the agent without contextual 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 provided, the description carries the full burden of behavioral disclosure. It states what the tool does but does not explain how it behaves—e.g., whether it's read-only, what output format to expect, if it has side effects, or any constraints like rate limits. This leaves significant gaps in understanding the tool's 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, efficient sentence that directly states the tool's purpose without any fluff or redundancy. It is front-loaded and appropriately sized, making it easy to understand quickly.
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 tool has 0 parameters, 100% schema coverage, and an output schema exists, the description is minimally adequate. However, it lacks details on behavioral aspects (e.g., output format, side effects) and usage context, which are important for a tool that analyzes project configurations, leaving room for improvement.
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 has 0 parameters with 100% coverage, so no parameter information is needed. The description does not mention parameters, which is appropriate, earning a baseline score of 4 for not adding unnecessary details beyond 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 clearly states the action ('analyze') and the target ('SAPUI5 project configuration from ui5.yaml, manifest.json, and package.json'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'analyze_current_file' or 'analyze_ui5_performance', which reduces the score from a perfect 5.
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 'analyze_current_file' for single files or 'analyze_ui5_performance' for performance analysis. It lacks explicit context, prerequisites, or exclusions, leaving usage unclear.
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 'fingerprint verification' and 'scaffolded materialization', which hint at security and setup processes, but doesn't detail what 'apply' entails operationally—such as whether it modifies project files, requires specific permissions, or has side effects. This leaves significant gaps in understanding 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, efficient sentence that front-loads the core action ('apply a saved agent pack') and adds key qualifiers ('with fingerprint verification and scaffolded materialization') without unnecessary elaboration. Every word contributes to understanding, making it optimally concise.
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 tool has 0 parameters, 100% schema coverage, and an output schema exists, the description's job is simplified. It adequately explains what the tool does but lacks details on behavioral aspects like effects on the project or error handling. With no annotations, it should provide more context about the 'apply' operation's impact, but the presence of an output schema mitigates some need for return value explanation.
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 has 0 parameters with 100% coverage, meaning no parameters are documented. The description doesn't need to compensate for missing param info, as there are none to explain. It appropriately focuses on the tool's purpose without redundant parameter details, earning a high baseline score.
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 ('apply') and resource ('saved agent pack'), and specifies the target ('to the current project') with additional context about verification and materialization. However, it doesn't explicitly differentiate from sibling tools like 'list_agent_packs' or 'save_agent_pack' in terms of when to use each, which prevents 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?
The description provides no guidance on when to use this tool versus alternatives like 'list_agent_packs' or 'save_agent_pack', nor does it mention prerequisites or exclusions. It implies usage through context but lacks explicit instructions, leaving the agent to infer based on the action 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?
No annotations are provided, so the description carries the full burden. It mentions what the tool checks but doesn't disclose behavioral traits such as whether it's read-only or mutative, execution time, permissions required, or output format. The description adds minimal context beyond the action, leaving gaps in understanding how the tool behaves operationally.
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 that front-loads the core action and lists specific checks without unnecessary words. Every part earns its place by clarifying the scope of the quality gate. It is appropriately sized for a tool with no parameters.
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 tool has no input parameters, an output schema exists, and no annotations are provided, the description is minimally adequate. It states the purpose and aspects checked, but lacks details on behavioral context (e.g., execution impact, result format) that would be helpful for an agent. The output schema likely covers return values, so the description doesn't need to explain those, but overall completeness is moderate due to missing operational guidance.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not add parameter information, which is appropriate. Baseline is 4 as per rules for 0 parameters, as the schema fully covers the absence of inputs.
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 ('Run consolidated quality gate') and the target ('UI5 projects'), with specific aspects checked (version compatibility, security, performance, OData usage, context docs freshness). It distinguishes from siblings by focusing on a comprehensive quality assessment rather than specific analyses like 'analyze_ui5_performance' or 'validate_ui5_version_compatibility'. However, it does not explicitly differentiate from all siblings (e.g., 'audit_project_mcp_state' might overlap in scope).
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 explicit guidance on when to use this tool versus alternatives is provided. The description implies it's for quality assessment of UI5 projects, but it doesn't specify prerequisites, timing (e.g., after changes), or contrast with siblings like 'analyze_ui5_project' or 'validate_ui5_code'. Usage is implied by the purpose, but no exclusions or alternatives 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 full burden but lacks behavioral details. It mentions validation and recommendations, but doesn't disclose whether this is read-only, requires specific permissions, affects project state, or has rate limits. The example (dedicated date controls) adds minimal context but insufficient for a mutation-aware 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, efficient sentence that front-loads the core purpose (validation and recommendations) with a concrete example. Every word contributes value without waste, making it easy to parse quickly.
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 0 parameters and an output schema exists, the description covers the basic purpose adequately. However, as a validation tool with no annotations, it lacks details on behavioral traits (e.g., safety, side effects) and doesn't leverage the output schema to hint at return values, leaving gaps in completeness.
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 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description doesn't add param info, which is appropriate, earning a baseline 4 for not introducing confusion or redundancy.
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 purpose: validating UI5 control/module compatibility against a project version and recommending better-fit components. It specifies the verb (validate) and resource (UI5 control/module compatibility), but doesn't explicitly differentiate from siblings like 'validate_ui5_code' or 'validate_ui5_odata_usage' beyond the compatibility focus.
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 mentions recommending components (e.g., dedicated date controls), but doesn't specify prerequisites, ideal scenarios, or exclusions compared to sibling tools like 'analyze_ui5_project' or 'validate_ui5_code'.
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 the tool analyzes metadata and returns specific components, but lacks details on error handling, performance characteristics, authentication needs, rate limits, or whether it's read-only or mutative. For a tool with zero annotation coverage, this is a significant gap in 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, efficient sentence that front-loads the core action ('analyze OData V2/V4 metadata') and clearly lists both input sources and output components. There is no wasted verbiage, and every part of the sentence contributes essential information.
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 has 0 parameters, 100% schema coverage, and an output schema exists, the description is reasonably complete. It specifies input sources and output components, which are crucial for understanding. However, without annotations, it could benefit from more behavioral context (e.g., read-only nature, error cases), though the output schema may cover 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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by specifying the sources (XML, file, URL, service root) from which metadata is analyzed, which compensates for the lack of parameters in the schema, providing useful context for the agent.
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 analyzes OData V2/V4 metadata from various sources (XML, file, URL, service root) and returns specific components (entities, properties, navigation, operations). It uses a specific verb ('analyze') and resource ('OData metadata'), but does not explicitly differentiate from sibling tools like 'validate_ui5_odata_usage' or 'scaffold_ui5_odata_feature', which may have overlapping domains.
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 lists input sources and output components, but does not mention prerequisites, typical scenarios, or comparisons with sibling tools like 'validate_ui5_odata_usage' or 'analyze_current_file', leaving the agent to 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 provided, the description carries the full burden of behavioral disclosure. It mentions a 'safe preview/apply patch flow', hinting at non-destructive previews and controlled application, but lacks details on permissions needed, rate limits, error handling, or what 'fixes' entail (e.g., auto-generation of keys). This leaves significant gaps for a tool with 8 parameters and mutation capabilities.
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 appropriately sized and front-loaded, packing key actions (extract, detect, apply) into a single sentence. Every phrase earns its place by outlining core functionality, though it could be slightly more structured for clarity.
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 tool's complexity (8 parameters, mutation capabilities) and no annotations, the description is incomplete—it lacks behavioral details and parameter explanations. However, the presence of an output schema mitigates the need to describe return values, keeping it minimally viable but with clear gaps for safe 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?
Schema description coverage is 0%, so the description must compensate for all 8 parameters. It only vaguely references 'sourceDir' and 'i18nPath' through context (UI5 project files) and hints at 'mode' and 'dryRun' with 'report'/'fix' and 'preview', but fails to explain parameters like 'reason', 'maxDiffLines', 'keyPrefix', or 'maxFiles'. This insufficiently adds meaning beyond the bare 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 clearly states the tool's purpose with specific verbs ('extract UI literals', 'detect missing/unused i18n keys', 'apply fixes') and resources (UI5 i18n). It distinguishes itself from siblings by focusing on i18n management, unlike other tools that analyze performance, generate code, or handle project structure.
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 through the mention of 'optional fixes with safe preview/apply patch flow', suggesting it can be used for reporting or fixing. However, it lacks explicit guidance on when to choose this tool over alternatives (e.g., other analysis tools) or prerequisites for use, leaving some context to inference.
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 full burden. It mentions 'dry-run and patch safety,' hinting at non-destructive behavior and safety mechanisms, but lacks details on permissions, rate limits, side effects, or what 'patch safety' entails. For a complex tool with 16 parameters, this is insufficient 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense sentence with zero waste. It front-loads the core purpose and includes key behavioral hints ('dry-run and patch safety'), making it highly efficient and well-structured for its 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?
Given the high complexity (16 parameters, nested objects, no annotations, 0% schema coverage) and presence of an output schema, the description is incomplete. It doesn't explain parameter semantics or behavioral nuances, relying too heavily on the output schema and leaving the agent under-informed for proper tool 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 doesn't explain any of the 16 parameters' purposes, relationships, or required combinations. While it mentions artifacts like 'blueprint' and 'guide,' it doesn't map these to parameters like 'agentDefinitions' or 'qualityGates,' leaving significant 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 specific action ('scaffold reusable project agent artifacts') and lists the exact outputs (blueprint, guide, bootstrap prompt, optional MCP config). It distinguishes from sibling tools like 'scaffold_project_skills' by focusing on agent artifacts rather than skills.
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 through mentioning 'dry-run and patch safety,' suggesting when to use safety features, but doesn't explicitly state when to choose this tool over alternatives like 'scaffold_project_skills' or 'materialize_recommended_agents.' No clear exclusions or prerequisites are provided.
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 validation across components and optional metadata cross-checks, implying a read-only analysis without side effects. However, it lacks details on permissions required, output format (though an output schema exists), error handling, or performance considerations (e.g., time-intensive scans). For a validation tool with zero annotation coverage, this is a significant gap in 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, efficient sentence that front-loads the core action ('validate UI5 OData usage') and lists key components without redundancy. Every word earns its place by specifying validation targets, making it appropriately sized for a zero-parameter tool with clear scope.
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 complexity (validation across multiple UI5 components), the description is reasonably complete. It outlines the validation scope, and with an output schema present, it doesn't need to explain return values. However, it lacks context on when to use it versus siblings, and with no annotations, it misses behavioral details like safety or performance. For a validation tool, this is adequate but not fully comprehensive.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by specifying the scope of validation (manifest, XML/JS bindings, model APIs, optional metadata cross-checks), which clarifies what the tool inspects beyond the empty schema. This compensates adequately, though it doesn't detail how metadata cross-checks are triggered or configured.
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 purpose: validating UI5 OData usage across specific components (manifest, XML/JS bindings, model APIs) with optional metadata cross-checks. It uses specific verbs ('validate') and resources ('UI5 OData usage'), making it distinct from general validation siblings like validate_ui5_code or validate_ui5_version_compatibility. However, it doesn't explicitly differentiate from analyze_odata_metadata or scaffold_ui5_odata_feature, which slightly limits sibling distinction.
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 doesn't mention prerequisites, context (e.g., during development, testing, or auditing), or exclusions. Sibling tools like analyze_odata_metadata or validate_ui5_code could overlap in function, but the description offers no explicit comparison or usage scenarios, leaving the agent to infer based on tool names 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?
No annotations are provided, so the description carries the full burden. It mentions 'promote/degrade' and 'automatic rules or manual override', indicating mutation behavior, but fails to disclose critical details such as required permissions, whether changes are reversible, rate limits, or what the output schema contains. This leaves 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, efficient sentence that front-loads the core action and resource, then adds context about methods (automatic rules or manual override). Every word contributes value without redundancy, making it highly concise and well-structured.
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 that the tool has 0 parameters and an output schema exists, the description need not cover parameters or return values. However, as a mutation tool with no annotations, it should provide more behavioral context (e.g., side effects, error conditions) to be fully complete. The current description is adequate but leaves gaps in transparency.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, focusing instead on the tool's purpose and behavior, which aligns with the schema's completeness.
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 ('promote/degrade') and resource ('pack lifecycle status'), specifying the target states (experimental/candidate/recommended/deprecated). However, it does not explicitly differentiate from sibling tools like 'list_agent_packs', 'rank_agent_packs', or 'materialize_recommended_agents', which may have overlapping or related functions.
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 by mentioning 'automatic rules over feedback metrics or manual override', suggesting contexts for application. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., 'rank_agent_packs' for ranking or 'materialize_recommended_agents' for materialization), and does not specify prerequisites or 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?
With no annotations provided, the description carries the full burden. It discloses 'dry-run safety,' indicating a non-destructive or safe behavior, which is useful. However, it lacks details on permissions, rate limits, error handling, or output specifics, leaving gaps in 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, dense sentence that efficiently conveys purpose, output components, input source, and safety feature. It is front-loaded with the main action and wastes no words, making it highly concise and well-structured.
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 0 parameters, 100% schema coverage, and an output schema present, the description is mostly complete. It covers the tool's purpose and safety aspect, but lacks details on behavioral traits like error handling or output format, which could be inferred from the output schema.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by specifying the input source ('service metadata'), which clarifies the implicit context, earning a baseline 4 for compensating with contextual meaning.
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 ('Generate') and the resource ('base UI5 OData feature scaffold'), specifying the output components (view/controller/manifest/i18n) and the input source ('from service metadata'). It distinguishes from siblings like 'generate_ui5_feature' by emphasizing OData and scaffolding, though not explicitly contrasting them.
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 mentions 'dry-run safety,' implying a non-destructive or safe execution context, but provides no explicit guidance on when to use this tool versus alternatives (e.g., 'generate_ui5_feature' or other scaffold tools). No prerequisites or exclusions are stated.
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 the tool detects patterns but does not describe how it behaves: whether it returns a report, raises errors, modifies code, or has side effects. For a security tool with zero annotation coverage, this lack of operational details 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part ('Detect risky JavaScript patterns including eval, command injection, and prototype pollution') directly contributes to understanding the tool's function, making it highly concise and well-structured.
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 tool's moderate complexity (security analysis), no annotations, and an output schema present, the description is partially complete. It covers the purpose and parameter semantics well, but lacks usage guidelines and behavioral transparency. The output schema likely handles return values, so the description's gaps in other areas keep it at an adequate but not fully helpful level.
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 has 0% description coverage, but the description implicitly clarifies the 'code' parameter by specifying it analyzes JavaScript for security patterns. This adds meaningful context beyond the schema's basic type constraints, though it does not detail format or examples. With only one parameter, the description adequately compensates for the schema gap.
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 specific verbs ('Detect') and resources ('risky JavaScript patterns'), and it distinguishes from siblings by focusing on security rather than analysis, refactoring, or generation. It explicitly lists the types of patterns detected (eval, command injection, prototype pollution), making the scope unambiguous.
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 sibling tools like 'lint_javascript_code' or 'validate_ui5_code' that might overlap in code analysis, nor does it specify prerequisites or contexts (e.g., use for security audits vs. general linting). This leaves the agent without clear usage instructions.
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 full burden for behavioral disclosure. While it states what the tool scans for, it doesn't describe how it operates (e.g., static analysis, runtime checks), what output to expect, whether it modifies files, performance characteristics, or error handling. This leaves significant behavioral gaps.
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 that packs substantial information about what the tool does and what it looks for. Every word earns its place with zero wasted text or redundancy.
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 tool has 0 parameters, 100% schema coverage, and an output schema exists, the description covers the core purpose adequately. However, as a security scanning tool with no annotations, it should ideally mention whether it's read-only, what format results come in, or any limitations - gaps that prevent a higher score.
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 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately focuses on the tool's purpose rather than parameter details, earning a baseline 4 for this dimension.
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 specific action ('Scan') and target ('UI5 XML/JS sources'), with explicit security risk categories listed (XSS, unsafe HTML injection, dynamic code execution, insecure redirects). It distinguishes itself from sibling tools like 'security_check_javascript' by specifying UI5-specific sources rather than general JavaScript.
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 'security_check_javascript' or 'analyze_current_file'. It doesn't mention prerequisites, context requirements, or any explicit when/when-not scenarios.
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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