Pabal MCP

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: apps-* tools handle app registration and management, aso-* tools manage ASO data, auth-check handles authentication, and release-* tools manage version and release note operations. The descriptions clearly differentiate their functions, eliminating any ambiguity.
Naming Consistency5/5
All tool names follow a consistent hyphenated pattern with clear prefixes (apps-, aso-, auth-, release-) and descriptive suffixes (e.g., add, init, search, pull, push). This structured naming convention makes it easy to understand tool groupings and purposes at a glance.
Tool Count5/5
With 10 tools, the server is well-scoped for mobile app store management, covering key areas like app registration, ASO data handling, authentication, and release management. Each tool serves a specific, necessary function without redundancy, making the count appropriate for the domain.
Completeness4/5
The tool set provides comprehensive coverage for core mobile app store workflows, including app setup, ASO data synchronization, authentication checks, and version/release note management. A minor gap is the lack of tools for deleting or updating registered apps, but agents can likely work around this given the strong coverage of other operations.
Average 3/5 across 10 of 10 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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"
  ]
}
```
Then . Browse examples.
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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?
No annotations are provided, so the description carries full burden. It mentions 'Register' (implying a write operation) and 'checks both stores', but doesn't disclose behavioral traits such as permissions required, whether registration is idempotent, rate limits, or what happens on failure. 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 with zero waste. It's front-loaded with the core purpose and includes essential details 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool ('Register') with no annotations, no output schema, and 3 parameters, the description is incomplete. It lacks crucial details like what the tool returns, error conditions, or side effects, leaving significant gaps for an AI agent to understand its full behavior.
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 100%, so the schema fully documents all parameters. The description adds minimal value beyond the schema, mentioning 'bundleId or packageName' (implied by the schema's description for 'identifier') and 'checks both stores' (implied by the 'store' parameter's enum). Baseline 3 is appropriate as the schema does the heavy lifting.
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 ('Register') and resource ('individual app'), specifying it works by 'bundleId or packageName' and 'checks both stores'. However, it doesn't explicitly differentiate from sibling tools like 'apps-init' or 'apps-search', which might have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 'apps-init' (which might initialize multiple apps) or 'apps-search' (which might search for apps). It mentions 'Automatically checks both stores' but doesn't clarify if this is unique to this tool or a general feature.
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 'save to local cache' and implies data fetching, but lacks details on permissions needed, rate limits, error handling, cache behavior (e.g., overwrite or merge), or what 'fetch ASO data' entails (e.g., metadata, rankings). This is inadequate for a tool with potential external API calls and local storage.
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 ('fetch ASO data') and includes key details (sources and cache saving). There is no wasted verbiage, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of fetching from external stores and saving locally, with no annotations and no output schema, the description is insufficient. It doesn't explain what 'ASO data' includes, the format of saved data, success/error responses, or dependencies on other tools like 'apps-init'. This leaves significant gaps for 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?
Schema description coverage is 100%, providing clear documentation for all 5 parameters. The description adds no additional parameter semantics beyond implying that 'app', 'packageName', or 'bundleId' identify the target, and 'dryRun' affects saving. This meets the baseline of 3 when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetch ASO data') and the target resources ('App Store/Google Play'), and mentions saving to local cache. It distinguishes from siblings like 'aso-push' (which likely pushes data) and 'apps-init' (which registers apps). However, it doesn't explicitly differentiate from 'release-pull-notes' or other data-fetching tools, keeping it at 4 instead of 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. It doesn't mention prerequisites (e.g., needing registered apps via 'apps-init'), exclusions, or comparisons to siblings like 'apps-search' or 'release-pull-notes'. This leaves the agent without 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 the full burden of behavioral disclosure. It mentions pushing data but doesn't cover critical aspects such as required permissions, rate limits, error handling, or the irreversible nature of the operation (unless 'dryRun' is used). This leaves significant gaps in understanding the tool's behavior and risks.
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, direct sentence that efficiently conveys the core action without unnecessary words. It is front-loaded with the key verb and resource, making it easy to parse quickly. Every part of the sentence serves a clear purpose, earning a high score for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a data-pushing operation with 6 parameters, no annotations, and no output schema, the description is insufficient. It lacks details on behavioral traits, error cases, and output expectations, leaving the agent with incomplete information to use the tool effectively in a real-world context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the baseline is 3. The description adds no additional meaning beyond the schema, as it doesn't explain parameter interactions (e.g., how 'app', 'packageName', and 'bundleId' relate) or provide usage examples. This meets the minimum viable level without enhancing parameter understanding.
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 ('push') and resource ('ASO data from local cache to App Store/Google Play'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'aso-pull', which handles data retrieval rather than pushing, leaving room for improvement in 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?
No guidance is provided on when to use this tool versus alternatives. For instance, it doesn't mention prerequisites like needing local cache data from 'aso-pull' or clarify usage relative to other tools like 'release-create'. This lack of context makes it harder for an agent to decide when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't describe behavioral traits such as what the output looks like (e.g., success/failure status, error messages), whether it's idempotent, or any rate limits. This leaves significant gaps for a tool that checks authentication status.
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. It's appropriately sized for a simple tool and front-loaded with the core purpose, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's purpose (checking authentication status) and lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., boolean status, detailed auth info) or potential side effects, which is crucial for an authentication-related tool. The schema coverage is high, but behavioral context is lacking.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'store' fully documented in the schema (including enum values and default). The description doesn't add any meaning beyond what the schema provides, such as explaining why one might choose 'both' over individual stores. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Check authentication status') and target resources ('App Store Connect / Google Play Console'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from sibling tools like 'apps-init' or 'apps-add' which might also involve authentication, missing full 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 (e.g., before performing operations that require authentication), exclusions, or how it relates to sibling tools like 'apps-init' that might handle authentication setup.
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 'Check' implies a read-only operation, it doesn't specify whether this requires authentication, has rate limits, returns structured data versus raw text, or handles errors. For a tool that presumably queries external app stores, this represents 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 extremely concise at just 6 words, front-loading the core purpose with zero wasted language. Every word earns its place by specifying both the action and target platforms.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and multiple parameters, the description is incomplete. It doesn't explain what 'latest versions' means (version numbers? release dates? changelogs?), what format the results come in, or how the parameters interact (e.g., whether 'app' is required when specifying 'store'). For a tool that queries external APIs, this leaves too much undefined.
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 100%, so the schema already documents all 4 parameters thoroughly. The description doesn't add any parameter semantics beyond what's in the schema - it mentions 'App Store/Google Play' which aligns with the 'store' parameter but provides no additional context about parameter relationships or usage patterns.
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 ('Check latest versions') and target resources ('from App Store/Google Play'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from potential sibling tools like 'release-create' or 'release-update-notes' that might also interact with release versions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'release-create', 'release-pull-notes', and 'release-update-notes' available, there's no indication of when checking versions is appropriate versus creating releases or managing release notes.
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 the tool fetches release notes but doesn't describe what 'fetch' entails (e.g., whether it retrieves from external APIs, requires authentication, has rate limits, or saves data). The mention of 'App Store/Google Play' hints at external sources but lacks operational 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 directly states the tool's purpose without unnecessary words. It's front-loaded and appropriately sized, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (fetching from external stores with 5 parameters) and lack of annotations and output schema, the description is insufficient. It doesn't explain what the tool returns (e.g., notes content, metadata), error conditions, or dependencies on other tools like 'apps-add' for registration. This leaves significant gaps for an AI agent to use it effectively.
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 100% description coverage, so parameters are well-documented in the schema itself. The description adds no additional meaning beyond implying that parameters relate to app identification and store selection, which is already clear from the schema. This meets the baseline score of 3 for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetch') and resource ('release notes from App Store/Google Play'), making the purpose immediately understandable. It doesn't explicitly differentiate from siblings like 'release-check-versions' or 'release-update-notes', but the verb 'fetch' suggests retrieval rather than checking or updating.
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 an app registered first), compare to siblings like 'release-check-versions' (which might check versions without fetching notes) or 'release-update-notes' (which updates notes), or specify scenarios where it's appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Update' implies a mutation operation, but the description doesn't specify required permissions, whether changes are reversible, rate limits, or what happens if parameters conflict. This leaves significant gaps for a tool with 8 parameters and no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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, with every word earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (8 parameters, no annotations, no output schema), the description is insufficient. It doesn't address behavioral aspects like mutation effects, error handling, or return values, leaving the agent with incomplete context for proper tool invocation.
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 100%, so the schema already documents all 8 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema, such as explaining relationships between parameters like 'app', 'packageName', and 'bundleId'. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Update release notes') and the resource ('for App Store/Google Play version'), providing specific verb+resource information. However, it doesn't distinguish this tool from sibling tools like 'release-pull-notes' or 'release-create', which would require explicit differentiation to earn 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 'release-pull-notes' or 'release-create'. There's no mention of prerequisites, conditions for use, or when not to use it. 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?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool can create versions or check/display latest versions, but doesn't clarify whether this is a read-only or write operation, what permissions are needed, whether it's destructive, or what the output format looks like. The dual behavior (create vs. check) adds complexity that isn't fully explained.
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 concise with two sentences that cover both primary and conditional behaviors. It's front-loaded with the main purpose, though the conditional behavior could be slightly clearer. No wasted words, but the dual functionality might benefit from more structured phrasing.
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 (dual create/check behavior, 6 parameters, no annotations, no output schema), the description is insufficient. It doesn't explain the relationship between parameters (e.g., how app, packageName, and bundleId interact), doesn't clarify whether creation is for one store or both when version is provided, and provides no information about return values or error conditions.
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 100%, so the schema already documents all parameters thoroughly. The description adds minimal value by mentioning the conditional behavior when version is not provided, but doesn't provide additional semantic context beyond what's in the parameter descriptions. Baseline 3 is appropriate when schema does the heavy lifting.
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 primary function ('Create a new version on App Store/Google Play') with a specific verb and resource. It also mentions a secondary behavior when version is not provided. However, it doesn't explicitly distinguish this from sibling tools like 'release-check-versions' or 'release-update-notes', which appear related to release management.
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 provides some usage context by explaining what happens when the version parameter is omitted ('checks and displays latest versions'). However, it doesn't offer guidance on when to use this tool versus alternatives like 'release-check-versions' or 'release-update-notes', nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 default behavior when called without a query but doesn't address other critical aspects like authentication requirements, rate limits, pagination, error handling, or what the return format looks like. For a search tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves in practice.
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 just one sentence that efficiently communicates the core functionality and default behavior. Every word earns its place, and it's front-loaded with the primary purpose. There's no redundancy 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 moderate complexity (search functionality with two parameters), lack of annotations, and absence of an output schema, the description is insufficiently complete. It doesn't explain what the search returns (e.g., app details, IDs, or metadata), how results are structured, or any behavioral constraints. This leaves the agent with significant uncertainty about how to interpret and use the tool's output.
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 100%, so the schema already fully documents both parameters (query and store). The description adds minimal value beyond the schema by reiterating that an empty query returns all apps, which is already stated in the schema's query description. No additional semantic context is provided for parameters, so the baseline score of 3 is appropriate.
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 ('Search') and resource ('registered apps'), making the purpose immediately understandable. It distinguishes this tool from siblings like 'apps-add' or 'apps-init' by focusing on search functionality rather than creation or initialization. However, it doesn't specify what constitutes a 'registered app' or the scope of the search beyond the query parameter.
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 provides implied usage guidance by stating 'Returns all apps if called without query,' which suggests this tool can be used for both filtered searches and retrieving all apps. However, it doesn't explicitly mention when to use this tool versus alternatives like 'aso-pull' or 'release-check-versions,' nor does it provide any exclusion criteria or prerequisites for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool's behavior: querying and automatic registration, with store-specific rules. However, it lacks details on permissions needed, rate limits, error handling, or what 'register automatically' entails (e.g., side effects). This is a moderate disclosure but leaves gaps for a tool with potential mutations.
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 highly concise and front-loaded: two sentences that directly state the purpose and usage rules without any fluff. Every sentence earns its place by providing essential information, making it efficient and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a tool that queries and registers apps, with store-specific behavior), no annotations, and no output schema, the description is moderately complete. It covers the core action and store rules but lacks details on output format, error cases, or deeper behavioral traits. For a tool with potential side effects and no structured output, it should do more to be fully adequate.
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 100%, so the schema already documents both parameters ('store' and 'packageName') with descriptions and enums. The description adds some context: it clarifies that 'packageName' is required for Google Play, which is implied but not explicit in the schema (which says 'required when setting up Google Play'). This provides marginal value beyond the schema, aligning with the baseline for high 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: 'Query app list from store API and register automatically.' It specifies the verb ('query' and 'register') and resource ('app list'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'apps-add' or 'apps-search', which might have overlapping functionality, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use this tool: 'App Store: auto-register all apps, Google Play: packageName required.' This gives explicit guidance for different store scenarios, including a requirement for Google Play. However, it doesn't mention when not to use it or name alternatives among sibling tools, such as 'apps-add' for manual registration, so it's not a full 5.
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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