ios-ship-doctor

by menansali

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool serves a distinct, non-overlapping purpose: ASC readiness, app listing, placeholder scanning, guideline explanation, privacy manifest generation, and a comprehensive preflight. No two tools could be confused.
Naming Consistency4/5
Most tools follow a verb_noun pattern (e.g., check_placeholder_content, generate_privacy_manifest) with a consistent snake_case style. The only outlier is 'preflight' which is a single word, but it is a common term and the overall pattern is clear.
Tool Count5/5
With exactly 6 tools, the server covers the core aspects of iOS app submission readiness without being excessive or lacking. Each tool justifies its presence.
Completeness5/5
The server covers the full lifecycle of pre-submission checks: placeholder content, privacy manifest generation, Info.plist keys, third-party SDK manifests, ASC credentials and metadata, and a comprehensive preflight that ties it all together. There are no obvious gaps for its stated purpose.
Average 4.2/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 11 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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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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It indicates scanning for specific content types and references Guideline 2.1, suggesting a compliance check. However, it does not disclose whether modifications occur, permissions needed, or the exact nature of the output, leaving some behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense sentence that efficiently lists scanned items. It is front-loaded and free of fluff, though a slightly more structured list could improve readability.
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 single parameter, no output schema, and no annotations, the description provides a solid overview of functionality. It references a relevant guideline and typical use cases. However, it omits details about the output format or whether results are returned as a list or summary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the parameter 'projectPath' is well-documented in the schema. The tool description adds no further detail about the parameter, meeting the baseline but not exceeding it.
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 scans source and Info.plist for specific placeholder content like lorem ipsum, test keys, and template tokens. The verb 'Scan' is specific and the resource is well-defined, distinguishing it from sibling tools that focus on submissions or app listings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use before review to check for unwanted content, which is clear context. However, it does not explicitly state when not to use or directly compare to sibling tools like preflight or explain_guideline, leaving the agent to infer suitable scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses key behaviors: default preview, write side-effect, and manual Xcode step. It covers scanning first-party code and existing declarations, but doesn't mention overwrite behavior or error cases.
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?
Three sentences covering purpose, usage, and post-step with no filler. Front-loaded with key action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 2-param tool with no output schema, description covers generation purpose, preview vs write, and post-save step. Could mention return value explicitly, but implied.
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 coverage is 100%, so baseline is 3. Description restates schema info but doesn't add extra meaning beyond defaults and path flexibility.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a valid PrivacyInfo.xcprivacy covering required-reason APIs. The verb 'generate' and resource 'PrivacyInfo.xcprivacy' are specific. Sibling tools are unrelated, so it distinguishes well.
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 explains default preview behavior and how to save with write=true, plus a post-save step. No explicit when-not-to-use or alternatives, but the tool is unique among siblings and context is clear.
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 bears full burden. It describes the tool as running checks and returning a report, without mentioning potential side effects, required permissions, error conditions, or limitations (e.g., handling of invalid project paths). The coverage is adequate but lacks depth.
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?
Two sentences with no filler. The first sentence states purpose and scope, the second provides usage guidance. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has one required parameter and no output schema. The description specifies what the report contains (prioritized, covering specific checks) but does not detail the output format. For a simple tool, this is nearly complete; a small gap in return structure could be improved.
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?
Schema coverage is 100%, so baseline is 3. The description adds that projectPath can be a repo root or ios/ directory, which is valuable extra guidance beyond what the schema provides ('Absolute path to the iOS project'). This justifies a higher score.
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 runs all App Store readiness checks and returns a single prioritized report, listing specific checks (privacy manifest, Info.plist, third-party SDKs, placeholder traps). It positions itself as the starting point, distinguishing from siblings like asc_check_submission or check_placeholder_content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Start here' and frames the tool as answering 'is this app ready to submit?', indicating when to use it. It does not explicitly mention when not to use it or provide alternatives, but the context is clear enough for an agent to decide.
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 burden of behavioral disclosure. It mentions the requirement for environment variables (authentication) and hints that the returned id is used elsewhere, but does not discuss side effects, rate limits, pagination, or error handling. For a list operation, basic safety can be inferred, but more detail would improve 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 two sentences, front-loaded with the core action and return value, followed by usage guidance (env vars and next step). Every sentence earns its place; there is no redundancy or fluff.
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 simplicity of the tool (no input parameters, no output schema), the description covers the essential points: what it does, what it returns, prerequisites, and how to use the result. However, it lacks details on whether the list is complete or paginated, and does not describe the exact format of the returned data. For a list tool, this is mostly sufficient but could be slightly more comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters, so schema coverage is trivially 100%. The description adds value by noting that the tool requires specific environment variables (not parameters) and that no explicit arguments are needed. This is clear and helpful, earning a top score.
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 'List the apps on your App Store Connect account' with a specific verb and resource. It also specifies the returned fields (id, name, bundle id) and mentions the required environment variables, making the purpose unambiguous and distinct from sibling tools like asc_check_submission.
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 gives clear context for when to use the tool: to retrieve an app id for use with asc_get_rejections. However, it does not explicitly state when not to use it or mention any alternatives among siblings, which would justify a higher score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description discloses two important behavioral traits: offline operation and no credential requirement. No side effects or limitations are mentioned, but it is adequate for a read-only explanation 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?
Two sentences achieve maximum clarity with zero waste: the first states the action, the second adds usage constraints. Perfectly front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description covers all necessary aspects: purpose, usage context, and key behavioral traits. 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?
The schema description covers the sole parameter at 100% with examples. The tool description adds no further parameter information beyond what the schema provides, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool explains a specific guideline number in plain language with a typical fix, clearly distinguishing it from sibling tools like submission checking or app listing.
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 specifies that the tool works offline and requires no credentials, providing clear context for when to use it. However, it does not explicitly exclude alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It explicitly lists what the tool checks (demo credentials, review notes, screenshots), implying a read-only behavior. It does not specify side effects or permissions, but is otherwise transparent.
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?
Two sentences with no filler. Each sentence adds essential information: what is checked, why it matters, and how it relates to a sibling tool. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description covers all relevant aspects: purpose, specific checks, related sibling, and a concrete use case (avoiding Guideline 2.1 rejection). No missing information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description adds value by specifying that the 'appId' comes from 'asc_list_apps', providing context beyond the schema description.
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 checks App Store Connect readiness for submission, listing three specific items (demo credentials, review notes, screenshot sets). It uses a specific verb 'Check' and resource, and distinguishes from sibling 'preflight'.
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 context on when to use (before submission to avoid rejection) and explicitly names an alternative ('preflight'), clarifying that preflight only checks the binary. It lacks explicit when-not-to-use statements.
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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