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rabdulsal

playstore-release-mcp

by rabdulsal

Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool targets a distinct action or resource: config verification, track status, bundle upload, releasing, listing text update, graphics upload, review listing, and reply. There is no overlap or ambiguity between them.

    Naming Consistency4/5

    All tools share the 'play_' prefix and most follow a verb_noun pattern (upload_bundle, release_to_track, update_listing, list_reviews, reply_review). 'play_app_status' is a noun phrase rather than a verb action, which is a minor deviation, but the overall pattern is consistent and predictable.

    Tool Count5/5

    8 tools is well-scoped for a Play Store release management server. Each tool covers an essential operation without redundancy, and the count fits comfortably within the typical 3-15 range.

    Completeness4/5

    The surface covers the core release lifecycle (upload, release, status) and store presence (listing text, graphics, reviews). Gaps include inability to read current listing text or images, adjust staged rollout percentages, or manage closed testers, but the primary workflows are sufficiently covered.

  • Average 4.1/5 across 8 of 8 tools scored. Lowest: 3.5/5.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • No commit activity data available
    • 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.

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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?

    With no annotations, the description carries the full burden. It usefully discloses that the reply is 'public' and is a 'developer' reply, signaling a public write operation. However, it does not address important behavioral aspects such as whether an existing reply can be overwritten, auth/permission requirements, or response/error behavior.

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

    Conciseness5/5

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

    The description is a single, front-loaded sentence that states the action and object without any filler. Every word earns its place, and it is easily scannable for an agent.

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

    Completeness3/5

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

    For a simple two-parameter mutation tool, the description conveys the core purpose but is somewhat thin given no annotations and no output schema. It omits workflow context (e.g., pairing with play_list_reviews), constraints on posting replies, and expected outcome details, leaving the agent to infer them.

    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 50%: review_id is documented as coming from play_list_reviews, while reply_text has no description. The overall description adds context that the reply is public and targets a user review, which helps interpret both parameters, but it does not specify reply_text limits or formatting.

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

    Purpose5/5

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

    The description uses a specific verb ('Post') and clearly identifies the resource ('a public developer reply to a user review'). It also implicitly distinguishes itself from sibling tools like play_list_reviews by indicating a write/reply action rather than a read/list action.

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

    Usage Guidelines2/5

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

    No guidance is provided about when to use this tool versus alternatives, nor does it mention prerequisites such as obtaining review_id from play_list_reviews. The description leaves workflow context entirely implicit, with only the schema hinting at the source of review_id.

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

  • Behavior2/5

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

    With no annotations provided, the description must carry the full burden of behavioral disclosure. It mentions that uploads are direct (no Console click-through) and gives dimensions for icon and feature graphic, but it does not disclose whether the upload overwrites existing images, required permissions, side effects, or success/failure behavior. This is a significant gap 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 two sentences with no fluff. The first sentence front-loads the core purpose and scope, while the second adds a useful comparative note. Every word earns its place.

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

    Completeness3/5

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

    The tool is relatively simple (3 params, no output schema), and the description covers the main purpose and some specifics. However, given the lack of annotations, it misses important context such as authentication requirements, overwrite behavior, and constraints for image types. It's adequate but not comprehensive.

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

    Parameters3/5

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

    Schema description coverage is only 33% (only file_path has a description). The description compensates partially by clarifying image types (e.g., '512x512 hi-res icon' and '1024x500 feature graphic') and listing examples of screenshots. However, it does not explain the language parameter or all enum values (e.g., sevenInchScreenshots, tvBanner), leaving some ambiguity.

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

    Purpose5/5

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

    The description clearly states the tool's function: 'Upload a store listing image' with specific types (screenshots, icon, feature graphic). This distinguishes it from siblings like play_upload_bundle (which likely uploads the app binary) and play_update_listing (which handles text). The verb and resource are explicit.

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

    Usage Guidelines3/5

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

    The description implies usage for uploading images to a store listing, and the note about 'no Console click-through needed' gives context about when to prefer this method. However, it does not explicitly state when to use this tool versus the sibling tools or mention any exclusions/alternatives.

    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?

    The description indicates a read-only operation by using 'List', but it does not disclose behavioral details such as pagination, rate limits, or the precise meaning of 'recent.' With no annotations, the description carries the transparency burden but only partially fulfills it.

    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 consists of two concise sentences. Every phrase adds value: the first defines the purpose and output, and the second provides platform context. There is no redundancy or filler.

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

    Completeness3/5

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

    For a simple list operation with one optional parameter and no output schema, the description provides the essential fields (star ratings and text), but it leaves 'recent' undefined and does not mention whether the response includes pagination or other metadata. Given the absence of annotations and output schema, the description is only moderately 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?

    The parameter max_results is neither described nor referenced in the description. With 0% schema description coverage, the description was expected to compensate for the missing parameter explanation. The parameter name and constraints in the schema are self-evident, but the description adds no semantic context about its role in limiting or paginating results.

    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 action ('List recent user reviews') and the key data returned ('star ratings and text'). It also distinguishes itself from the sibling tool play_reply_review by focusing on reading reviews, and the note about no App Store Connect equivalent adds platform context.

    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 this is the intended method for fetching reviews on Play, explicitly noting 'Play exposes reviews directly via the API.' However, it does not explicitly state when not to use this tool or mention alternatives like play_reply_review, so it falls short of full explicit guidance.

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

  • Behavior3/5

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

    With no annotations, the description carries the burden. It discloses the API limitation clearly, but does not state update semantics (e.g., whether fields are overwritten entirely) or any required permissions. This adds some context but not rich behavioral detail.

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

    Conciseness5/5

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

    Two concise sentences with the core purpose front-loaded. Every word earns its place, and the limitation is noted succinctly without redundancy.

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

    Completeness4/5

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

    For a simple update tool, the description covers scope and important limitations. However, it lacks details about overwrite behavior, response format, or prerequisites. Still, given the tool's simplicity, it is reasonably 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 description must compensate. It names three of the four parameters (title, short_description, full_description) but omits 'language', leaving that parameter's purpose and format unexplained. Partial compensation only.

    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 updates Play Store listing text for a locale, listing specific fields (title, short description, full description). This distinguishes it from sibling tools like play_upload_graphics and play_release_to_track.

    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 what the tool can and cannot do, notably that Data Safety and content rating forms have no public API and must be done via Play Console. This implies when to use this tool vs. the web console, though it doesn't name alternative sibling tools.

    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 carries the burden. It discloses the specific checks performed, including a conditional behavior ('if creds are present'), and notes the non-check of local toolchain. It doesn't explicitly state whether the tool is read-only or what happens on failure, but 'verify' implies non-mutation, adding useful 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?

    Three sentences that are front-loaded with the core purpose, then enumerate specific checks, then provide usage context. Every sentence earns its place with no fluff or repetition.

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

    Completeness4/5

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

    For a zero-parameter tool with no output schema and no annotations, the description covers the key aspects: what it verifies, when to use it, and a scope clarification. It lacks an explicit statement about return values or failure behavior, but the 'verify' intent makes the outcome reasonably predictable.

    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?

    There are zero parameters, and schema coverage is 100% (vacuously). The description explains what the tool acts on (PLAY_PACKAGE_NAME and credentials), which are environment-level context rather than parameters. Baseline for 0 params is 4, and no additional parameter information is needed.

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

    Purpose5/5

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

    The description states a specific verb 'Verify' with a clear resource: Play release config end-to-end, detailing exactly what it checks (service-account credentials, package name, API reachability). This distinguishes it from sibling tools like play_app_status or play_upload_bundle by focusing on pre-flight release setup verification.

    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?

    Explicitly instructs 'Run this first in any release session', which is a clear when-to-use directive. Also clarifies what it does not do ('No local toolchain check is needed'), providing a when-not. However, it doesn't name specific alternative tools for different scenarios, only implying sequencing.

    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 carries the full burden. It discloses significant behavioral traits: production is 'the point of no return,' subject to policy review, while testing tracks 'publish immediately with no review gate.' It could add more about side effects (e.g., overwriting previous releases) but the provided cautions are valuable.

    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, front-loaded with the core action, followed by essential caveats. Every sentence earns its place without 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?

    For a release tool with no output schema and no annotations, the description covers the critical context: production risk, human confirmation, and instant publishing for testing tracks. It could mention how to verify the release afterwards (e.g., via play_app_status) or prerequisites, but it is largely complete for the described purpose.

    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 67%. The description adds meaning beyond the schema by explaining track semantics — production vs. testing, and custom closed-testing track names. It also clarifies that version_code is from play_upload_bundle. It does not expound on status, rollout_fraction, or release_notes, but the schema partially covers those.

    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 opens with a specific verb and resource: 'Assign an uploaded versionCode to a release track and publish it there.' This clearly distinguishes the tool from siblings like play_upload_bundle (uploading) or play_update_listing (listing updates).

    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?

    Provides clear context on when to use the tool: production vs. testing tracks, and the review gate difference. It explicitly warns to 'confirm with the human first for production.' However, it does not name alternative tools or provide explicit when-not-to-use scenarios, so it stops short of a 5.

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

  • Behavior4/5

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

    With no annotations provided, the description carries the full burden. It indicates the tool is read-only by describing it as a 'snapshot' and enumerates the exact information returned. However, it does not disclose potential caveats like data freshness, permissions, or error behavior, which would be valuable.

    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-loading the core value (snapshot of tracks and release details) and then providing a direct use case. Every word earns its place.

    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 zero-parameter, read-only status tool, the description is complete. It names the tracks, the data fields, and the intended use case. No output schema exists, but the description adequately conveys what is returned.

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

    Parameters4/5

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

    The tool has zero parameters, so the baseline is 4. The description adds no parameter-specific information, but none is needed since there are no parameters to clarify.

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

    Purpose5/5

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

    The description clearly identifies the tool as a status snapshot for all release tracks, listing specific data fields (version codes, rollout status, staged-rollout percentage). It distinguishes itself from sibling tools that perform actions (upload, release, update) by focusing on read-only state.

    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 states when to use the tool: 'Use this to answer where is the release right now?'. While it gives clear context, it does not mention alternatives or when not to use it, which would elevate it to a 5.

    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 carries the full burden. It discloses that the tool returns the versionCode and that it does not ship to a track, which is important behavioral context. However, it does not mention any side effects like whether uploading overwrites existing bundles or if special permissions are required, so it is not fully 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, front-loaded with the purpose, then providing essential follow-up details (return value and next step). Every sentence earns its place; no fluff.

    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, the description covers the action, prerequisite, return value, and relationship to the release flow. No output schema exists, but the description explains the output. It is complete enough for an agent to select and invoke correctly.

    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 covers the only parameter (aab_path) with 100% description coverage. The description mentions '.aab' and the path, but adds no syntax or format detail beyond what the schema already states. Baseline 3 is appropriate.

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

    Purpose5/5

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

    The description starts with 'Upload a signed .aab (Android App Bundle) to Play', which is a specific verb+resource and clearly differentiates from siblings like play_release_to_track (which ships to a track). It unambiguously states the tool's function.

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

    Usage Guidelines5/5

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

    The description explicitly states a prerequisite ('must already be built and signed') and provides an alternative/next step ('pass it to play_release_to_track to actually ship it to a track'), giving clear when-to-use context and an explicit alternative.

    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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