apk-docforge

by alejandrojlamas

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 targets a distinct stage or artifact: search/download handle acquisition, analyze_artifact creates the analysis, and the get/list tools expose distinct outputs such as findings, features, screens, reports, or prompts. There are no overlapping tool purposes that would confuse an agent.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern: search_*, download_*, analyze_*, get_*, and list_*. The get_ vs list_ split is also consistent: get_ returns a single item or document, while list_ returns a collection.
Tool Count5/5
Nine tools is an appropriate size for an APK analysis pipeline. Every tool maps to a distinct workflow step or output artifact, and none feel redundant or extraneous.
Completeness4/5
The pipeline covers the full lifecycle needed for APK docforge work: search, download, analysis, report generation, prompt generation, and detailed findings/feature/screen listings. The only minor gap is the absence of a general list_analyses or candidate-management tool, which could limit discoverability but does not break the core workflow.
Average 3/5 across 9 of 9 tools scored. Lowest: 2.3/5.
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 is passing
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How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description gives no indication of side effects, read-only nature, performance, or any caveats associated with generating a prompt. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loads the primary purpose in a single sentence. However, the sentence is somewhat cryptic due to the undefined 'Codex' term, and the structure could benefit from a brief clarification of what the prompt is used for.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a minimal description, no output schema, and no annotations, this tool description is incomplete. Given the existence of several sibling analysis tools, the description fails to provide sufficient context to distinguish its output and usage, especially for an agent that might not know what 'Codex ingestion prompt' means.
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 description mentions the single parameter implicitly ('for an analysis'), but with 0% schema coverage, it doesn't add any meaning beyond the schema's basic 'analysis_id' string type. It doesn't explain what the analysis_id represents or how to obtain it, leaving the agent without sufficient parameter context.
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 gets a Codex ingestion prompt for an analysis, which is specific to the 'prompt' resource and distinguishes it from other analysis-related tools like get_analysis and get_report. However, the term 'Codex ingestion prompt' is opaque without further explanation of what makes it a Codex-specific prompt, so the purpose is only partially clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when this tool should be used versus alternatives like get_analysis or get_report. The description doesn't clarify the relationship between a Codex ingestion prompt and other analysis outputs, 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?
There are no annotations, so the description carries the full burden. It mentions quarantine and provenance but does not clarify what these mean for the output (e.g., is the file transformed, does it include metadata?), nor does it state authentication, return format, or any side effects. For a download tool, it does not disclose if quarantine files are downloaded in a special form or if provenance is included as metadata. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise and front-loaded with the action. It includes relevant qualifiers ('persisted allowed candidate', 'quarantine and provenance') without excessive wordiness. However, it could be slightly clearer, but overall it is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 2 parameters, 0% schema coverage, no annotations, and no output schema, the description needs to compensate. It mentions quarantine and provenance, which are output-related, but does not explain the output format, file location (out parameter), or any constraints. The description is insufficient for an agent to invoke the tool correctly without additional assumption.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description does not explain the meaning of the 'out' parameter (with default 'downloads') despite it being optional. It only reuses the parameter name 'candidate_id' in a description that says 'numeric candidate id', but the schema type is string, which is contradictory and unhelpful. The description adds no information about the 'out' parameter or the format expected for candidate_id.
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 ('download'), the resource ('persisted allowed candidate'), and the identifier ('numeric candidate id'), and briefly mentions 'quarantine and provenance' which hints at additional output contents, distinguishing it from sibling search/analysis tools. However, it does not differentiate from the sibling 'get_*' tools explicitly, as they may also retrieve candidate-related data, but the verb 'download' suggests file retrieval.
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 siblings like 'analyze_artifact' or 'get_report'. The description implies use when a persisted allowed candidate needs to be downloaded, but there are no explicit alternatives or exclusions. This is minimal guidance without 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?
There are no annotations, so the description carries the full burden for behavioral disclosure. It only says 'Get' and does not explicitly state that this is a read-only operation, what the output looks like, whether any side effects occur, or what happens on failure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the purpose and result. It wastes no words, though it could be slightly longer to clarify the identifier ambiguity.
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 one-parameter retrieval tool, the description provides the basic purpose and expected output ('summary and output paths'). However, with no output schema and no annotations, it leaves gaps around output structure, the database-id option, and error behavior, making it only minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description is the only source of parameter meaning. It mentions 'analysis id or database id,' but the schema only has analysis_id, creating ambiguity about whether analysis_id accepts a database id or whether a separate parameter is missing. No format or validation details are provided.
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 'Get' and the resource 'analysis summary and output paths,' and it indicates lookup by an identifier. It is distinct enough from siblings like analyze_artifact and get_report, though it does not explicitly differentiate itself from 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 gives no guidance on when to use this tool versus alternatives such as get_report or analyze_artifact. It only states the mechanism ('by analysis id or database id') without specifying context, 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?
With no annotations, the description carries the full burden of behavioral disclosure. It indicates a read operation but does not mention return format, pagination, error conditions, or any side effects. The description adds little beyond what the name and schema already imply.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, short sentence with no redundant words. It is front-loaded with the verb and resource, 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?
Though the tool is simple (one parameter, no output schema), the description lacks essential context such as what static screens are, whether the result is a list of IDs or names, and any limitations. Given the absence of annotations and output schema, this description is under-specified for reliable 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?
The input schema has one required parameter, analysis_id, with no description in the schema. The tool description references 'an analysis' which loosely maps to analysis_id but does not explain its semantics, type, or expected format. With 0% schema coverage, 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 identifies the tool as a list operation targeting 'static screens' scoped to an analysis. It is concise and specific enough to distinguish from other list tools like list_findings or list_features, though it could be more explicit about what 'static screens' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as get_analysis or list_features. The phrase 'mapped for an analysis' implies a prerequisite (analysis_id) but does not explain 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 to convey safety or side effects, the description must carry the burden, but it only states 'static apk-docforge analysis' without disclosing whether the operation is read-only, touches external services, or has side effects. The static qualifier conflicts with the schema's dynamic mode, adding confusion rather than clarity.
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, brief sentence that is easy to scan and front-loads the core action. It could be improved by removing 'static' to avoid redundancy with the schema's mode parameter, but it remains concise overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given four parameters, including an enum for mode and no output schema, the description fails to mention the dynamic mode, output options, or device handling. It provides minimal context for a tool of this complexity, leaving the agent without critical usage 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?
Schema description coverage is 0%, so the description must explain parameters, but it only hints that 'path' points to local files via 'local APK/APKS/XAPK'. It provides no context for 'out', 'mode', or 'device', and the mention of 'static' diverges from the schema's mode enum, failing to clarify rather than helping.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Run') and resource ('static apk-docforge analysis') and enumerates artifact types (APK/APKS/XAPK), which helps distinguish it from broader siblings like search_apps or get_report. However, the term 'static' is potentially misleading since the schema allows a 'dynamic' mode, slightly obscuring the full scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for a local APK/APKS/XAPK artifact' implies this tool targets local files, suggesting a use case versus cloud-based alternatives (e.g., download_app). However, there is no explicit guidance on when to use it instead of siblings like get_analysis or list_findings, nor any exclusions or alternative suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It indicates a read operation but does not disclose potential errors, auth requirements, or whether the report is freshly generated. It adds minimal behavioral context beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is direct and to the point, with no unnecessary words. It earns its place by stating exactly what the tool does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite being a simple tool with one parameter, the description is under-specified. It lacks details about the return format (beyond 'Markdown'), error behavior, or how to use the analysis_id in practice. Given no annotations and no output schema, the description should provide more context to be complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must explain the parameter. It implicitly references analysis_id by saying 'for an analysis', but does not explain what the ID is, how to obtain it, or any format constraints, leaving the agent to infer meaning from the parameter name alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' and resource 'Markdown report' scoped to 'an analysis', making it clear what the tool returns. It distinguishes itself from siblings like get_analysis by specifying 'Markdown report' rather than generic analysis data.
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 get_analysis or other related tools, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full transparency burden, but it only states the basic action. It does not mention whether results are paginated, ordered, readonly, permission-restricted, or what happens if the analysis does not exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, short sentence with no filler, redundant phrasing, or unnecessary details. It is easy to parse and front-loads the core verb and object.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only one parameter and no output schema, so the core action is minimally conveyed. However, the description omits what the findings list returns, any limitations, and interaction with sibling tools, which leaves clear contextual 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?
The only parameter is analysis_id, but the schema covers 0% with no description and no format details. The tool description only implies its purpose through the phrase 'for an analysis,' which is minimal compensation.
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 ('List') and an explicit resource ('security findings') with a clear scope ('for an analysis'). It distinguishes itself from sibling tools like list_features and list_screens by targeting a distinct resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus related tools like get_analysis, get_report, or list_features. There are no exclusions, prerequisites, or alternative tool references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'list', implying read-only, but it does not mention output shape, pagination, filtering, required permissions, or any other runtime 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 entire description is one compact, front-loaded sentence. There is no filler or redundant detail; every word carries meaning.
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 one-parameter list tool with no output schema, this is minimally adequate: it names the resource and its scope. However, it does not explain what 'features' means, how results are returned, or what distinguishes inferred from observed features, leaving contextual 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%, and the description only loosely maps to the analysis_id parameter with 'for an analysis'. This is minimal compensation since the parameter name already indicates it is an analysis identifier.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' plus a clear resource, 'features' with 'inferred and observed' qualifiers, scoped to 'an analysis'. It distinguishes clearly from sibling tools like list_findings and list_screens, which focus on different artifact types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance about when to use this tool instead of the siblings. The phrase 'for an analysis' implies a usage context, but it does not offer any alternatives, exclusions, or prerequisites, so the agent gets no direction for selecting between list_features, list_findings, or get_analysis.
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 full responsibility for behavioral disclosure. It reveals that the tool searches only 'allowed' sources, does not download, and persists candidates locally—key traits beyond a simple search. It does not, however, mention error handling, return behavior, or side effects beyond persistence.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence contains no fluff. Every word contributes meaning, and it efficiently conveys both the primary action and the persistence side effect.
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?
In the absence of an output schema, the description should explain what the tool returns (e.g., candidates, success status, or a list). It mentions persisting candidates locally, which implies a side effect but not the return payload. It also does not clarify what 'candidates' are or how they might be used with sibling tools like 'get_analysis' or 'download_app'.
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 description does not mention any of the three parameters, and schema coverage is 0%. While parameter names and defaults are present in the schema, the description adds no extra clarity about 'query', 'limit', or 'sources', leaving the agent to infer meaning (especially for valid 'sources' values).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Search') and resource ('allowed app sources') and clarifies the non-downloading nature, effectively distinguishing it from sibling 'download_app'. The addition of 'persist candidates locally' further specifies behavior beyond the tool name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly contrasts with downloading by stating 'without downloading', giving the agent a clear when-not-to-use signal. It also notes a side effect (persistence), but does not explicitly name alternative tools or exhaustive when-to-use conditions.
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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