flutter-orchestrator
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation4/5
Most tools target distinct lifecycle phases (UI design, backend scaffolding, testing, security, observability), but generate_flutter_mock_factory and generate_flutter_charts are both for UI data presentation, and the three scaffold_* tools could be confused by name.
Naming Consistency4/5Tool names predominantly follow a verb_noun snake_case pattern (generate_, scaffold_, audit_, configure_, design_, diagnose_). A few deviations like orchestrate_flutter_project and generate_and_run_flutter_tests do not break the overall consistency.
Tool Count4/523 tools for an end-to-end Flutter generator server is justified given the coverage of UI, backend, tests, platforms, CI/CD, security, localization, auth, mocks, and observability. Count is on the higher side but well-scoped for full-stack generation.
Completeness4/5Coverage spans prompt decomposition, UI, backend, database, tests, platform configs, CI/CD, localization, deep links, mocks, auth, observability, and offline fallback. Minor exceptions like a dedicated code-gen migration tool or app store screenshots could be considered, but nonessential.
Average 3.4/5 across 23 of 23 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 6 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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states the tool both audits and scaffolds, but doesn't explain side effects—e.g., whether it modifies files, whether it's destructive, auth requirements, or the nature of the output. The scaffolding action is implied but its impact is unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no fluff. The audit function is front-loaded, and the scaffolding is secondary. However, it could be more structured by separating audit and scaffold phases or mentioning output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No annotations, no output schema, and the description omits critical context: prerequisites (must be an existing Flutter project?), side effects (does it overwrite files?), operation modes (does it audit only if no flags set?), and return behavior. For a combined audit+scaffold tool, this is a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers all three parameters with clear descriptions (codeSnippet, enableBiometrics, enableCertificatePinning) at 100% coverage. The description adds nothing beyond the schema; it doesn't clarify parameter usage or dependencies, so the baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it audits Flutter code for security issues and scaffolds secure components (Keychain, biometrics, SSL pinning). This distinguishes it from general audit tools like audit_flutter_codebase or audit_flutter_accessibility, though it doesn't explicitly differentiate from those siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 (e.g., audit_flutter_codebase for general audits). It doesn't mention prerequisites, scenarios, or exclusions, so an agent must infer the appropriate 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?
No annotations are present, so the description carries the full burden of behavioral disclosure. It discloses that the tool produces 'test execution commands' but does not clarify whether the tool actually runs the tests, despite the name 'generate_and_run_flutter_tests'; it also does not state side effects such as writing test files into the project or requiring an existing Flutter project.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence of roughly 25 words that front-loads the core purpose and contains no filler. Brevity comes at a small cost, since two of the four testType enum values are missing from the prose, but the structure itself is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a moderate-complexity tool (4 params) with no annotations and no output schema, so the description must carry more weight. It leaves unclear what the agent actually receives (generated test code, commands, or both), whether files are modified, and when to prefer this tool over generate_flutter_golden_tests; it also fails to mention the golden/integration support present in the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 four parameters, warranting the baseline of 3. The description adds minor flavor (testWidgets for widget tests, Riverpod/Bloc for state tests) but no per-parameter semantics beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('Generates') with concrete resources: Flutter unit tests, widget tests via testWidgets, Riverpod/Bloc state tests, and execution commands. However, it does not distinguish itself from the near-sibling generate_flutter_golden_tests, and it omits 'golden' and 'integration' from the prose even though both appear in the testType enum, so the stated scope under-covers the actual scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no when-to-use guidance, no exclusions, and names no alternatives. With generate_flutter_golden_tests as a direct sibling covering one of this tool's own enum values, an agent has no basis in the description alone to decide which test-generation tool to call.
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 does not mention side effects such as file creation, configuration changes, or dependencies, nor does it indicate what the scaffolded output looks like. This is a significant gap for a scaffolding tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that names the core features without repetition or fluff. It is appropriately concise and front-loads the primary purpose, though it could be structured to include usage guidance without much length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with three parameters, no output schema, and no annotations, the description is incomplete. It does not specify what files or configuration are generated, how the provider differentiates implementation, or what performance monitoring means in practice. An agent cannot anticipate the tool's full effect or output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 33% (only customEventNames has a description). The tool description mentions 'type-safe custom analytics event loggers' but does not explain how the provider enum affects scaffolding behavior or what enablePerformanceMonitoring controls. The description adds little value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb (scaffolds) with a clear resource (observability features) and names the concrete deliverables: crash reporting, analytics event loggers, and HTTP latency interceptors. This distinguishes it from sibling scaffold tools like scaffold_flutter_database or scaffold_flutter_backend, which target different domains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives, nor any mention of prerequisites or exclusion cases. The description only states what it does, leaving the agent to infer appropriate usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool catches network failures and serves cached/mock data, and implies it prevents crashes, but it doesn't explain the side effects of scaffolding (e.g., code generation, file modifications, or project structure changes). The behavioral claims are somewhat vague but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence, concise and front-loaded with the core purpose. It contains some marketing-style language ('seamlessly', 'zero crash') that slightly dilutes the technical clarity, but it is not verbose and gets to the point quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema and no parameter descriptions, the description must carry the full context for an agent. It explains what the interceptor does but omits how it integrates, what files it touches, how the fallback is configured, and what the agent should expect after invocation. The two parameters are unexplained, leaving the tool only partially understood.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% — neither parameter has a description. The tool description also mentions nothing about `cacheDurationMinutes` or `enableDemoMockFallback`. The parameter names are self-explanatory to an extent, but the description adds no meaning about their behavior, defaults, or interaction.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('scaffolds') and a clear resource ('automatic fallback interceptor'), and states the purpose: catching Wi-Fi drops and serving mock data for offline resilience. This distinguishes it from sibling scaffold tools by focusing on network failure handling, though it doesn't explicitly say how it differs from alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'during live stage demos' hints at a use case, but there's no explicit guidance on when to use this tool versus alternatives, no prerequisites, and no mention of when not to use it. The agent is left to infer intent from the technical description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions scaffolding but doesn't disclose side effects (e.g., file creation, dependency changes, whether it modifies existing code), required permissions, or reversibility. For a scaffolding tool that likely creates files, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with the core purpose. Efficient and no wasted words, though it could benefit from a second sentence on usage context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a scaffolding tool with 3 parameters and no output schema, the description is thin. It doesn't explain what files are generated, how the provider parameter affects output, or what the agent should expect after invocation. Siblings like scaffold_flutter_backend likely have similar gaps, but this tool's complexity warrants more detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 67% (featureName and systemInstruction have descriptions, provider has enum but no description). The description adds context about what the scaffold includes but doesn't elaborate on parameter usage beyond schema. The provider enum is self-explanatory, but systemInstruction could use more context on how it's used.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool scaffolds Gemini SDK integration for Flutter, listing specific components (streaming responses, Riverpod state controllers, interactive chat views). It distinguishes from siblings like scaffold_flutter_backend or scaffold_flutter_database, though it doesn't explicitly name a sibling it is not.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for Flutter AI features but doesn't explicitly state when to use this vs alternatives like generate_flutter_api_bridge or scaffold_flutter_offline_resilience. No exclusions or alternative routing provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states what the tool audits but doesn't disclose behavioral traits like whether it modifies code, requires specific permissions, or how it reports findings. It doesn't mention if it's read-only or if it can suggest fixes. For a tool that audits code, the agent needs to know if it's safe to run on production code or if it makes changes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently lists the audit categories. It's front-loaded with the verb 'Audits' and the resource. No wasted words, though it could be slightly more structured with bullet points for the categories.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is adequate for a simple audit tool with 2 parameters and no output schema. However, it doesn't explain what the output looks like (report format, severity levels, etc.) which an agent might need to know. It also doesn't mention whether the audit is synchronous or asynchronous, or if there are limits on code snippet size.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters are documented in the schema. The description adds no additional parameter semantics beyond what the schema provides. The fileType enum is self-explanatory. Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool audits Flutter/Dart source code for specific issue categories (performance bottlenecks, missing const constructors, controller memory leaks, architectural violations). This is a specific verb+resource with clear scope. It doesn't explicitly differentiate from sibling audit tools like audit_flutter_accessibility or audit_flutter_security, but the focus on performance/const/leaks/architecture is distinct enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for code auditing but doesn't explicitly state when to use this tool versus alternatives like audit_flutter_accessibility or audit_flutter_security. It doesn't mention when not to use it or provide context on selecting between audit tools. The fileType parameter hints at usage context but the description doesn't elaborate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It adds meaningful details beyond the name: the generated charts are animated, interactive, gradient-filled, tooltip-equipped, and depend on fl_chart. However, it never clarifies what 'scaffolds' actually does operationally: return code, write files, overwrite existing widgets, or generate a full project file. The description is partially transparent but incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
One dense sentence, front-loads the primary verb and resource, and packs in the most relevant details: chart types, implementation library, gradient fills, tooltips, and hackathon-oriented motivation. There is no filler or repeated information from the name or schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a code-generation/scaffolding tool with no output schema and no annotations, the description should state what kind of result is produced—a Flutter widget, a renderable chart, executable code, or a placeholder scaffold—not just 'scaffold via fl_chart'. It also does not reconcile 'Donut' with 'pie' or cover 'sparkline', leaving an operationally ambiguous definition for real invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 33% and the description does not compensate enough. It adds some meaning to chartType by listing chart styles and visual features, but it does not explain dataPoints, does not document the accepted enum values, and labels one enum option incorrectly by calling pie 'donut'. The dataPoints shape is actually described in the schema, but chartTitle and dataPoints still receive little added semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a concrete action ('Scaffolds') and target resource ('Line charts, Bar graphs, and Donut charts via fl_chart'), making the tool distinct from generic Flutter scaffolding siblings. It loses a point because it says 'Donut charts' while the schema enum uses 'pie', and it does not mention the 'sparkline' option at all.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for hackathon data storytelling' gives an implied usage context, but there are no explicit when-to-use or when-not-to-use instructions compared to sibling tools. An agent must infer when this is preferred over the other Flutter generation utilities.
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 provided, so description carries full burden. It does not disclose that golden tests are baseline snapshots that may become brittle or require updating when UI changes, and doesn't mention whether it creates files or requires an existing widget. Only states generation, not side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
One concise sentence with clear purpose, front-loaded. No wasted words. Could list generated files but not required.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for basic generation but missing details: effect on existing golden files, whether it runs them, and per-device configuration output. No output schema forces more burden; description doesn't cover edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers screenName and widgetName with descriptions, but testThemes lacks description (only default). Description doesn't clarify that testThemes controls the test matrix. With 67% coverage, description adds minimal value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb+resource: generates golden snapshot tests for Flutter widgets. It specifies the matrix (Light/Dark, phone/tablet) which distinguishes it from generate_and_run_flutter_tests, though it doesn't explicitly name that sibling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for golden snapshot generation but lacks explicit when-to-use vs generate_and_run_flutter_tests. Sibling list hints at alternatives but no guidance on selecting this one.
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 must carry the behavioral burden. 'Scaffolds' implies code generation, and the listed technologies convey scope, but the description does not disclose whether existing files are overwritten, whether a Flutter project is required, or what side effects occur on the filesystem.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense sentence with no filler. It front-loads the action and quickly enumerates the main scaffolding areas, though the long serial list makes it slightly harder to parse at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main generated areas and the schema fully documents parameters, but it lacks context about output location, generated file behavior, and when this tool is appropriate relative to similarly named siblings. It is adequate but not complete for a scaffolding operation with no output schema or annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents every parameter and enum. The description echoes the technology choices but adds little beyond the schema, such as tradeoffs between providers or how featureName maps to generated artifacts.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb, 'Scaffolds', and identifies the output resources: Clean Architecture repositories, remote data sources, local caching, and state-management controllers. It distinguishes the tool's combined backend scope from many siblings, though it doesn't explicitly contrast with overlapping tools like scaffold_flutter_database.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to choose this tool over siblings such as scaffold_flutter_database, scaffold_flutter_offline_resilience, or scaffold_flutter_auth_flow. The description states what it scaffolds but not the conditions, prerequisites, or exclusions an agent should consider.
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 explains what is generated (schemas, DAOs, migrations) but omits side effects such as file creation, potential overwrites, required project context, or any dependencies it may install. It also does not describe what happens on failure or how the agent should verify the result. The description lacks critical behavioral transparency for a scaffolding operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that front-loads the core purpose and deliverables. There is zero redundancy or filler; every word contributes to understanding the tool's function. It is an exemplary concise definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the schema covering all parameters, the tool is complex (generates multiple artifacts) and lacks an output schema. The description does not mention what the agent should expect after execution (e.g., file paths, generated code structure, potential side effects on the project). It also does not specify any required preconditions or integration steps, making it incomplete for an agent that needs to invoke and verify the scaffold.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with descriptions for databaseName and schemaVersion, and the tables parameter is described. The tool description mentions 'table schemas' and 'migration routines' which align with the parameters but does not add substantive detail beyond what the schema already provides. The baseline of 3 applies because the schema carries the semantic load effectively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Scaffolds' and the resource 'offline-first type-safe Drift (SQLite) database' with specific deliverables: table schemas, DAOs with reactive streams, and schema version migration routines. This distinguishes it from sibling scaffolding tools like scaffold_flutter_backend or scaffold_flutter_auth_flow, which target different subsystems.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 prerequisites (e.g., a Flutter project), scenarios where it should be avoided, or exclusions (e.g., if a backend database is needed). The agent must infer usage solely from the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions what files are generated but does not state whether it overwrites existing files, whether it requires an existing Flutter project, whether it is idempotent, or what the return value is. For a tool that likely writes multiple files, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the core action, lists specific outputs, and wastes no words. It is appropriately sized for the tool's purpose and easy to parse at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has three parameters, one required, with enums and defaults, and no output schema, the description is inadequate. It does not clarify the output format, whether it modifies existing project files, what the 'Web WASM CanvasKit bootstrap' entails, or any side effects. An agent would be uncertain about the tool's behavior after reading this, making it incomplete for effective invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 33% (only projectName has a description). The description adds no extra meaning to permissions or targetPlatforms beyond the schema enums and defaults. It does not explain the format or purpose of these parameters. Since the coverage is low, the description should compensate but does not, leaving the agent to infer semantics from names and enums alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Generates'), the resource ('native platform configurations'), and enumerates concrete outputs (iOS Info.plist permission strings, AndroidManifest.xml permissions, Web WASM CanvasKit bootstrap). This clearly distinguishes it from sibling tools like audit_flutter_codebase or generate_flutter_cicd_pipeline. An agent can immediately understand its purpose without inspecting the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. However, the specificity of 'generates native platform configurations' strongly implies the appropriate use case, and the sibling tool names do not overlap with this functionality. There is no misleading guidance, but the lack of explicit alternatives or when-not-to-use leaves room for improvement.
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. It discloses that the tool diagnoses but doesn't disclose how it operates (e.g., whether it returns a fix, whether it requires all parameters, or whether it's a read-only analysis). It also doesn't mention any side effects, limitations, or what the output contains. This is a moderate gap, but the description does name the specific error types, giving some behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence, concise and front-loaded with the primary action and scope. It uses a colon to list specifics. It's efficient and clear, though it could be even more structured by separating the list into a separate sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is a diagnostic service with 4 parameters and no output schema, the description should clarify what kind of output the agent can expect (e.g., explanatory text, suggestions). It also doesn't state whether the tool handles only the listed error types or also others. It's adequate but leaves some key context (return value, scope limitations) unspecified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents each parameter. The description doesn't add deeper meaning beyond the schema — it doesn't explain how to combine them or which parameter is most essential (errorMessage is required). It just lists the error types, which helps map to inputs but doesn't go beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Diagnoses') and clears resource ('Flutter errors'), and enumerates the categories of errors it handles. However, it doesn't differentiate from the many sibling tools beyond the obvious — there's no explicit statement of what this tool is not, nor does it distinguish from other diagnostic-like tools (e.g., audit_flutter_codebase). It's clear but not distinguished.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it — when encountering Flutter errors of the listed categories — but there's no explicit guidance on when not to use it or which sibling tools are alternatives. It would benefit from a note like 'For general code audits, use audit_flutter_codebase instead.' Without exclusions, it's merely implied.
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?
There are no annotations, so the description carries the full behavioral burden. It transparently states that files are generated and identifies the main outputs, but it does not disclose whether existing files are overwritten, whether project configuration is modified beyond l10n.yaml, or whether a Flutter project must already exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence that efficiently names all deliverables. Every listed item contributes to tool selection: the config file, the translation format, the locale-switching behavior, and RTL support.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lists the key outputs, which is reasonably complete for a code-generation tool with no output schema. It remains incomplete because it does not tie the optional parameters to the generated behavior, does not mention side effects or prerequisites, and gives no indication of what customization gaps a caller should expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 33%, and the description adds little parameter-level meaning. The locale list '(en, es, ar)' partially clarifies supportedLocales and defaultLocale, but it does not explain how stringKeys maps into the generated ARB files, what happens when no stringKeys are provided, or how the locale parameters affect output.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('Generates') and a precise set of artifacts: l10n.yaml, standard ARB localization files, a dynamic locale-switching notifier, and RTL handling. This makes the tool's scope immediately clear and distinguishes it from the broader Flutter scaffolding and configuration tools in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
When to use the tool is implied clearly by the artifact list: it is for adding ARB-based localization and locale switching to a Flutter project. However, there is no explicit guidance on when not to use it, no stated prerequisites, and no mention of alternatives for simpler or more custom localization setups.
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?
There are no annotations to lean on, and the description does mention that checks are performed and wrappers are generated. However, it is ambiguous whether generating the wrappers modifies the input snippet, creates new files, or only returns wrapper code in the response. For a tool without annotation support, this is a useful but incomplete view of side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, tight sentence that leads with the central audit purpose and then lists specific criteria and outcome. There is no fluff, repetition, or misplaced information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter tool, the description does enough to explain what gets inspected and why an outcome is generated. Still, with no output schema or annotations, the missing clarity about whether the tool edits code and what the return value looks like leaves the agent without a complete mental model of the operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the single parameter with a clear description ('Flutter widget code to audit'), and the tool description refers to Flutter widget trees, which closely aligns. Since schema coverage is 100%, the description only adds marginal context about the exact audit scope rather than new parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Audits') with a specific resource ('Flutter widget trees') and explicitly names WCAG 2.1 AA, screen reader Semantics, and touch target size. It clearly identifies a focused accessibility audit tool and can be differentiated from audit_flutter_codebase and audit_flutter_security, though it does not explicitly say it is not those.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the use case clear: run this when auditing Flutter widget accessibility against WCAG and when wanting generated AccessibleTouchTarget wrappers. It does not explicitly mention alternatives or exclusions, but the narrow focus on accessibility makes the intended scenario reasonably obvious.
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 of disclosing behavior. It does reveal the concrete artifacts involved (assetlinks.json, apple-app-site-association, FCM routing), but it does not mention side effects on existing project files, prerequisites like domain verification, or whether the configuration is reversible.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that front-loads the action and lists the affected areas without repetition or filler. Every phrase contributes information about what the tool configures.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a multi-platform configuration tool with no output schema or annotations, the description should explain invocation context and effects more thoroughly. It names the artifacts and scope, but does not address how the routes parameter is consumed, what outputs are produced, or what preconditions exist, so an agent would have to infer those.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 67%, with customScheme and domainHost already described. The description adds no parameter-level detail, and the optional routes array is left without explanation of how path, screenName, and parameters map to go_router or platform deep links, though its name makes its role partially inferable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb, 'Configures', and names four concrete targets: go_router deep linking, Android App Links (assetlinks.json), iOS Universal Links (apple-app-site-association), and FCM push notification routing. This clearly differentiates the tool from more generic sibling tools like generate_flutter_platform_config.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for setting up deep linking and push-notification routing, but it never explicitly states when to prefer it over alternatives or when not to use it. Usage context is inferable from the purpose, but there is no direct guidance or exclusion criteria.
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 behavior disclosure. It states what the tool produces (widgets, layouts, state integration, animations) but not HOW results are delivered — whether it writes files, returns code, or generates a design spec. The design-oriented phrasing makes its non-destructive nature inferable, but the output mechanism remains unspecified, which matters for a code-generation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single, well-constructed sentence with zero filler. The most distinctive content (Material 3 responsiveness, state management options, animations) is front-loaded, giving an agent immediate signal about what this tool does without wading through prose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with four well-documented parameters and no output schema, the description covers the what but not the full how — notably the output delivery format and any workflow expectations (e.g., does it expect a prior decompose_flutter_prompt call?). It's adequate but leaves the agent guessing about invocation results, which a richer description could resolve.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline of 3 applies. The description adds modest value beyond the schema by hinting at the design philosophy (Material 3, responsive, production-ready) that shapes output, but it doesn't detail parameter usage or format expectations beyond what the schema already documents.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Designs') with a clear resource (Flutter UI) and enumerates concrete deliverables: widgets, Material 3 responsive layouts, Riverpod/Bloc state integration, and animations. This distinguishes it cleanly from siblings like scaffold_flutter_backend or generate_flutter_platform_config, which target entirely different concerns.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for UI-design work through its focus on widgets, layouts, and state management, but it doesn't explicitly state when to use it versus alternatives or mention exclusions. No sibling is named, and the boundary against tools like decompose_flutter_prompt (prompt decomposition) or generate_flutter_charts (a narrow UI subset) is left to inference.
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 transparency burden. It does disclose meaningful behavior: generated artifacts are realistic but fake, and repositories are in-memory, implying no persistence. However, it does not say whether the tool writes files, modifies an existing Flutter project, or introduces dependencies, so the side-effect profile is only partially disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one efficient sentence with no filler. It front-loads the action and artifact types and then adds the use-case context, earning its length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a generator with no output schema and no annotations, an agent needs to know what fields maps to, what itemCount controls, and what happens to the project after generation. The description only hints at the overall purpose, leaving important operational details unexplained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 33%: domainName is documented, but fields and itemCount are not. The description does not mention either parameter, so it fails to compensate for the schema gap. The word 'domain' weakly relates to domainName, but the semantics of fields and itemCount are left to inference.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('Generates') and concrete resources ('mock data factories', 'fake entities', 'in-memory mock repositories'), and connects them to a clear use case ('hackathon UI prototyping'). This makes it easy to distinguish from sibling generation tools like golden tests, API bridges, or chart generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for instant hackathon UI prototyping' gives clear context for when this tool is appropriate. It does not explicitly name alternatives or state when not to use it, but the mock-specific wording strongly implies the intended scenario.
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 of behavioral disclosure, and it does so well. It reveals a key behavior: 'Checks target platforms first (asks if not specified),' warning the agent that the tool may pause for clarification. It also sets expectations that the tool will execute multiple steps (decomposition, file creation). This is valuable context about side effects that the schema cannot convey.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler; the first sentence states the purpose, and the second lists the workflow. Information is effectively front-loaded. The list of steps is a bit long, but for an orchestration tool of this complexity, it's an appropriate and dense summary. Nearly every word carries meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 7 params, no output schema, and no annotations, the description competently maps the high-level flow. However, given the tool's complexity, an agent might need more context about return values, expected execution time/long-running operations, or failure states. The description clearly explains the 'what' and 'in what order' but is silent on outcomes or errors, which is a noticeable gap for a high-stakes orchestrator.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all parameters thoroughly, hitting the baseline of 3. The description adds value by explaining the targetPlatforms interaction (asks if omitted), which is not fully captured in the parameter description alone. However, it doesn't provide additional detail on other parameters like prompt or stateManagement, which are already adequately described in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb and resource: 'End-to-end multi-agent orchestration for Fltter apps.' It enumerates a concrete pipeline (platform checks, prompt decomposition, pubspec creation, UI, backend/state, tests), which distinguishes it from the many specialized sibling tools like design_flutter_ui or scaffold_flutter_backend. An agent can immediately tell this is the do-everything orchestrator. This goes beyond a mere restatement of the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for full-project generation by listing the full workflow (UI screens, backend/state layer, tests), which strongly contrasts with the single-purpose siblings. However, it never explicitly states 'use this for full projects' or 'for just one layer use design_flutter_ui instead.' The usage context is implied through the listed pipeline steps rather than stated as guidance.
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 provided, so the description carries the full burden. It discloses key behavioral traits: generates animated carousel (PageView with dots), M3 social login UI, and token-persisting Riverpod controllers. 'Token-persisting' implies statefulness and side effects, which is useful for the agent. However, it does not disclose the exact Flutter version compatibility, whether it modifies existing files, or the specific package dependencies added. The description is transparent about the main scope and behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense sentence that front-loads the key features and uses parenthetical clarification for the carousel. Every element adds value: the instant/animated nature, the UI components, and the Riverpod controllers. It is concise without being vague, and well-structured for quick scanning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (scaffolding a full auth flow with multiple components) and the lack of output schema or annotations, the description is somewhat incomplete. It covers the main deliverables but does not mention how the tool integrates with an existing Flutter project (does it modify files?), what Riverpod setup is expected, or the structure of the generated code. It also doesn't explain the toggle defaults which could affect behavior. With three parameters, only one documented in schema, and no output schema, the description leaves an agent uncertain about preconditions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 33% (only appName has description, which is just 'Application name.'). The description only mentions appName implicitly in context of scaffolding, and doesn't explain enableSocialLogins or enableOnboardingCarousel beyond their names. The description does not explain how these booleans affect the output or mention their defaults. The context signals show 3 parameters with 33% coverage, so the description must compensate but fails to do so.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description is specific and action-oriented: 'Scaffolds an instant animated Onboarding carousel (PageView with dots), Material 3 Social login UI (Google/Apple/Email), and token-persisting Riverpod Auth controllers.' This clearly identifies the verb (scaffold), the resource (Flutter auth flow components), and the specific deliverables (onboarding, social login, Riverpod auth). It distinguishes itself from sibling tools like scaffold_flutter_backend or scaffold_flutter_database by focusing on auth flow and UI.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage in a Flutter project when auth flow scaffolding is needed, but does not explicitly state when to use this tool versus alternatives like scaffold_flutter_backend or generate_flutter_api_bridge. There is no explicit 'when not to use' or mention of prerequisites. For a tool with many siblings, more explicit routing would be beneficial.
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 must carry the behavioral info. It discloses the 'always checks and verifies target platforms first' behavioraine. However, it doesn't mention potential side effects, authentication requirements, or what happens when the prompt can't be decomposed (e.g., ambiguous input), nor the output format. The behavior disclosed is minimal and could be more informative, such as noting that a clarification might be sent back if a target platform is unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact at two sentenceshol and front-loads the key action ('Deconstructs Flutter prompts'). The second sentence adds a behavioral guidance (target platform check) that is useful and efficiently phrased. No wasted words, though the two clauses could be separated for clarity, but it's still pretty crisp.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (producing features, modules, sprint plans) and lack of an output schema, the description conveys what class of output is expected (features, modules, sprint plans) but not the format. It also hints at the conditional logic for target platforms. For a planning tool that returns a structured plan, the description is relatively complete for an agent to decide when to call itate it, but doesn't specify the output structure, which lowers it from a 5.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has descriptions for all five parameters, including the targetPlatforms array which is explicitly 'if not provided or mentioned in prompt, a clarification is returned' (this is in the schema description). The tool description adds marginal value about the parameters; it doesn't explain the 'sprint plans' output or how architecturePattern affects results. With essentially 100% schema coverage, the baseline of 3 is appropriate, and the description doesn't go beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: deconstructs Flutter prompts into Clean Architecture features, modules, and sprint plans. The verb 'deconstructs' is specific skill (planning/decomposition) and the resource 'Flutter prompts' is identified where it comes from. This distinguishes it from sibling tools like scaffold_flutter_backend or generate_flutter_tests, which are about execution rather than planning.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states the tool always checks and verifies target platforms first, which is a clear usage hint. It doesn't explicitly state when to use this tool instead of siblings, but the purpose is clean enough for an agent to infer it should be called when a user provides a high-level prompt to break down. No explicit exclusions are given, but the context is sufficiently portrayed.
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 present, so the description carries the full burden. It discloses key generated outputs and specifics such as signed APKs, self-signed MSIX certificates, and Fastlane. However, it does not state whether files are created/overwritten, whether GitHub CLI/secrets are prerequisites, or what side effects occur.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single dense sentence front-loads the core purpose before enumerating major features. There is no filler, repetition of the tool name, or unnecessary explanation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description gives enough detail for an agent to select the tool and understand its main outputs, but with no output schema and no annotations, it omits operational details like where workflows are written, whether existing files are overwritten, and what external tools are required. These gaps matter for a generator tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is high (83%), so the schema already documents most parameters. The description adds context by tying split-per-ABI, MSIX, and Fastlane directly to the generated workflow, but it does not meaningfully clarify parameter values beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Generates'), a clear resource ('GitHub Actions workflows for Flutter'), and enumerates concrete artifacts such as split-per-ABI APKs, keystore scripts, MSIX packaging, and Fastlane. It is distinctive among the sibling tools, none of which claim CI/CD workflow generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the context clear: this is the tool for production, multi-platform Flutter CI/CD pipeline generation. It does not explicitly name exclusions or alternatives, but the purpose is unambiguous enough for an agent to know when to invoke it.
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 full burden. It mentions it 'generates' files, which hints at side effects like writing to disk, but does not disclose network calls to pub.dev, potential overwrites of existing files, or authentication needs. It is clear but lacks depth on behavioral consequences.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single, densely packed sentence that front-loads the action ('researches'), specifies the domain ('pub.dev packages'), and lists the concrete outputs. Every phrase adds value without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the input and output artifacts but lacks any mention of what the tool returns (e.g., a summary, success status, or the generated file contents). Since there is no output schema, describing the return value would be helpful for agents to know how to handle the response. This is a gap given the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all parameters (packages, projectName, stateManagement, targetPlatforms). The description does not add extra meaning beyond what the schema provides, but the high schema coverage makes this acceptable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('researches'), a precise resource ('pub.dev packages'), and concrete outputs ('standard pubspec.yaml and analysis_options.yaml'). It also adds compatibility verification ('Dart 3.6+ / Flutter 3.27+'), which distinguishes it from other Flutter-related tools in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for dependency research and project configuration setup, which suggests its niche among siblings focused on other concerns (e.g., testing, security, UI). However, it does not explicitly state when NOT to use it or name alternatives, leaving some room for interpretation.
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 provided, so the description carries the full burden. It discloses what is generated (four artifacts), which is helpful for an agent to infer the side effects (code generation, no destructive operations). However, it does not clarify whether the tool overwrites existing files, whether it requires a specific project structure, or whether it generates code in-place. This is a minor gap but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that is concise and front-loaded with the main verb and object, then lists deliverables. No wasted words. It could benefit from breaking into two sentences to separate the purpose from the deliverables, but it is appropriately short for the information conveyed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is moderately complex (4 parameters with nested structures) and has no output schema or annotations. The description explains the overall output but does not explain required inputs (e.g., that models and endpoints are optional or how they are used), nor does it clarify return behavior (e.g., does it write files, return code?). For a code-generation tool, this is a clear gap, but the core purpose is clear enough for a simple use case.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (serviceName and baseUrl have descriptions, but models and endpoints do not). The description adds little about parameters beyond the overall purpose. It does not explain how models and endpoints relate to the generation, forcing the agent to infer from names. The coverage is moderate, so the description could have compensated more, but the basic intent is inferable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action (Generates) and the resource (full-stack Flutter API client contracts), listing four concrete deliverables (Dio REST client, JSON DTOs, Riverpod providers, WebSocket realtime subscription providers). This distinguishes it from sibling tools like scaffold_flutter_backend or generate_flutter_mock_factory, though it does not explicitly name an alternative.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when needing a full-stack Flutter API integration, but it does not explicitly state when not to use it or mention alternatives. Given the sibling tools (e.g., generate_flutter_mock_factory for mocks, scaffold_flutter_backend for backend scaffolding), the description could be more explicit about selection criteria, but the output specifics are clear enough.
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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