Backend Architect MCP Server

by jemhakdog

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 has a clearly distinct purpose with no overlap: get_file_instruction provides a prompt, get_next_pending_task fetches tasks, initialize_project sets up structure, save_* tools store different planning aspects, and write_component_file writes files. The descriptions clearly differentiate their functions, preventing agent misselection.
Naming Consistency4/5
The naming follows a consistent verb_noun pattern with minor deviations: most tools use verb_noun (e.g., save_database_plan, initialize_project), but get_file_instruction and get_next_pending_task use verb_adjective_noun, and write_component_file uses verb_noun_noun. This slight inconsistency is readable but not perfectly uniform.
Tool Count5/5
With 9 tools, the count is well-scoped for backend project management, covering initialization, planning, task management, and file writing. Each tool earns its place by addressing specific aspects of the workflow, avoiding bloat or thin coverage.
Completeness4/5
The tool set covers core backend development workflows: project setup, planning (database, roles, routes, tests, context), task management, and file writing. Minor gaps exist, such as no tools for updating or deleting plans, but agents can work around this by re-saving or using existing tools effectively.
Average 2.9/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 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
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This repository includes a README.md file.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'saves' data, implying a write operation, but does not disclose permissions needed, whether changes are reversible, rate limits, or what 'state' entails. The description lacks details on behavioral traits beyond the basic action, leaving significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that is front-loaded with the tool's action. It avoids unnecessary words and gets straight to the point, though it could be more informative. The structure is clear but under-specified in content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description need not explain return values, but it is incomplete for a mutation tool with no annotations. It lacks details on usage context, parameter meaning, and behavioral implications. With 1 parameter and low schema coverage, the description does not provide enough context for effective use, especially compared to sibling tools.
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 1 parameter with 0% description coverage, and the description does not add meaningful semantics. It mentions 'context' but does not explain what this parameter should contain, its format, or examples. With low schema coverage, the description fails to compensate, providing minimal value beyond the schema's structure.
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 'saves organizational context and complex operation requirements to state', which provides a vague purpose. It mentions a verb ('saves') and resources ('organizational context', 'complex operation requirements'), but lacks specificity about what 'state' refers to or how this differs from sibling tools like save_database_plan or save_roles_plan. The purpose is understandable but not clearly distinguished 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 Guidelines2/5
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. The description does not mention prerequisites, appropriate contexts, or exclusions. With sibling tools like save_database_plan and save_roles_plan, there is no indication of how this tool's function relates to or differs from them, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions writing a file and marking a task as done, implying mutation, but fails to detail permissions, side effects, error handling, or what 'marks as done' entails. This is a significant gap for a tool that likely modifies state.
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 with two clear actions in a single sentence, making it front-loaded and efficient. However, it's overly brief given the tool's complexity, potentially sacrificing necessary detail for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters with 0% schema coverage, no annotations, and likely involves mutation (writing files and marking tasks), the description is incomplete. It doesn't explain the parameters, behavioral traits, or usage context, and while an output schema exists, the description doesn't provide enough information for safe and effective 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?
Schema description coverage is 0%, so the schema provides no parameter details. The description adds no meaning beyond the parameter names ('type', 'name', 'content'), failing to explain what these represent (e.g., file type, filename, content format). This leaves all three parameters undocumented, which is inadequate for a tool with multiple required inputs.
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 'writes the file and marks the task as done', which provides a clear verb ('writes') and resource ('file'), but it's vague about what kind of file or task is involved. It doesn't distinguish from siblings like 'save_database_plan' or 'save_test_plan', which might also involve writing files or marking tasks, leaving ambiguity in its specific purpose.
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 offers no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context (e.g., after getting a task from 'get_next_pending_task'), or exclusions, leaving the agent to infer usage based on the name alone, which is insufficient for effective tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions returning a 'strict SYSTEM PROMPT' but does not explain what 'strict' entails, any constraints (e.g., format, length), or the response behavior (e.g., error handling). For a tool with no annotations, this leaves significant gaps in understanding its operational traits.
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 front-loaded and efficient, with no wasted words. It directly states the tool's action and output, making it appropriately sized for its purpose, though it could benefit from more detail to improve clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which should cover return values), the description's minimal content is somewhat acceptable. However, with no annotations, 2 undocumented parameters, and vague purpose, it is incomplete for effective use. It meets a baseline but has clear gaps in context and guidance.
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 2 parameters with 0% description coverage, and the tool description does not add any meaning beyond the schema. It does not explain what 'task_type' or 'task_name' represent, their expected values, or how they influence the returned prompt. With low schema coverage, the description fails to compensate, leaving parameters undocumented.
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 'Returns a strict SYSTEM PROMPT for the agent to write the code,' which specifies a verb ('Returns') and resource ('SYSTEM PROMPT'), but it is vague about what the prompt contains or its exact purpose. It does not clearly differentiate from sibling tools like 'write_component_file' or 'get_next_pending_task,' leaving ambiguity in its role.
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 prerequisites, context, or exclusions, such as when to choose 'get_file_instruction' over 'write_component_file' or other siblings. This lack of direction makes it unclear in what scenarios this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states 'Saves simulation scenarios to state' without disclosing behavioral traits such as permissions needed, whether it overwrites existing data, error handling, or side effects. It's inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words, making it highly concise. However, this brevity contributes to its lack of detail, but structurally it's 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?
Given the tool's mutation nature (implied by 'Saves'), no annotations, 0% schema coverage, and an output schema (which helps but isn't described), the description is incomplete. It doesn't cover key aspects like behavior, parameters, or usage context, making it insufficient for effective tool selection.
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 provides no parameter information beyond the tool name implying 'tests'. It doesn't explain what 'tests' should contain, their structure, or examples, failing to compensate for the schema's lack of descriptions.
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 'Saves simulation scenarios to state' provides a basic verb ('Saves') and resource ('simulation scenarios'), but it's vague about what 'state' means and doesn't differentiate from sibling tools like save_database_plan or save_roles_plan. It's not tautological but lacks specificity.
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 like save_database_plan or save_roles_plan. The description implies a save operation but offers no context on prerequisites, timing, or exclusions, leaving the agent with minimal usage cues.
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 'Saves' which implies a write/mutation operation, but doesn't disclose behavioral traits such as whether this overwrites existing data, requires specific permissions, has side effects, or handles errors. The phrase 'to state' is ambiguous and adds minimal context beyond the basic action.
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 with two sentences that directly state the action and parameter details. It's front-loaded with the main purpose, though the second sentence could be more integrated. There's no wasted text, but it could be slightly more structured for clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 1 parameter with 0% schema coverage, no annotations, and an output schema (which reduces need to explain returns), the description is minimally adequate. It covers the basic action and parameter structure but lacks details on behavior, usage context, or error handling, making it incomplete for a mutation tool without annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds some semantics by specifying that each role should have 'name', 'description', and 'permissions', which clarifies the expected structure of array items. However, with 0% schema description coverage and 1 parameter ('roles'), this partially compensates but doesn't fully explain the parameter's purpose or constraints (e.g., format of 'permissions'). Baseline is 3 due to schema coverage being low but description providing some value.
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 action ('Saves user roles/permissions to state') and specifies the resource ('roles/permissions'), but it's vague about what 'to state' means (e.g., persistent storage, session state, or configuration file). It doesn't differentiate from sibling tools like 'save_database_plan' or 'save_route_plan', which have similar naming patterns but unclear distinctions.
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. The description lacks context about prerequisites (e.g., whether roles must be validated first), exclusions, or comparisons to sibling tools like 'save_organization_context' or 'save_test_plan', leaving the agent with no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool saves data to state, implying persistence, but doesn't clarify if this is a write operation, what permissions are needed, whether it overwrites existing data, or how errors are handled. This is inadequate for a tool with mutation implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It front-loads the key action and resource, making it easy to scan and understand the core purpose immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which reduces the need to describe return values) but no annotations and poor schema coverage, the description is moderately complete. It covers the purpose but lacks usage guidelines, detailed parameter semantics, and behavioral context, making it insufficient for fully informed tool selection.
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 0% description coverage, with one required parameter 'models' as an array of objects. The description mentions 'table schemas (fields, types, relationships)' but doesn't explain how this maps to the 'models' parameter, leaving semantics vague and failing to compensate for the schema's lack of documentation.
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 ('Saves') and the resource ('table schemas') with specific attributes ('fields, types, relationships') and destination ('to state'). It distinguishes from siblings like 'save_roles_plan' by specifying the type of data being saved, though it doesn't explicitly contrast 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?
No guidance is provided on when to use this tool versus alternatives like 'save_organization_context' or 'save_roles_plan'. The description implies it's for saving database schemas but doesn't specify prerequisites, timing, or exclusions, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool saves data to state, implying a write operation, but lacks details on permissions, idempotency, error handling, or what 'state' refers to (e.g., memory, file, database). This leaves significant gaps in understanding how the tool behaves beyond its basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which should cover return values), no annotations, and low schema coverage, the description is minimally adequate. It specifies the resource being saved but lacks details on behavior, usage context, and parameter specifics, making it incomplete for safe and effective use without additional documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description must compensate. It mentions 'API endpoints (method, path, summary)', which hints at the structure of the 'routes' parameter, adding some meaning beyond the schema's generic object array. However, it doesn't fully explain the expected format or constraints, leaving ambiguity for the agent.
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 ('Saves') and the resource ('API endpoints (method, path, summary) to state'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'save_database_plan' or 'save_test_plan' beyond the resource type, which prevents a perfect score.
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, such as other 'save_' tools or how it relates to operations like 'initialize_project'. There's no mention of prerequisites, exclusions, or specific contexts for usage, leaving the agent with minimal direction.
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 the tool creates files and folders, implying a write operation, but doesn't disclose behavioral traits such as whether it overwrites existing files, requires specific permissions, handles errors, or has side effects. The mention of 'Defaults to current directory' adds minimal context, but key behavioral details are missing for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: a single sentence that directly states the tool's action and key detail. Every word earns its place, with no redundancy or unnecessary elaboration, making it efficient and easy to understand.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which likely covers return values), the description doesn't need to explain outputs. However, as a mutation tool with no annotations and minimal parameter documentation, it should provide more context on behavior and usage. The description is adequate for basic understanding but lacks depth for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the input schema: it explains that the 'root_path' parameter defaults to the current directory ('.'), which is implied by 'Defaults to current directory.' This clarifies the parameter's purpose and default behavior. With 0% schema description coverage and only one parameter, the description effectively compensates, though it could specify path format or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Creates the folder structure and pyproject.toml configured for uv.' It specifies both the action (creates) and the resources (folder structure, pyproject.toml), and mentions the technology (uv). However, it doesn't explicitly differentiate from sibling tools, which are unrelated file/plan operations, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some implied usage context: 'Defaults to current directory.' This suggests when to use the default parameter, but it doesn't offer explicit guidance on when to use this tool versus alternatives (e.g., other project initialization methods) or any prerequisites. The sibling tools are unrelated, so no direct comparison is needed, but general guidance is lacking.
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 burden. It discloses the priority-based behavior, which is useful context beyond the input schema. However, it doesn't cover other traits like error handling, return format details (though output schema exists), or whether it's idempotent or state-changing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences that front-load the core purpose and add essential priority context. Every word earns its place, with no wasted text or structural issues.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, output schema provided), the description is complete enough for an agent to understand what it does and the priority order. It could slightly improve by hinting at the return type or error cases, but the output schema mitigates this gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema already documents this fully. The description doesn't need to add parameter details, and it appropriately avoids redundancy, earning a baseline score above 3 for not cluttering with unnecessary info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Returns') and resource ('first unbuilt item'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'save_route_plan' or 'write_component_file' which might also relate to project tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by specifying priority order ('Models -> Routes -> Tests'), which suggests when to use it for task sequencing. But it lacks explicit guidance on when not to use it or alternatives among siblings, such as whether to use this for planning vs. execution tasks.
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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