Codix Build MCP

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct domain and output: project analysis, stack recommendation, architecture, templates, API generation, database schema, security, deployment, etc. Even the 'generate' tools are clearly differentiated by their object (prompt, API, docs). No two tools appear to do the same thing.
Naming Consistency3/5
All tools share the codix prefix and lowercase dot-separated structure, but the second segment mixes verbs (analyze, get, generate) with nouns/adjectives (schema, checklist, guide, smart). This weakens the consistency of the verb_noun pattern, though it remains readable.
Tool Count4/5
At 16 tools, the server is slightly above the typical 3-15 range, but the broad development lifecycle it covers justifies the count. The tools are not redundant, so the size feels reasonable rather than bloated.
Completeness4/5
The tool surface covers the major phases of a project build: analysis, stack, architecture, templates, API, database, security, docs, deploy, debug, marketplace, and cost optimization. Minor gaps exist, such as a dedicated testing tool or direct code scaffolding, but these can be worked around via the API test plan and template commands.
Average 3/5 across 16 of 16 tools scored. Lowest: 2.1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 4 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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.json to 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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose effects, side effects, or prerequisites, but it states only the action ('apply') without explaining what changes occur, whether files are modified, or if any setup is required.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise but under-specified. While it is a single short sentence, it omits critical details, making it more of an under-specification than a well-structured summary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a potentially mutating tool with no output schema and no annotations. The description fails to explain what happens after applying, what the result looks like, or any constraints, making it completely inadequate for safe invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the tool description does not mention any of the three parameters (platform, brandName, primaryColor) or their role in the design system, leaving the agent without any guidance on how to fill them.
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 applies a design system, with specific elements (tokens, components, mobile UX rules). It is a distinct verb+resource pairing, though it doesn't specify the target or context of application.
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, nor any exclusions or prerequisites. The description is a single standalone phrase without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It implies a filtering/selection behavior ('return only'), but does not disclose side effects, required prerequisites, or limitations. There is no mention of whether this is a read-only operation, what happens if no context matches, or how the 'smart' selection is performed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short sentence with no word waste, and it leads with the tool's purpose. However, it is under-specified to the point of being unhelpful, lacking any structured breakdown of parameters or usage context, so it does not earn a higher score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description must compensate for the missing behavioral and return-value details. It does not. For a tool with four parameters and a non-trivial task (selecting context chunks), this one-liner is incomplete, leaving major gaps in what the agent needs to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description adds no parameter-level meaning. It does not explain what 'brief', 'stack', 'include', or 'activeTask' mean or how they relate to the stated task. With four parameters and no additional information, the agent is left to infer parameter semantics from names alone, which is insufficient.
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 states a specific verb ('return') and resource ('context chunks needed for the active task'), which clearly distinguishes it from sibling tools like codix.stack.recommend or codix.prompt.generate. However, 'context chunks' is vague and does not specify what kind of context (e.g., code, files, data), so it stops short of a 5.
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 phrase 'for the active task' implies when to use it, but there is no explicit guidance on when not to use it or which alternative should be chosen instead. Sibling tools are listed, but no comparisons or exclusions are mentioned, leaving the agent without clear decision support.
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 disclosing behavior. It says 'generate guidance' but does not clarify whether this is a read-only operation, what side effects occur, or what the return format is. This is a significant transparency gap for a tool that could potentially interact with a project's files.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence with no wasted words, and it front-loads the primary action ('Generate database schema guidance'). However, it is under-specifying, omitting crucial information about parameters and usage, which makes it efficient but at the cost of completeness.
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 that there is no output schema, no annotations, and only sparse parameter schemas (two optional fields with an enum), the description alone must provide context about what the agent will receive and how parameters factor in. It does not, leaving the tool only minimally viable for actual use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not mention the 'database' or 'entities' parameters at all. The agent is left without any explanation of what these parameters mean, how they should be populated, or how they affect the generated guidance. The description entirely fails to compensate for the lack of schema descriptions.
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 'generate[s] database schema guidance' with a specific verb and resource, mentioning migrations, relations, and seeders. It differentiates from siblings like codix.api.generate by focusing on the database schema domain, though the word 'guidance' is slightly ambiguous (advisory vs. concrete output).
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 given on when to use this tool versus alternatives, and there are no prerequisites or exclusions mentioned. The description only states what the tool does without any context about suitable scenarios, making it difficult for an agent to decide 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.
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 says 'Generate... plan' but doesn't clarify whether this modifies files, returns a plan object, requires authentication, or has other side effects. This is a significant transparency gap for a tool that might scaffold code.
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 one concise sentence and is front-loaded with the main purpose. It lists multiple output artifacts efficiently. It loses a point because 'from resources' is vague and could be rephrased for clarity without adding length.
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 three parameters with no schema descriptions, no annotations, and no output schema, the description is far too sparse. It omits what 'resources' are, what auth/style choices mean, and what the generated output actually looks like. The sibling context suggests many similar generators, so more differentiation is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only references 'resources' (via 'from resources') but leaves 'auth' and 'style' completely unexplained. The enums for auth and style provide options but no semantic meaning, so the description adds minimal value beyond the schema.
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 names a specific verb ('Generate') and a clear resource ('API route/controller/service/validation/test plan'), which distinguishes it from sibling tools like docs.generate or prompt.generate. However, 'from resources' is ambiguous—it doesn't specify whether resources are file paths, resource names, or data models—so it's not a perfect 5.
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 usage guidance is provided beyond the implied purpose. The description does not state when to prefer this over alternatives, what inputs are required, or any prerequisites, leaving the agent to infer 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?
With no annotations supplied, the description carries the full burden of behavioral disclosure. It states the tool generates documentation content but does not disclose side effects (e.g., whether files are written), required permissions, or output format, which is insufficient for a generate 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, front-loaded sentence with no filler. It is efficient and to the point, though it is terse and leaves out important details.
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 three parameters, no annotations, and no output schema, a one-sentence description is insufficient. It fails to describe input semantics, expected output, or side effects, leaving significant ambiguity for an agent attempting to invoke the tool correctly.
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 does not explain any of the three parameters (projectName, sections, projectType). Parameter names and enum values provide some clues, but the description adds no semantic meaning and does not compensate for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') and resource ('documentation'), and indicates the output type ('outline and starter snippets'), making the core purpose clear. It does not explicitly differentiate from sibling tools like api.generate or template.get, but the focus on docs is evident.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. The description doesn't mention sibling tools, prerequisites, or exclusions, leaving the agent to infer usage solely from the name 'Generate documentation'.
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 must carry behavioral disclosure. It states 'suggest' implying a non-mutating advisory role, but does not describe return format, side effects, or any requirements. This is minimal for a tool with no safety annotations.
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, focused sentence with no filler words. However, it is arguably under-specified, though that is captured in other dimensions; as a sentence it is concise.
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?
For a tool with 3 parameters (2 enums), no annotations, and no output schema, the description is insufficient. It omits information about expected outputs, input semantics, and usage context, making it hard for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description mentions no parameters. It does not explain how 'stack,' 'budget,' or 'prompt' influence the optimization suggestions, offering no semantic value beyond the schema's enums.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'suggest' with the resource 'prompt-token and infrastructure cost optimizations,' making its function clear. It distinguishes itself from sibling tools like codix.stack.recommend or codix.project.analyze by focusing exclusively on cost optimization.
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, use cases, or exclusions, leaving the agent without clear selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavioral traits but only states the input-driven purpose. It does not mention whether the operation is read-only, what the output looks like, whether inputs are required, or any edge cases. The verb 'Recommend' suggests a non-mutating action, but otherwise transparency is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that directly states the tool's purpose and inputs. There is no filler or redundant elaboration, making it maximally concise.
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?
For a 4-parameter tool with no output schema and no annotations, the description is too sparse. It does not explain what the recommendation output contains, how to handle omitted parameters, or how inputs influence the result, leaving significant gaps for an agent trying to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description simply restates the four parameter names in a sentence without adding meaning about their enum values, optionality, or how they affect the recommendation. It provides no semantic value beyond the property names already present in the schema.
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 function: recommending a stack based on project type, budget, team level, and hosting target. The verb 'Recommend' and noun 'stack' are specific, and the listed inputs distinguish it from broader tools like architecture.get. It does not explicitly name sibling alternatives, so it misses the top 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 implies usage when a stack recommendation is needed but provides no explicit guidance on when to choose this tool over siblings like architecture.get or template.get. There are no exclusions, prerequisites, or alternative tool references, leaving the agent without clear decision criteria.
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 only states that it returns a checklist, without disclosing whether it is read-only, deterministic, or any side effects, which is a significant gap for a 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence, front-loaded with the primary action and resource. It has no redundant words, though it could be expanded with useful details without losing conciseness.
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, no annotations, and no output schema, the description is too minimal to fully understand behavior and output. It addresses the basic purpose but leaves critical context like output format and any constraints unstated, making it incomplete for an agent to confidently invoke.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions all three parameters (stack, features, compliance) but only as a list, without explaining how they influence the checklist or any additional semantics. The enums in the schema provide more detail than the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Return' and identifies the resource 'security checklist' with the input dimensions 'stack, features and compliance needs'. This clearly distinguishes it from sibling tools like architecture.get or template.get, although it doesn't explicitly name alternatives.
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 when to use: when a security checklist is needed based on stack, features, and compliance. However, it gives no explicit context about when not to use or alternative tools, so it only reaches the 'implied usage' level.
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 must fully disclose behavior. It only states 'Check readiness' without explaining what readiness means, what checks are performed, whether it is read-only, or what the output looks like. This is a minimal behavioral disclosure.
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, straightforward sentence with no unnecessary words. It is appropriately concise, though it sacrifices 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?
The tool has 5 optional parameters and no output schema, yet the description only gives a high-level goal. It misses what 'readiness' constitutes, what the agent should expect in return, or how to interpret results. This is insufficient for an AI agent to invoke the tool correctly in varied contexts.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the description adds no information about parameters like 'target', 'hasDocs', or 'projectType'. The description does not compensate for the schema's lack of descriptions, leaving parameter meaning entirely from field names and enums.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Check') and clearly identifies the resource/action: readiness for Codinfy Store / CodeCanyon packaging. This clearly distinguishes it from sibling tools like codix.license.inject or codix.deploy.guide.
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 implied use case is to verify packaging readiness for marketplaces, but there is no explicit when-to-use or alternative guidance. The description provides enough context for a reasonable agent to infer the tool's purpose, but lacks exclusions or comparisons.
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 core function but does not mention side effects, prerequisites, error handling, or whether the operation is safe/read-only. The verb 'map' implies analysis, but the description lacks sufficient context about what happens on invalid input or unrecognized errors.
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. It communicates the core purpose efficiently, earning its place.
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?
Without an output schema or annotations, the description is too sparse. It does not explain the expected return format, how to use the optional parameters, or what to do if the error is unclear. The tool's actual usage requires more context than provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, yet the description does not compensate. It only implies the 'error' parameter and entirely ignores 'stack' and 'environment'. The agent has no guidance on how to populate these optional parameters or what they affect, leaving significant ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'map' and identifies both the input (error message) and output (likely causes and verification commands). This clearly distinguishes it from sibling tools like codix.project.analyze or codix.stack.recommend, which have different scopes.
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 implicitly suggests use when you have an error message, but it does not explicitly state when to use this tool versus alternatives or provide any exclusions. Since sibling tools do not directly compete, the lack of explicit guidance is acceptable but not ideal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only mentions a design constraint ('without hardcoding secrets') but does not disclose side effects, authentication needs, rate limits, or output format. 'Generate' suggests a non-mutating operation, but this is not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of ten words, front-loaded with the primary action and resource. Every word earns its place, and there is no redundancy or fluff.
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 absence of annotations and output schema, the description should provide more context about inputs, outputs, and usage. It only states the tool generates instructions, leaving significant gaps for a 3-parameter tool. The description is inadequate for full contextual understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention any of the three parameters (stack, productType, offlineGraceHours). It adds no meaning beyond the raw schema, failing to compensate for the lack of parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Generate') and resource ('license integration instructions'), making the tool's purpose clear. The qualifier 'without hardcoding secrets' distinguishes it from sibling generation tools like codix.api.generate or codix.docs.generate.
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 the tool should be used when license integration instructions are needed, but it does not explicitly state when to use it vs alternatives or provide exclusions. No clear comparison with sibling tools is given, so guidance is only implicit.
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?
Without annotations, the description carries the transparency burden. The verb 'Return' implies a read-only operation, and it specifies the resource being returned. However, it does not disclose whether any authentication or special permissions are needed, or what the exact output structure looks like.
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, clear sentence with no wasted words. It is front-loaded with the purpose and effectively communicates the tool's function.
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?
There is no output schema, so the description should clarify what 'canonical architecture layers and build order' means and what the return format is. It does not explain the output structure or the meaning of 'canonical,' leaving significant ambiguity for an agent invoking this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only mentions 'project type and stack' generically, providing no additional meaning about the enum values or how they affect the returned architecture. The description adds minimal value beyond the schema's enum names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'canonical architecture layers and build order' for a given project type and stack. This is a specific verb+resource combination that distinguishes it from sibling tools like project analysis or stack recommendation.
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 any exclusions, prerequisites, or comparative context with siblings such as codix.stack.recommend or codix.project.analyze.
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 must disclose behavioral traits, but it only states the analysis action and outputs. It does not mention side effects, permissions, dependencies, or whether the tool modifies state. This leaves the agent with little insight into execution behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that clearly conveys the core purpose without redundant details. Every word contributes to the understanding of the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite a clear purpose, the tool lacks context for parameter usage, return structure, and behavioral nuances. With no annotations and no output schema, the one-line description is insufficient for an agent to invoke the tool confidently with correct parameters.
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 only hints at the 'brief' parameter by saying 'short project brief'. It does not explain the 'mustHave' or 'constraints' arrays, leaving 2 of 3 parameters semantically unexplained. The description adds minimal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Analyze'), the resource ('a short project brief'), and the outputs ('type, modules, risks, milestones and Smart Context chunks'). This distinguishes it from sibling tools, which focus on other tasks like generating prompts or recommending stacks.
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 when a project brief needs analysis, but it does not explicitly state when to choose this tool over siblings or mention any exclusions. No alternative tools are named, so the guidance is only implied.
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 disclosing behavior. It only mentions 'Smart Context Mode' without explaining what that entails, and omits any details about side effects, external calls, authentication, or output format. This is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys the core action and key differentiator. Every word earns its place, with no filler or redundant 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 four parameters, no output schema, and no annotations, the description is insufficiently complete. It doesn't explain what 'Smart Context Mode' means, how the input brief is used, what the output prompt looks like, or how parameters like output and targetAgent affect behavior. This is a substantial gap for effective tool usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameter meaning. It does not mention any of the four parameters (brief, output, maxTokens, targetAgent), nor does it imply them beyond the generic notion of a prompt generation. The description adds no value to the schema's parameter definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') and resource ('compact agent prompt') and further distinguishes the tool with 'Smart Context Mode instead of long pasted docs,' which differentiates it from sibling tools like codix.context.smart and codix.docs.generate. The purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'instead of long pasted docs' provides clear context that this tool is appropriate when a concise prompt is needed and long documentation should be avoided. While it doesn't name specific alternative tools or exclusions, it gives a clear situational cue.
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 is the sole source of behavioral info. It states it generates steps, implying a read-only guide, but does not specify output format, side effects, or any prerequisites. It could benefit from noting that it produces instructions rather than executing deployment.
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?
Description is a single sentence with no filler. Every element—verb and target list—contributes meaningful content, and it is front-loaded with the action.
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's simple two-parameter schema and no output schema, the description covers the basic purpose and target options. However, it omits the 'stack' parameter and any detail about the returned steps or when to use this tool, leaving moderate gaps for an agent.
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 descriptions are absent (0% coverage). The description lists all target enum values ('cPanel, VPS, Docker, ...'), which adds some semantic context for 'target', but it does not address the 'stack' parameter at all, leaving its meaning (e.g., laravel-livewire vs static) unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Generate' and clearly identifies the resource ('deployment steps') plus enumerates supported targets (cPanel, VPS, Docker, etc.), making it distinct from sibling tools like docs.generate or api.generate.
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 a clear function but does not give explicit 'when to use' guidance or contrast with alternatives. It implies usage for generating deployment instructions but lacks exclusions or scenarios.
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 is the sole source of behavioral transparency. It discloses the output nature (file tree, commands, notes) but does not mention side effects, error handling, prerequisites, or any security implications. For a simple retrieval tool, the description is adequate but not rich.
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, well-structured sentence that front-loads the action and output. It contains no fluff or redundancy; every word contributes to conveying the tool's purpose.
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 low complexity (one parameter, no output schema) and minimal annotations, the description covers the core purpose and expected return values. It could be more complete by hinting at when to use it relative to siblings, but this is a minor gap for a simple template retrieval tool.
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 schema for 'id' has an enum but no descriptions (0% coverage). The description compensates by mapping the parameter to example technologies (Laravel, Next.js, Flutter, WordPress, API, docs, and more), which helps an agent understand the meaning of the enum values and infer the expected input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Return') and resource ('project template') with detailed scope (file tree, commands, notes) and lists supported technologies. This clearly distinguishes it from sibling tools like codix.architecture.get or codix.stack.recommend.
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 enumerating template categories (Laravel, Next.js, Flutter, etc.), but it does not explicitly state when to use this tool over alternatives or provide any 'use when' / 'instead of' guidance. The intended context is somewhat inferable, but no exclusions or alternatives are mentioned.
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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