codecity-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool addresses a distinct aspect of codebase analysis: structure, file summaries, dependency graph, and complexity hotspots. There is no overlap in their purposes, making selection unambiguous.
Naming Consistency5/5All tool names follow a consistent get_<noun> pattern, with clear resource names (repo_structure, file_summary, dependency_graph, complexity_hotspots). The naming is uniform and predictable.
Tool Count5/5With 4 tools, the set is well-scoped for a code analysis server. Each tool covers a core need and none are redundant, making the count appropriate.
Completeness4/5The server covers the main exploration workflows: orienting via structure, inspecting files via summaries, understanding dependencies, and identifying complex areas. Missing full file content retrieval is a minor gap since summaries include excerpts.
Average 4/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It honestly describes the heuristic and purpose but does not mention if the operation is read-only, how files are traversed, or any potential error modes. It also omits return format, though that is partially covered by the purpose.
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 states the purpose and heuristic without extraneous words. Every part contributes to understanding.
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?
For a simple tool with no output schema, the description conveys the core behavior (ranking files) and the criteria used. It could be more explicit about the return format (e.g., a list of file paths with scores), but the given information is largely sufficient for a basic understanding.
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%: both repoPath and limit have descriptive schemas. The description adds no parameter-specific meaning beyond the heuristic context, so the baseline of 3 applies without extra credit.
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 ranks files using a size/complexity heuristic (function count, class count, lines of code). This specific verb-resource pairing distinguishes it from siblings like get_repo_structure and get_dependency_graph.
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 'so you know which parts of a codebase are worth looking at first' implies use for prioritizing code review, but it does not explicitly state when to use this tool versus alternatives or mention exclusions. Sibling tools are not referenced.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses key behavior: it resolves relative imports only (ignoring other import types), and it returns internal edges and external package names separately. This gives the agent a good mental model, though it omits potential limitations like error handling or performance.
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 two concise sentences that front-load the action and resource, include necessary output details, and contain no superfluous words.
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?
For a one-parameter, no-output-schema tool, the description explains the behavior, input (via schema), and output structure. It sufficiently covers internal vs external dependency classification but does not address edge cases like invalid paths or unresolved imports.
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 already provides a clear description for the only parameter, repoPath, covering 100% of parameters. The tool description adds no extra parameter semantics, so the baseline of 3 is appropriate.
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 that the tool builds a dependency graph by resolving relative imports, which is a specific and unambiguous action. It distinguishes itself from sibling tools like get_repo_structure and get_file_summary by focusing on import relationships and return structure.
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 usage context is implied from the description (use when you need dependency insights), but there is no explicit when-to-use or when-not-to-use guidance, nor any mention of alternative tools. This leaves the agent to 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.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It states the output (tree plus totals) but does not mention side effects, read-only nature, recursive behavior, or performance implications. Adequate for a simple read operation, but leaves some ambiguity.
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?
Two sentences, front-loaded with the primary function and followed by a usage recommendation. Every word earns its place; no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity tool with a single parameter and no output schema, the description fully covers what the tool does and when to use it. The mention of 'plus totals' clarifies the return content, making it complete for an orientation utility.
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% for the single parameter repoPath, and the description adds no additional nuance beyond what the schema already provides. Baseline of 3 applies because the schema fully documents the parameter.
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 returns a folder/file tree plus aggregate totals (file count, lines of code). It distinguishes itself from sibling tools by positioning it as an orientation tool before deeper analysis.
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?
Explicitly advises to 'Use this first to get oriented before drilling into individual files,' giving a clear usage context. Does not name sibling alternatives explicitly, but the guidance implies when it is appropriate relative to deeper analysis tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavior. It discloses what the tool returns and assures efficiency by not reading the whole file. It doesn't mention potential side effects or limitations (e.g., file size limits), but for a read-only summary tool, this is reasonably transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the action and result. Every word adds value, and it avoids redundant phrasing.
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?
For a simple tool with two well-described parameters and no output schema, the description covers the key return elements and the practical benefit. It could mention edge cases or how the excerpt is selected, but the provided details are sufficient for an agent to understand and invoke the tool.
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 fully describes both parameters with 100% coverage, including the distinction between repoPath and filePath. The description adds no additional parameter detail beyond what the schema provides, so the baseline of 3 is appropriate.
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 returns a structural summary of a single file, enumerating specific contents (line count, function/class count, imports, excerpt). This distinguishes it from sibling tools like get_repo_structure (whole repository) and get_dependency_graph (relationships).
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 'without needing to read the whole file' gives a clear usage context: use this for a quick overview rather than fetching entire file contents. However, it doesn't explicitly state when not to use it or mention alternatives, though the sibling tool names provide implicit contrast.
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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- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
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