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yingsf

pycharm-code-quality-mcp

by yingsf

jetbrains_inspect_files

Inspect 1-200 absolute file paths using PyCharm's JetBrains inspections to identify code quality issues and return problem ranges.

Instructions

Inspect 1 to 200 absolute file paths with PyCharm's built-in JetBrains inspections via the local JetBrains MCP Server. Reuses one MCP session for all files; a single file failure does not abort the others. Returns inspection problems (1-based ranges).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
timeout_msNo
errors_onlyNo
project_rootNo
file_absolute_pathsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden. It discloses the file count limit, session reuse, non-abort behavior on file failure, and output format (inspection problems with 1-based ranges). It does not explicitly state read-only nature or permissions, but covers key behavioral traits.

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—two sentences that front-load the core purpose and include key behavioral notes. Every sentence adds value without redundancy.

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 absence of annotations and 0% schema coverage, the description is reasonably complete for core usage but lacks parameter details for timeout_ms, errors_only, and project_root. The existence of an output schema mitigates the need to describe return format, but the missing parameter semantics reduce completeness.

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%, yet the description only elaborates on 'file_absolute_paths' (noting they must be absolute). The other parameters (timeout_ms, errors_only, project_root) are left completely unexplained, forcing the agent to infer from names alone. This is insufficient compensation for missing schema 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 clearly states the action ('inspect'), the resource ('absolute file paths'), and the mechanism ('PyCharm's built-in JetBrains inspections via local JetBrains MCP Server'). It distinguishes from sibling tools like jetbrains_inspect_git_changes by specifying file paths rather than git changes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for inspecting specific file paths (1-200) and mentions session reuse and independent file failure handling, but does not explicitly state when to avoid this tool in favor of alternatives like code_quality_status or code_quality_analyze_git_changes. However, the context provides sufficient differentiation via sibling names.

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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