FileScopeMCP
FileScopeMCP
あなたのAIはすでにコーディングの方法を知っています。今度はあなたのコードベースを知る番です。
FileScopeMCPはあなたのコードを監視し、すべてのファイルの重要度をランク付けし、すべての依存関係をマッピングし、AIが生成した要約をバックグラウンドで常に最新の状態に保ちます。LLMが「このファイルは何をするもの?」と尋ねたとき、ソースコードを読み込ませることなく、正確な回答を得ることができます。
Claude Code、Cursor AI、またはスタンドアロンのデーモンとして動作します。標準で12の言語をサポートしています。
主な機能
重要度ランキング — 依存関係の数、エクスポート内容、配置場所に基づいて、すべてのファイルが0〜10でスコアリングされます。LLMは重要なファイルを優先的に認識します。
依存関係マッピング — Python、JS/TS、C/C++、Rust、Go、Ruby、Lua、Zig、PHP、C#、Javaにわたる双方向のインポート追跡。循環依存関係も検出します。
常に最新 — ファイル監視機能とセマンティックな変更検知により、メタデータが自動的に更新されます。TS/JSはASTレベルの差分検知、それ以外はLLMによる分析を行います。実際に変更されたものだけを再処理します。
LLMブローカー — バックグラウンドプロセスが、llama.cppの llama-server(またはOpenAI互換のHTTP API)を通じてすべてのAI作業を調整します。優先順位付きキューにより、対話型クエリがバックグラウンド処理よりも優先されます。単一のGPUで動作します。
Nexusダッシュボード — localhost:1234 で動作するWeb UI。すべてのリポジトリにわたるコードベースを視覚的に探索できます。インタラクティブな依存関係グラフ、ファイル詳細パネル、ライブブローカーアクティビティ、リポジトリごとの健全性監視を提供します。
Related MCP server: GonMCPtool
クイックスタート
git clone https://github.com/admica/FileScopeMCP.git
cd FileScopeMCP
./build.sh # installs deps, compiles, registers with Claude Code以上です。任意のプロジェクトでClaude Codeセッションを開くと、FileScopeMCPが自動的に初期化されます。以下を試してください:
find_important_files(limit: 5)
status()AIによる要約が必要ですか? ./setup-llm.sh を実行して、プラットフォーム固有のガイドに従いllama.cppの llama-server をセットアップしてください。詳細は docs/llm-setup.md を参照してください。これを行わなくても、他の機能はすべて動作します。
プロジェクトの .gitignore に以下を追加してください:
.filescope/
.filescope-daemon.logMCPツール
ツール | 説明 |
| 重要度スコアの高いファイル |
| ファイルに関するすべての情報:要約、概念、変更の影響、依存関係、鮮度 |
| 重要度付きのファイルツリー全体 |
| 循環依存関係チェーンの検出 |
| ブローカー接続、キューの深さ、LLMの進捗、監視状態 |
| コードベース全体をLLM処理キューに追加 |
| 別のプロジェクトを指定 |
| 手動オーバーライド |
| 追跡対象からファイルやパターンを除外 |
| 特定のファイルに関連する循環依存関係 |
Nexusダッシュボード
npm run nexus # opens at http://localhost:1234マシン上のすべてのFileScopeMCPリポジトリに接続する読み取り専用のWebダッシュボードです:
プロジェクトビュー — 重要度によるヒートカラーと鮮度インジケーター付きのファイルツリー。ファイルをクリックすると詳細メタデータを表示
依存関係グラフ — インタラクティブなCytoscape.jsによる可視化。ディレクトリによるフィルタリングやノードクリックによる調査が可能
システムビュー — ライブブローカー状態、リポジトリごとのトークン使用量、ストリーミングアクティビティログ
設定 — 表示するリポジトリの管理、ブラックリストからの削除や復元
.filescope/data.db ディレクトリをスキャンしてリポジトリを自動検出します。設定は不要です。
仕組み
Your code changes
→ file watcher picks it up
→ AST diff classifies the change (exports? types? body only?)
→ importance scores recalculated
→ staleness cascades to dependents (only if exports/types changed)
→ LLM broker regenerates summaries, concepts, change impact
→ your AI's next query gets fresh answersすべてはプロジェクトごとの .filescope/data.db(SQLite、WALモード)に保存されます。ブローカーは ~/.filescope/broker.sock のUnixソケットを介して、すべてのリポジトリのLLM作業を調整します。
ドキュメント
ドキュメント | 内容 |
llama.cpp / llama-serverのインストール(ローカル、WSL2+Windows、リモート) | |
プロジェクトごとの設定、ブローカー設定、除外パターン | |
Claude Code、Cursor AI、デーモンモードのセットアップ | |
よくある問題と解決策 | |
依存関係検知、重要度計算式、カスケードエンジン、ストレージ |
ライセンス
Copyright (c) 2026 admica. All rights reserved. LICENSE を参照してください。
Available Tools
14 toolscreate_file_treeC
Create or load a file tree configuration
| Name | Required | Description | Default |
|---|---|---|---|
| baseDirectory | Yes | Base directory to scan for files | |
| filename | Yes | Name of the JSON file to store the file tree |
TDQS
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 hints at creation and loading behaviors but doesn't disclose critical details: whether it overwrites existing files, requires specific permissions, handles errors (e.g., invalid directories), or returns any output. For a tool that likely involves file system operations, this lack of transparency is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action ('Create or load'), though it could be more specific. The structure is straightforward, but the brevity contributes to vagueness rather than clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of file system operations and the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'create' involves (e.g., scanning, JSON generation) or 'load' entails (e.g., reading from disk, validation). For a tool with two required parameters and no structured output, more behavioral and result context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for 'baseDirectory' and 'filename'. The description adds no additional meaning beyond the schema, such as format examples (e.g., absolute vs. relative paths) or usage context. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, but no extra value is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Create or load a file tree configuration' states a purpose but is vague about what 'create' and 'load' entail. It mentions 'file tree configuration' but doesn't specify if this involves scanning directories, generating JSON, or both. Compared to siblings like 'list_files' or 'select_file_tree', it lacks clear differentiation in scope or operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. With siblings like 'list_files', 'select_file_tree', and 'list_saved_trees', the description doesn't indicate if this is for initial setup, persistence, or retrieval of configurations. There's no mention of prerequisites, such as whether the base directory must exist or the filename must be unique.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
debug_list_all_filesB
List all file paths in the current file tree
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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 action ('List') but doesn't describe what 'current file tree' means, whether this requires prior setup (e.g., via 'select_file_tree'), or the format of the output (e.g., a list of paths). This leaves significant gaps for a tool with no 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.
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 any wasted words. It is front-loaded and appropriately sized for a simple tool, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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, no output schema, no annotations), the description is minimally adequate. However, it lacks context about dependencies (e.g., relation to 'select_file_tree') and output details, which could be important for an agent to use it correctly in this server's ecosystem.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate, earning a baseline score of 4 for adequately handling the lack of parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('all file paths in the current file tree'), making the purpose unambiguous. However, it doesn't explicitly distinguish itself from the sibling tool 'list_files', which suggests similar functionality, 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.
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 like 'list_files' or 'find_important_files'. It lacks context about prerequisites, such as needing a selected file tree, or exclusions, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_file_treeC
Delete a file tree configuration
| Name | Required | Description | Default |
|---|---|---|---|
| filename | Yes | Name of the JSON file to delete |
TDQS
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 'Delete', implying a destructive mutation, but doesn't clarify if this is irreversible, requires specific permissions, has side effects (e.g., affecting related files), or provides confirmation. This is a significant gap for a destructive 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.
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's front-loaded and appropriately sized, with every word contributing to clarity, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's destructive nature, no annotations, and no output schema, the description is incomplete. It lacks critical context such as safety warnings, return values, or error handling, which is insufficient for a mutation tool that deletes configurations, especially compared to siblings that handle file trees non-destructively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the parameter 'filename' documented as 'Name of the JSON file to delete'. The description doesn't add any meaning beyond this, such as file format details or constraints, so it meets the baseline of 3 where the schema handles the parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete') and the resource ('a file tree configuration'), which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_saved_trees' or 'select_file_tree', which might involve file tree configurations without deletion, so it lacks sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. For example, it doesn't mention prerequisites (e.g., needing an existing file tree), exclusions, or comparisons to siblings like 'create_file_tree' or 'list_saved_trees', leaving the agent without contextual usage cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find_important_filesC
Find the most important files in the project
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of files to return (default: 10) | |
| minImportance | No | Minimum importance score (0-10) |
TDQS
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 'most important files' but doesn't explain how importance is determined (e.g., based on scores from other tools like 'get_file_importance'), what the output format is, or any performance considerations like rate limits. This leaves significant gaps for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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's front-loaded and appropriately sized, though it could benefit from more detail to improve clarity and completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (involves ranking or filtering based on importance), lack of annotations, and no output schema, the description is insufficient. It doesn't explain how importance is defined, what the output includes (e.g., file names, scores), or how it interacts with sibling tools like 'get_file_importance'. More context is needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting 'limit' and 'minImportance' parameters. The description adds no additional semantic context beyond implying importance-based filtering, which aligns with 'minImportance' but doesn't elaborate further. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose ('Find the most important files') with a specific verb and resource, but it's vague about what constitutes 'important' and doesn't differentiate from siblings like 'get_file_importance' or 'list_files'. It provides basic direction 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.
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 'get_file_importance' (which might retrieve importance scores) or 'list_files' (which might list all files). The description implies a ranking or filtering based on importance, but it doesn't specify contexts or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_diagramC
Generate a Mermaid diagram for the current file tree
| Name | Required | Description | Default |
|---|---|---|---|
| layout | No | ||
| maxDepth | No | Maximum depth for directory trees (1-10) | |
| minImportance | No | Only show files above this importance (0-10) | |
| outputFile | No | Optional output file name for the diagram | |
| outputFormat | No | Output format (mmd or png) | |
| showDependencies | No | Whether to show dependency relationships | |
| style | Yes | Diagram style |
TDQS
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 generates a diagram but doesn't explain what happens after generation (e.g., where the diagram is saved, if it's displayed or returned as data, or any side effects like file creation). For a tool with 7 parameters and no output schema, this lack of behavioral context is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Generate a Mermaid diagram for the current file tree.' It's front-loaded with the core purpose, has zero waste, and is appropriately sized for the tool's complexity. Every word earns its place, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, nested objects, no output schema, and no annotations), the description is incomplete. It doesn't explain the output (e.g., whether it returns a file path, diagram data, or nothing), behavioral aspects like side effects, or usage context relative to siblings. For a diagram-generation tool with rich parameters, this minimal description leaves too many gaps for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is high at 86%, with most parameters well-documented in the schema (e.g., 'maxDepth' has description 'Maximum depth for directory trees (1-10)'). The description adds no parameter-specific information beyond what the schema provides, so it meets the baseline of 3 for high coverage but doesn't compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate a Mermaid diagram for the current file tree.' It specifies the verb ('Generate'), resource ('Mermaid diagram'), and scope ('current file tree'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'create_file_tree' or 'list_files,' which could also involve file tree 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.
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 doesn't mention sibling tools like 'create_file_tree' (which might create a textual representation) or 'list_files' (which might list files without a diagram), nor does it specify prerequisites or contexts for use. The agent must infer usage from the purpose alone, which is insufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_file_importanceC
Get the importance ranking of a specific file
| Name | Required | Description | Default |
|---|---|---|---|
| filepath | Yes | The path to the file to check |
TDQS
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 action ('Get') but does not disclose behavioral traits such as whether this is a read-only operation, if it requires specific permissions, what the output format looks like, or any rate limits. This leaves significant gaps for an agent to understand how to invoke it correctly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It does not explain what 'importance ranking' means, the return format, or how it differs from sibling tools. For a tool with no structured data to supplement it, this leaves the agent with insufficient context to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the parameter 'filepath' clearly documented in the schema. The description does not add any meaning beyond what the schema provides (e.g., it doesn't explain what 'importance ranking' entails or format details), so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('importance ranking of a specific file'), making the purpose understandable. However, it does not explicitly differentiate from sibling tools like 'find_important_files' or 'recalculate_importance', which prevents a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 'find_important_files' (which might list important files) or 'recalculate_importance' (which might update rankings). There is no mention of prerequisites, context, or exclusions, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_file_summaryC
Get the summary of a specific file
| Name | Required | Description | Default |
|---|---|---|---|
| filepath | Yes | The path to the file to check |
TDQS
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 only states the action without detailing aspects like read-only nature, potential errors (e.g., file not found), response format, or any side effects, leaving significant gaps for an AI agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with zero waste, clearly front-loading the core action. It is appropriately sized for a simple tool, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what a 'summary' entails, potential return values, or behavioral traits, which are crucial for a tool with no structured output documentation, leaving the agent with insufficient context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no meaning beyond the input schema, which has 100% coverage and fully documents the 'filepath' parameter. With high schema coverage, the baseline is 3, as the schema handles the parameter documentation adequately without extra detail from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Get') and resource ('summary of a specific file'), which is clear but basic. It doesn't differentiate from sibling tools like 'get_file_importance' or 'read_file_content', which also retrieve file metadata/content, leaving the exact purpose somewhat vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. With siblings like 'get_file_importance' and 'read_file_content' that might serve similar retrieval purposes, the description lacks context on specific use cases, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_filesB
List all files in the project with their importance rankings
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states what the tool does, not behavioral traits. It doesn't disclose if this is a read-only operation, potential performance impacts, rate limits, or authentication needs. For a list operation with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('List all files') and adds key detail ('with their importance rankings'). There is no wasted text, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states the purpose but lacks context on behavior, output format, or usage guidelines. For a simple list tool, this might suffice, but it doesn't fully compensate for the absence of annotations or output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds no parameter info, which is appropriate here. Baseline is 4 for zero parameters, as the schema fully handles the lack of inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and resource 'files in the project', specifying they come with 'importance rankings'. It distinguishes from siblings like 'find_important_files' (which likely filters) and 'debug_list_all_files' (which may include debug info), though not explicitly named. However, it doesn't fully differentiate from 'list_saved_trees' (which lists trees, not files), 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.
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 'find_important_files' (for filtered results) or 'debug_list_all_files' (for detailed output). The description implies it lists all files, but doesn't specify contexts like initial exploration or when importance data is needed, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_saved_treesB
List all saved file trees
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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 action ('List all saved file trees') but doesn't describe what 'saved file trees' means, how results are returned (e.g., format, pagination), or any constraints like permissions or rate limits. This leaves significant gaps 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded and directly communicates the core functionality, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'saved file trees' are, how results are structured, or any behavioral traits like safety or performance. For a tool with no structured data to rely on, this leaves the agent with insufficient context to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter details, so it meets the baseline expectation for a parameterless tool. No additional semantic value is required or provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List all saved file trees' clearly states the verb ('List') and resource ('saved file trees'), making the tool's purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_files' or 'debug_list_all_files', 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.
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 like 'list_files' or 'debug_list_all_files'. It lacks context about prerequisites, timing, or exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
read_file_contentC
Read the content of a specific file
| Name | Required | Description | Default |
|---|---|---|---|
| filepath | Yes | The path to the file to read |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. While 'Read' implies a read-only operation, it doesn't disclose important behavioral traits like file size limits, encoding handling, error conditions (e.g., missing files), or performance characteristics. The description is minimal and lacks operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a simple tool with one parameter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read operation with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns (e.g., raw text, binary data, structured content) or address potential complexities like large files or permission issues. Given the lack of structured metadata, more descriptive context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'filepath' parameter clearly documented. The description doesn't add any parameter-specific information beyond what the schema provides, so it meets the baseline of 3 where the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Read') and resource ('content of a specific file'), making the tool's purpose immediately understandable. It distinguishes from siblings like 'list_files' (which lists files) or 'get_file_summary' (which provides summaries), though it doesn't explicitly mention these distinctions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. With siblings like 'get_file_summary' or 'list_files', there's no indication whether this tool should be preferred for raw content retrieval or if it has specific use cases compared to other file-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
recalculate_importanceB
Recalculate importance values for all files based on dependencies
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but provides minimal behavioral context. It states the operation recalculates values 'for all files', implying a batch mutation, but doesn't disclose permissions needed, whether it's destructive to existing data, execution time, or error handling. This is 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core action and scope, making it easy to parse. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., side effects, permissions), expected output, or error conditions. The tool's complexity (recalculating for all files) warrants more context than provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds no parameter details, which is appropriate. Baseline is 4 for zero parameters, as there's nothing to compensate for.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Recalculate') and target resource ('importance values for all files'), with a specific criterion ('based on dependencies'). It distinguishes from siblings like 'get_file_importance' (read-only) and 'set_file_importance' (manual setting), but doesn't explicitly name them. Purpose is specific and non-tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. It doesn't mention prerequisites (e.g., after dependency changes), exclusions, or compare to siblings like 'find_important_files' or 'set_file_importance'. Usage context is implied only by the action 'recalculate'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
select_file_treeC
Select an existing file tree to work with
| Name | Required | Description | Default |
|---|---|---|---|
| filename | Yes | Name of the JSON file containing the file tree |
TDQS
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 mentions 'select' but doesn't disclose behavioral traits such as whether this loads the tree into memory, sets a default context, requires specific permissions, or has side effects. The description is minimal and lacks operational details needed for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with zero waste: 'Select an existing file tree to work with'. It's appropriately sized for the tool's apparent simplicity, though this conciseness may contribute to gaps in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'select' entails operationally, what happens after selection (e.g., sets context for other tools), or the return value. For a tool with one parameter and no structured behavioral hints, the description should provide more context to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'filename' documented as 'Name of the JSON file containing the file tree'. The description adds no additional meaning beyond this, as it doesn't mention parameters at all. With high schema coverage, the baseline score of 3 is appropriate, as the schema adequately defines the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Select an existing file tree to work with' states a clear verb ('select') and resource ('file tree'), but it's vague about what 'select' means operationally. It distinguishes from siblings like 'create_file_tree' by specifying 'existing', but doesn't clarify how this differs from 'list_saved_trees' or other file-related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 implies it's for selecting an existing file tree, but doesn't specify prerequisites (e.g., must have saved trees), exclusions, or direct comparisons to siblings like 'list_saved_trees' or 'create_file_tree'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
set_file_importanceC
Manually set the importance ranking of a specific file
| Name | Required | Description | Default |
|---|---|---|---|
| filepath | Yes | The path to the file to update | |
| importance | Yes | The importance value to set (0-10) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a manual setting operation, implying mutation, but doesn't address whether this overwrites existing values, requires specific permissions, has side effects, or provides confirmation of success. For a mutation tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 any wasted words. It's appropriately sized and front-loaded with the core action, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what happens on success/failure, whether changes are reversible, or how this interacts with sibling tools like 'recalculate_importance'. For a tool that modifies system state, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters ('filepath' and 'importance') clearly documented in the schema. The description adds no additional parameter semantics beyond what the schema already provides, such as format examples or edge cases, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('manually set') and target ('importance ranking of a specific file'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_file_importance' (read) or 'recalculate_importance' (automatic calculation), which would be needed for 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.
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 like 'recalculate_importance' (automatic calculation) or 'get_file_importance' (read-only). It also doesn't mention prerequisites such as file existence or permissions, 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.
set_file_summaryC
Set the summary of a specific file
| Name | Required | Description | Default |
|---|---|---|---|
| filepath | Yes | The path to the file to update | |
| summary | Yes | The summary text to set |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool sets a file summary, implying a mutation operation, but fails to address critical aspects like permissions required, whether the operation is idempotent, error handling, or side effects. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with zero wasted words. It front-loads the core purpose efficiently, making it easy to parse and understand quickly without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's mutation nature, lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral traits like error conditions, response format, or integration with sibling tools, leaving the agent with insufficient context for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting both parameters ('filepath' and 'summary'). The description adds no additional semantic context beyond what the schema provides, such as format examples or constraints, so it meets the baseline for adequate but minimal value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Set') and the target resource ('summary of a specific file'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'get_file_summary', which retrieves rather than sets file summaries, leaving room for improvement in sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 doesn't mention prerequisites (e.g., file existence), exclusions, or related tools like 'get_file_summary' for retrieval, leaving the agent without contextual usage cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
14 tool updates
v1.0.0- First observed
create_file_tree - First observed
debug_list_all_files - First observed
delete_file_tree - First observed
find_important_files - First observed
generate_diagram - First observed
get_file_importance - First observed
get_file_summary - First observed
list_files - First observed
list_saved_trees - First observed
read_file_content - First observed
recalculate_importance - First observed
select_file_tree - First observed
set_file_importance - First observed
set_file_summary
TDQS
Scored across 14 tools
Every tool has a clearly distinct purpose with no ambiguity. Tools like 'create_file_tree', 'delete_file_tree', and 'select_file_tree' handle tree management, while 'read_file_content', 'get_file_summary', and 'set_file_summary' focus on file content operations. The separation between listing functions ('debug_list_all_files', 'list_files', 'list_saved_trees') and importance calculations ('get_file_importance', 'set_file_importance', 'recalculate_importance') is well-defined, preventing misselection.
All tool names follow a consistent verb_noun pattern with snake_case throughout. Verbs like 'create', 'delete', 'list', 'get', 'set', 'read', 'find', 'generate', 'select', and 'recalculate' are used predictably with corresponding nouns. There are no deviations in naming conventions, making the tool set highly readable and predictable.
With 14 tools, the count is well-scoped for managing file trees and analyzing file importance in a project. Each tool earns its place by covering distinct aspects such as tree configuration, file listing, content access, importance ranking, and diagram generation. This number is neither too sparse nor overwhelming, fitting the server's purpose effectively.
The tool surface provides complete CRUD/lifecycle coverage for file tree management and file analysis. It includes creation, selection, listing, and deletion of trees, along with operations for reading, summarizing, and setting importance for files. Tools like 'recalculate_importance' and 'generate_diagram' add advanced functionality, leaving no obvious gaps that would cause agent failures in this domain.
Maintenance
Related MCP Connectors
Codebase graphs, caller impact analysis, and recorded project context for AI coding agents.
Coding agents in multi-service codebases routinely rebuild existing helpers, trust stale type definitions, and modify API contracts without knowing who consumes them. Carrick solves this by indexing your entire TypeScript ecosystem across service and repository boundaries. By integrating deeply with the TypeScript compiler, Carrick traces every route, type, and cross-service call while recording function behaviour so agents search by intent rather than name. Delivered via MCP for AI agents and LSP for IDEs, Carrick ensures models see existing endpoints and utilities before generating new code. The scanner is source-available and runs from your CLI or CI pipeline.
Deterministic context layer for your codebase: change impact, blast radius, answers with receipts.
Give your AI agent a persistent map of your project's structure, dependencies, and bugs.
Related MCP Servers
- FlicenseBqualityDmaintenanceA Model Context Protocol server that helps AI code editors locate TypeScript symbol definitions in codebases, particularly useful for finding original definitions of imported symbols and classes.119 npm-
- AlicenseCqualityDmaintenanceA TypeScript-based Model Context Protocol toolkit that enables AI to interact with code files, manage translations, build projects, and search for files and code content.339 npm5MIT
- AlicenseNot gradedqualityDmaintenanceA structural codebase indexer that exposes 18 tools via the Model Context Protocol for AI-assisted code navigation, enabling efficient querying of functions, classes, dependencies, and call chains without reading entire files.63AGPL 3.0
- AlicenseNot gradedqualityFmaintenanceEnables Claude Code to query a TypeScript dependency graph and retrieve the minimal set of files needed for code review, implementation, or debugging.MIT