ellmos-clatcher-mcp
Officialellmos-clatcher-mcp
🇩🇪 ドイツ語版
Claude Patcher -- AIコーディングエージェントにネイティブでは備わっていないユーティリティツールを追加するMCPサーバーです。ファイルの修復、フォーマット変換、重複検出、一括操作などが可能です。
ellmos MCPファミリーの一部です:
サーバー | フォーカス | npm |
ファイルシステム操作、プロセス管理、インタラクティブセッション |
| |
コード解析、AST解析、インポート管理 |
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ellmos-clatcher-mcp | ユーティリティツール:修復、変換、検出、一括操作 |
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各サーバーは異なる領域をカバーしています。ワークフローに応じて、1つ、2つ、または3つすべてを使用してください。
ツール
ツール | 説明 |
| 壊れたJSONの修復:コメント、末尾のカンマ、シングルクォート、BOM/NULの削除 |
| エンコーディング問題の修正:BOM削除、二重エンコードされたUTF-8、cp1252アーティファクトの修正 |
| 二重エンコードによるドイツ語ウムラウトの破損を修正(例: |
| JSON、YAML、TOML、XML、CSV、INI間の変換 |
| コンテンツハッシュ(SHA256)による重複ファイルの検索(同一コンテンツでグループ化) |
| 2つのディレクトリの比較、またはスナップショットを取得して次回の呼び出し時に差分を表示 |
| 正規表現パターンを使用したファイルの一括リネーム(ドライランプレビュー付き) |
| ZIPアーカイブの作成、展開、またはリスト表示 |
| ファイルハッシュ(SHA256、MD5、SHA1、SHA512)の計算(オプションで検証可能) |
| BOM、末尾の空白の削除、改行コードの修正、NULバイトの削除 |
| コードファイル内の絵文字の検索 |
| テキストに対して正規表現パターンをテストし、グループを含むすべての一致を表示 |
破壊的なツールはすべてデフォルトでドライランモードになっており、変更を書き込むには明示的に dry_run: false を指定する必要があります。
Related MCP server: Code Buddy
インストール
Claude Code CLI
claude mcp add ellmos-clatcher-mcp -- npx ellmos-clatcher-mcpnpm (グローバル)
npm install -g ellmos-clatcher-mcp
claude mcp add ellmos-clatcher-mcp -- ellmos-clatcherソースから
git clone https://github.com/ellmos-ai/ellmos-clatcher-mcp.git
cd ellmos-clatcher-mcp
npm install
npm run build
node dist/index.jsテスト
npm test12のツールすべてをカバーする122のテスト(vitest)。
要件
Node.js >= 18
ライセンス
ellmos-ai エコシステム
このMCPサーバーは、ellmos-ai エコシステム(AIインフラストラクチャ、MCPサーバー、インテリジェントツール)の一部です。
MCPサーバーファミリー
サーバー | ツール | フォーカス | npm |
43 | ファイルシステム、プロセス管理、インタラクティブセッション |
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17 | コード解析、AST解析、インポート管理 |
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12 | ファイル修復、フォーマット変換、一括操作 |
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13 | AIアシスタント経由のn8nワークフロー管理 |
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AIインフラストラクチャ
プロジェクト | 説明 |
LLM用テキストベースOS — 109以上のハンドラー、373以上のツール、932以上のスキル | |
自動ルーティングと予算追跡を備えたプロバイダー中立のLLMオーケストレーション | |
軽量なエージェントメモリ、コネクタ、自動化インフラストラクチャ | |
セルフホスト型AI研究スタック(Ollama + n8n + Rinnsal + KnowledgeDigest) | |
Claude Code用自律エージェントチェーンフレームワーク | |
ミニマリストなデータベース駆動型LLM OSプロトタイプ(4関数、1テーブル) | |
LLMオペレーティングシステム用テストフレームワーク(7次元) |
デスクトップソフトウェア
パートナー組織である open-bricks は、AIネイティブなデスクトップアプリケーションをバンドルしています。これは、AI時代のために構築されたモダンなオープンソースソフトウェアスイートです。カテゴリには、ファイル管理、ドキュメントツール、開発者ユーティリティなどが含まれます。
免責事項 / Liability
Dieses Projekt ist eine unentgeltliche Open-Source-Schenkung im Sinne der §§ 516 ff. BGB. Die Haftung des Urhebers ist gemäß § 521 BGB auf Vorsatz und grobe Fahrlässigkeit beschränkt. Ergänzend gelten die Haftungsausschlüsse aus GPL-3.0 / MIT / Apache-2.0 §§ 15–16 (je nach gewählter Lizenz).
Nutzung auf eigenes Risiko. Keine Wartungszusage, keine Verfügbarkeitsgarantie, keine Gewähr für Fehlerfreiheit oder Eignung für einen bestimmten Zweck.
このプロジェクトは無償のオープンソース寄贈です。法的責任は故意および重大な過失に限定されます(ドイツ民法第521条)。自己責任でご利用ください。保証、メンテナンスの約束、可用性の保証、特定の目的への適合性については一切責任を負いません。
Available Tools
12 toolsarchiveB
Create, extract, or list ZIP archives.
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | Operation | |
| dry_run | No | Preview create/extract without changing files | |
| overwrite | No | Allow extraction to overwrite existing files | |
| extract_to | No | Extraction directory (for extract) | |
| archive_path | Yes | Path to the ZIP file | |
| source_paths | No | Files/directories to add (for create) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden of behavioral disclosure, but it only restates the action enum from the schema. It does not mention the dry_run default, overwrite safety, the need for source_paths during create, or what 'list' returns. The drug is minimal and adds nothing beyond the schema's existing param descriptions.
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 no redundancy. It is appropriately short, but it sacrifices enough detail that the tool feels under-specified for its complexity.
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 that there is no output schema and no annotations, the description should at least clarify action-dependent parameters, the meaning of dry_run, and the expected behavior of list. It provides none of this, leaving significant ambiguity for an agent trying to invoke the tool correctly.
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%, so the schema already documents all parameters and their roles. The description adds no additional parameter-level meaning, 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 names specific verbs (create, extract, list) and a specific resource (ZIP archives), making the tool's purpose immediately clear. It also distinguishes itself from the sibling tools, which are all focused on fixing, converting, or checking files rather than archiving.
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?
There is no explicit guidance about when to use this tool versus an alternative, no conditions, and no exclusions. The intended use is only implied by the operation names and the schema, which is not enough for an agent to confidently decide between this and other file-related utilities.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
batch_renameA
Rename multiple files using regex pattern, prefix/suffix, or counter. Always preview first with dry_run=true.
| Name | Required | Description | Default |
|---|---|---|---|
| dry_run | No | true = preview only | |
| pattern | Yes | Regex pattern to match in filenames | |
| directory | Yes | Directory containing files to rename | |
| extensions | No | Comma-separated extensions to filter (e.g. 'jpg,png') | |
| replacement | Yes | Replacement string ($1, $2 for capture groups) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It mentions renaming and dry_run preview but does not detail actual effects when dry_run=false, permissions needed, or if original files are preserved. Partial 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 two sentences, front-loading the core purpose and key usage tip. No redundant information.
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?
The description does not explain return value (e.g., list of renamed files, errors). Without output schema, agents lack understanding of what to expect after execution.
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 covers 100% of parameters, but the description introduces 'prefix/suffix or counter' as methods not reflected in the schema. This mismatch could mislead an agent into expecting parameters that do not exist.
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 'Rename multiple files' using specific methods (regex, prefix/suffix, counter) and distinguishes this tool from sibling tools like archive or regex_test.
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 advises 'Always preview first with dry_run=true', providing clear usage guidance. It does not explicitly exclude scenarios or name alternatives, but the advice is direct and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
checksumA
Calculate file hash (SHA256, MD5, SHA1, SHA512). Optionally verify against expected hash.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to the file | |
| expected | No | Expected hash to verify against | |
| algorithm | No | sha256 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description discloses read-only behavior (calculate hash) and optional verification, but lacks details on side effects, permissions, or output format. No annotations exist to supplement.
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?
Single sentence front-loads 'Calculate file hash' and efficiently covers all aspects without waste.
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?
Covers core functionality and algorithms, but lacks output format, error conditions, or behavior when verification fails. No output schema 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?
Adds meaning beyond schema by mentioning optional verification against expected hash. Schema already covers path and algorithm enum, but description ties expected to verify action.
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?
Description clearly states the action (calculate file hash) and resource (file hash), with explicit algorithm options. It distinguishes from sibling tools like archive and batch_rename, which are unrelated.
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?
Description implies usage for hashing files and optional verification. While no explicit when-not or alternatives are provided, sibling tools are distinct, making context clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
cleanup_fileC
Remove BOM, trailing whitespace, fix line endings, remove NUL bytes. Configurable per-option.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to the file | |
| dry_run | No | ||
| remove_bom | No | ||
| remove_nul_bytes | No | ||
| ensure_final_newline | No | ||
| normalize_line_endings | No | lf | |
| remove_trailing_whitespace | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose side effects and behavior. It states the tool modifies files but omits whether it edits in-place, creates backups, or its safety profile. The dry_run parameter hints at previewing, but this is not explained.
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 short (two sentences) and covers core functionality. While concise, it lacks structured organization and could benefit from bullet points or clearer separation of capabilities.
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 7 parameters and no output schema, the description is incomplete. It fails to mention return values, dry-run behavior, or default configurations. 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?
Schema description coverage is only 14%. The description says 'Configurable per-option' but does not elaborate on individual parameters. Parameter names are somewhat self-explanatory, but enum and default values are not clarified.
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 lists specific cleanup operations (BOM, whitespace, line endings, NUL bytes) and states configurability. It clearly identifies the tool's function, though it could better differentiate from sibling tools like fix_encoding.
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 on when to use this tool versus alternatives. The description does not mention prerequisites, suitable contexts, or scenarios to avoid.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convert_formatA
Convert between data formats: JSON, YAML, TOML, XML, CSV, INI. Reads input file and writes output file.
| Name | Required | Description | Default |
|---|---|---|---|
| dry_run | No | Preview conversion without writing the target file | |
| input_path | Yes | Source file path | |
| output_path | Yes | Target file path | |
| input_format | Yes | Source format | |
| output_format | Yes | Target format |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full behavioral burden, yet it only states generic I/O ('Reads input file and writes output file'). This is undercut by the schema's dry_run default of true, meaning the tool previews by default and does NOT write unless dry_run is set to false — a behavior the description's 'writes output file' misleadingly implies. No disclosure of overwrite behavior, error handling, or side effects.
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?
Two short sentences with zero filler. The verb and format list are front-loaded, and the second sentence adds the input/output behavior. 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?
For a moderate 5-parameter tool with 100% schema coverage, the core function is adequately described. However, with no output schema and no annotations, the absence of any note about the dry_run default (preview-only unless dry_run=false) and lack of clarity about whether write mode overwrites existing files leaves meaningful gaps for an agent deciding how to invoke the tool.
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%, so every parameter (input_path, output_path, input_format, output_format, dry_run) is already documented in the schema. The description's format list merely mirrors the enums and adds no new meaning, so the baseline of 3 applies.
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 names a specific verb ('Convert'), a resource (data formats), and enumerates the exact supported formats (JSON, YAML, TOML, XML, CSV, INI). This makes it unmistakably distinct from siblings like fix_json, checksum, and batch_rename, none of which perform cross-format conversion.
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 usage context is implied by the phrase 'Convert between data formats' — an agent can infer this is the go-to tool for format translation. However, there is no explicit when-to-use guidance or exclusion; notably, no distinction from fix_json (repair vs. convert) is stated, and no alternative tools are named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
detect_dupesB
Find duplicate files in a directory by content hash (SHA256). Groups files with identical content.
| Name | Required | Description | Default |
|---|---|---|---|
| min_size | No | Minimum file size in bytes (skip empty files) | |
| directory | Yes | Directory to scan | |
| recursive | No | Scan subdirectories | |
| extensions | No | Comma-separated file extensions to check (e.g. 'py,js,ts'). Empty = all files |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions the hashing algorithm and grouping behavior, but lacks details on performance implications (e.g., scanning large directories), file permissions, or handling of symbolic links. Without annotations, more disclosure is needed.
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?
A single sentence that is concise and front-loaded, conveying the essential purpose and method without extraneous words.
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?
The description lacks information about the return format (e.g., list of file groups) and error handling. Given no output schema and no annotations, the description should provide more context about what the tool returns and its behavior.
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 coverage is 100% (all 4 parameters described). The description does not add parameter-specific details beyond the schema, but the schema itself is clear. 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 tool finds duplicate files using SHA256 hashing and groups identical content. This distinguishes it from siblings like 'checksum' (computes hashes) and 'cleanup_file' (deletes files).
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 list of sibling tools is given but not referenced, and no context is provided about situations where this tool is appropriate or not.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fix_encodingA
Fix encoding issues: detect and repair BOM, broken UTF-8, cp1252 artifacts. Common on Windows.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to the file | |
| dry_run | No | true = analyze only, false = write fixed file |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must reveal behavioral traits. It mentions 'detect and repair' but does not clarify default behavior (dry_run=true means analysis-only) or potential side effects like file modification. The schema supplies dry-run semantics, but the description adds no behavioral 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 extremely concise at two sentences, delivering the core purpose and common context without wasted words. It is front-loaded with the main action.
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?
While the description explains what encoding issues it fixes and mentions Windows, it lacks information about return values, the analysis/repair process, and default behavior (dry_run). For a tool with no output schema, more detail on output or success indicators would improve completeness.
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 coverage is 100% with clear descriptions for both parameters (path and dry_run). The tool description does not add extra meaning beyond what the schema already provides, so a 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 tool's purpose: fixing encoding issues, specifically BOM, broken UTF-8, and cp1252 artifacts. It uses a specific verb ('fix') and resource ('encoding issues'), and distinguishes itself from siblings like 'fix_umlauts' by listing concrete problems.
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 implies usage when encoding problems are present, especially on Windows, but does not explicitly state when to use this tool over alternatives like 'fix_umlauts' or 'convert_format'. No exclusions or prerequisites are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fix_jsonA
Repair broken JSON: strip comments, fix trailing commas, convert single quotes, remove BOM/NUL. Supports dry_run mode.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to the JSON file | |
| dry_run | No | true = analyze only, false = write repaired file |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description mentions dry_run mode behavior but does not disclose potential side effects like overwriting the original file or creating backups, which are important for a repair tool.
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 that efficiently conveys the tool's action and key features with no redundant information.
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 no output schema, the description omits what the tool returns (e.g., success status, repaired content), leaving an information gap for the agent about the tool's output.
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 coverage is 100%, and the description only repeats the dry_run behavior without adding extra meaning about path requirements or expected file format beyond the schema.
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: 'Repair broken JSON' and lists specific fixes (strip comments, fix trailing commas, convert single quotes, remove BOM/NUL), making it distinct from sibling tools like fix_encoding or cleanup_file.
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 implies when to use (for JSON files with syntax issues) but does not provide explicit guidance on when not to use or mention alternatives among siblings like fix_encoding or convert_format.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fix_umlautsA
Fix broken German umlauts from double-encoding or cp1252 artifacts (ä→ä, ö→ö, etc.)
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to the file | |
| dry_run | No | true = analyze only |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description does not disclose whether the tool modifies the file in-place, requires backup, or other behavioral traits. The dry_run parameter hints at analysis, but effects of actual fix are unclear.
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?
Single sentence efficiently conveys purpose and examples with no redundancy.
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 simple tool with two well-described params and no output schema, description covers essential purpose. Could mention return values or confirmation of changes, but adequate for straightforward task.
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 covers 100% of parameters with descriptions. The description adds clarifying examples for the fix operation, but does not add meaning beyond what schema already provides for each 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?
Description clearly states the tool fixes broken German umlauts from double-encoding or cp1252, with specific character examples (ä→ä, etc.). It distinguishes itself from sibling 'fix_encoding' by being specific to umlauts.
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 explicit guidance on when to use this tool vs alternatives like 'fix_encoding'. The context of German umlauts is implied, but no when-not-to-use or comparison provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
folder_diffA
Compare two directories, or take a snapshot and compare on next call. Shows new, modified, and deleted files.
| Name | Required | Description | Default |
|---|---|---|---|
| directory | Yes | Directory to compare/snapshot | |
| compare_to | No | Second directory to compare against. Omit for snapshot mode. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry burden. It discloses that it shows new/modified/deleted files and has snapshot mode, but does not explicitly state it is read-only or mention performance implications.
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?
Two concise sentences with no unnecessary words. Front-loaded purpose and key details.
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?
Adequately covers purpose and parameters, but missing return format details (no output schema). Fairly complete for a simple diff tool.
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 coverage is 100%, and description adds clarification on snapshot mode (omit compare_to). Provides context beyond schema, though somewhat redundant.
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?
Description clearly states the tool compares directories with two modes (direct comparison and snapshot), and lists what it shows (new, modified, deleted files). Differentiates from sibling tools like archive or batch_rename.
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?
Describes two usage modes: provide two directories for comparison or omit compare_to for snapshot. Implicitly guides when to use each mode, but lacks explicit alternatives or when-not-to-use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
regex_testA
Test a regex pattern against text. Shows all matches with groups and positions.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to test against | |
| flags | No | Regex flags (g, i, m, s, u) | g |
| pattern | Yes | Regex pattern |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description reveals that matches, groups, and positions are shown, but lacks details on edge cases, errors, or performance. Basic behavioral info is present but not comprehensive.
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?
One efficient sentence that conveys core functionality without wasted words.
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?
No output schema; description states outputs (matches with groups and positions) but not format or structure. Adequate for a simple tool, but could be more explicit about return value organization.
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 covers all parameters (100%). The description does not add new meaning to parameters beyond what's in schema; it only describes output behavior. Baseline score 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 tool tests a regex pattern against text and lists outputs (matches, groups, positions). It distinguishes from siblings like archive or batch_rename which have unrelated purposes.
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 does not provide guidance on when to use this tool vs. alternatives, nor does it mention when not to use it. Usage is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_emojiB
Scan code files for emoji characters. Useful for finding accidental emojis in source code.
| Name | Required | Description | Default |
|---|---|---|---|
| directory | Yes | Directory to scan | |
| recursive | No | ||
| extensions | No | Comma-separated file extensions | py,js,ts,json,md,txt,yaml,yml,toml |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It does not state that the tool is read-only, nor does it describe any side effects, permissions, or handling of binary files. The scanning nature is implied but not explicitly declared as non-destructive.
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 two sentences, front-loaded with the action, and contains no redundant or unnecessary words. It efficiently communicates the core purpose.
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?
The description lacks information about the tool's output format, which is critical since there is no output schema. It does not explain how the tool returns results (e.g., list of files, count) or handle edge cases. The behavioral transparency gap further reduces completeness.
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?
With 67% schema description coverage, the description adds no extra meaning to the parameters beyond what the schema provides. It does not explain the 'recursive' parameter (which lacks a schema description) or give examples of valid 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 explicitly states 'Scan code files for emoji characters', which is a specific verb and resource. It clearly differentiates from sibling tools, none of which target emoji scanning. The added phrase 'Useful for finding accidental emojis in source code' reinforces the purpose.
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 implies when to use ('Useful for finding accidental emojis'), but does not provide explicit guidance on when not to use or alternatives. Sibling tools do not overlap, so no exclusion needed, but the guidance is minimal.
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.
2 tool updates
v1.0.16- Changed
archive2 fields changed- added
Input schema / properties / dry_runAdded value: +{ + "default": true, + "description": "Preview create/extract without changing files", + "type": "boolean" +} - added
Input schema / properties / overwriteAdded value: +{ + "default": false, + "description": "Allow extraction to overwrite existing files", + "type": "boolean" +}
- Changed
convert_format1 field changed- added
Input schema / properties / dry_runAdded value: +{ + "default": true, + "description": "Preview conversion without writing the target file", + "type": "boolean" +}
12 tool updates
v1.0.5- First observed
archive - First observed
batch_rename - First observed
checksum - First observed
cleanup_file - First observed
convert_format - First observed
detect_dupes - First observed
fix_encoding - First observed
fix_json - First observed
fix_umlauts - First observed
folder_diff - First observed
regex_test - First observed
scan_emoji
TDQS
Scored across 12 tools
Most tools have clearly distinct purposes (e.g., checksum, archive, folder_diff, batch_rename). However, fix_umlauts, fix_encoding, and cleanup_file overlap in handling encoding issues and BOM removal, which could cause some confusion when choosing between them.
The majority of tools follow a verb_noun pattern (fix_*, convert_format, detect_dupes, cleanup_file, scan_emoji), but there are notable exceptions like checksum, archive, folder_diff, and regex_test. The mixed ordering of verb_noun versus noun_verb (or noun-only) breaks a predictable convention.
With 12 tools, the set is well-scoped for a file utilities and data cleanup server. It covers a broad range of functionalities without feeling bloated or insufficient for its apparent purpose.
The toolset covers encoding fixes, format conversion, hashing, archiving, duplicate detection, diffing, renaming, and regex testing, which is comprehensive for its domain. Minor gaps like a general text replacement or search tool exist, but they are not critical dead ends given the current utilities.
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