Loading ToolBench
A local RAG-based code analysis and optimization server that indexes git repositories, analyzes code style, detects agentic patterns, and provides semantic search over project files using embeddings and Qdrant vector database.
Server has 7 tools with basic descriptions and input schemas, but significant quality gaps. All tools have descriptions (positive), but most are generic and lack actionable detail for LLM selection. Input schemas present but incomplete: parameters lack type definitions in several tools (e.g., 'limit' in search_codebase has no explicit type constraint). No output schemas documented. Error handling is minimal, no recovery guidance, no categorization of retryable vs fatal errors. Tool naming is reasonable (verb_noun pattern) but descriptions don't explain WHEN to use each tool vs alternatives. No tool annotations (readOnlyHint, destructiveHint) despite clear risk levels. Parameter descriptions are sparse, e.g., 'language' in analyze_code_style lacks enum constraint documentation. No pagination support documented for list-like tools. Overall: functional but well below production baseline.
Analyzes Python and TypeScript/JavaScript code for agentic style issues. Detects missing type hints, undocumented functions, and patterns that reduce agent compatibility. Returns a list of issues with severity levels.
Clears the vector index for a specific git branch. Removes all indexed embeddings and resets the index state, allowing a fresh re-indexing on the next index_repository call.
Detects code patterns that indicate agentic or tool-like behavior in the codebase. Identifies functions that could be exposed as MCP tools, functions with clear input/output contracts, and functions suitable for agent integration.
Generates an AI-powered summary of a specific file in the repository. Summarizes the purpose, key functions/classes, and main logic of the file to aid understanding.
Retrieves comprehensive context about a git repository including branch name, current commit hash, commit date, total indexed files, and index status. Useful for understanding the current state of the repository and what has been indexed.
Indexes a git repository incrementally. On first run, indexes all tracked files at the current commit. On subsequent runs, only indexes changed files since the last indexed commit. Uses embeddings to create a searchable vector index stored in Qdrant, scoped to the current git branch.
No output schemas documented. LLMs cannot plan downstream calls or extract required fields. Tools return unstructured text (e.g., 'Returns a list of issues') without field definitions.
Parameter type constraints missing or undocumented. 'language' in analyze_code_style should declare enum('python'|'typescript'|'all'), 'limit' in search_codebase lacks min/max bounds. LLMs cannot validate inputs.
No tool annotations (readOnlyHint, destructiveHint, idempotentHint). clear_index is marked DESTRUCTIVE but tool definition lacks annotation. Agents cannot infer safety properties.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 43 | <=2025-11-25 | v2 |
Performs semantic search over the indexed codebase using natural language queries. Returns the most relevant code snippets and file paths ranked by similarity to the query.
Error handling lacks recovery guidance. No tool documents what to do on failure (retry? ask user? fatal?). E.g., search_codebase may fail if index not initialized, but no guidance provided.
Descriptions lack WHEN/WHY context. 'Performs semantic search' is WHAT; missing is WHEN to call this vs get_file_summary, or what prerequisites exist (index must be initialized first).