Loading ToolBench
Local-first AI platform with MCP server exposing RAG knowledge base and multi-provider LLM gateway through Model Context Protocol
LocalMind defines 25 tools with moderate quality. Most tools have descriptions (20/25), but many descriptions are brief (avg ~80 chars vs. baseline 194). Input schemas are present for all tools with type definitions and parameter descriptions, which is strong. However, output schemas are not documented, LLMs cannot plan downstream tool usage without knowing what fields are returned. Tool naming follows verb_noun conventions ('documentSearch', 'chat', 'saveSnippet'), but several lack clarity about idempotence and side effects. Error handling guidance is absent, no recovery hints or error classifications. Composition is fair: tools operate on distinct concerns (RAG, chat, snippets, code quality), but some tools combine multiple responsibilities (e.g., 'scaffoldProject' writes files AND substitutes placeholders). The server includes destructive operations (deleteSnippet) without confirmation patterns. Parameter descriptions are mostly present and specific, but several lack constraint examples (e.g., topK range, temperature bounds). Overall, this is a solid mid-tier implementation: better than 50% of community servers, but falls short of production-grade tooling due to missing output schemas and error handling.
Analyze a git diff string for common issues: console.log, TODO, debugger, hardcoded credentials, empty catch blocks.
Build a regex pattern from a description or keyword (email, url, ipv4, uuid, etc.).
Send a message to an LLM through the multi-provider gateway. Supports multi-turn conversations via conversationId. Providers: OLLAMA, OPENAI, ANTHROPIC, GOOGLE.
Calculate cyclomatic complexity of a code snippet. Returns score, rating, and breakdown. Languages: java, python, javascript, typescript, rust.
Scan project dependencies for known vulnerabilities. Supports Maven (pom.xml) and npm (package.json).
Compare HTTP responses from two URLs. Shows differences in status code, time, body, and headers.
Convert a regex pattern between formats: java, python, javascript, pcre.
Output schemas not documented. LLMs cannot plan downstream calls or extract result fields. documentSearch, chat, listModels, all code tools return data but no schema is visible in definitions.
Destructive tools (deleteSnippet, scaffoldProject file write) lack confirmation or dry-run patterns. Agents can delete data or overwrite projects without a safety gate.
No error handling guidance in tool descriptions. Tools do not explain what errors can occur, whether they are retryable, or how to recover. E.g., 'chat' does not document rate limits, API failures, or invalid provider errors.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | D | 54 | 2026-07-28+ | v2 |
| 2026-03-09 | F | 22 | - | v1 |
Delete a code snippet by its ID.
Search documents in the LocalMind knowledge base using RAG. Returns relevant chunks with similarity scores.
Explain a regex pattern in natural language, component by component.
Find declared dependencies not imported or used in source code.
Generate an equivalent cURL command from HTTP request parameters.
Retrieve a specific code snippet by its ID.
Audit dependency licenses, flagging copyleft licenses (GPL, AGPL, LGPL, MPL-2.0).
List available LLM providers and their status in LocalMind.
List available templates: spring-boot-api, angular-app, maven-multi-module, mcp-server, react-app.
List all tags used across code snippets with their usage count.
Analyze a regex pattern and suggest optimizations (redundant classes, unnecessary groups, greedy quantifiers).
Save a reusable code snippet with metadata (title, language, description, tags).
Generate a single component/service/controller/model file.
Generate a complete project structure from a template with placeholder substitution.
Search snippets by keyword, tag, or programming language. Filters can be combined.
Send an HTTP request and return status code, headers, body, and response time in ms.
Suggest improvements: magic numbers, long functions (>30 lines), deep nesting (>4 levels), duplicate patterns, unused variables.
Test a regex pattern against a list of strings. Returns match results with captured groups.
Parameter constraints missing or vague. 'topK' has no min/max bounds (baseline expects 1 - 100). 'temperature' has no range (should be 0 - 2 or similar). 'timeoutMs' unbounded. LLMs may pass invalid values.
Tool descriptions too brief for LLM selection. Several descriptions under 60 chars (vs. baseline 194 avg). 'listModels' (18 chars), 'listProjectTemplates' (9 chars), 'listSnippetTags' (11 chars) lack context for when/why to call them.
Chat tool combines two separate concerns: LLM messaging AND multi-provider gateway logic. Should split into 'send_message' (with provider/model selection) and a separate 'list_providers'. Current design makes it hard to reuse just messaging logic.
scaffoldProject and scaffoldComponent combine multiple responsibilities: template selection, file generation, placeholder substitution. Should offer separate tools for discovery (list templates, describe template) and generation.
No idempotency guarantees stated. 'saveSnippet', 'scaffoldProject' appear to be write operations but no description explains if repeated calls with same ID/name are safe or create duplicates.
Tool 'chat' lacks transparency about LLM cost and token consumption. Agents calling this repeatedly may rack up high costs without guidance. No warning in description.