Loading ToolBench
A FastAPI-based multi-agent AI platform with tool execution, capability guards, and AutoGen integration. Provides tools for code execution, database queries, email, file operations, HTTP requests, shell commands, and user interaction.
11 tools with complete schemas and descriptions, but significant quality gaps. Most tools have basic descriptions (50-150 chars) and parameter schemas, but lack LLM-optimized guidance, error recovery hints, and actionable constraints. Destructive tools (code_execute, shell_command, file_write, email_send) lack confirmation/dry-run patterns. Parameter descriptions are minimal, many omit format constraints, ranges, or dependency documentation. No tool annotations (readOnlyHint, destructiveHint, idempotentHint) present. Output schemas not documented. Error handling is absent, no recovery guidance or categorization. Composition is reasonable (single responsibility per tool), but chaining support is weak (missing IDs in responses).
Ask the user a question and wait for their response. Use this when you need clarification or approval before proceeding.
Execute code in a sandboxed environment. Supports Python, JavaScript, TypeScript, Bash, and more.
Execute a read-only SQL query against the database. Returns rows as a list of dictionaries.
Read emails from the inbox. Can filter by sender, subject, or date range.
Send an email. IMPORTANT: Always get user approval before sending. Provide to, subject, and body.
List files and directories at the given path. Returns names, types, and sizes.
Destructive tools lack confirmation/dry-run patterns. code_execute, shell_command, file_write, and email_send can cause irreversible harm without agent safeguards or user approval workflows.
No tool annotations (readOnlyHint, destructiveHint, idempotentHint) present. LLMs cannot distinguish safe from dangerous tools without explicit hints.
Parameter descriptions lack format constraints, ranges, and dependency documentation. E.g., 'timeout' has no min/max; 'language' in code_execute has no enum; 'action' in plan_update lacks explanation of when each enum value applies.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | C | 60 | 2026-07-28+ | v2 |
Read the contents of a file at the given path. Returns the file content as text.
Write content to a file. Creates the file and parent directories if they don't exist. Overwrites existing content by default.
Make an HTTP request to a URL. Supports GET, POST, PUT, DELETE. Returns status code, headers, and body.
Update the current task execution plan. Can add new steps, mark steps complete, or modify existing steps.
Run a shell command in the project workspace. Returns stdout, stderr, and exit code.
No output schemas documented. LLMs cannot plan downstream tool calls or extract required fields. E.g., email_read returns 'list of dictionaries' but structure is undefined; file_list returns 'names, types, sizes' but field names and types are not specified.
Error handling absent. No recovery guidance, categorization (retryable vs fatal), or actionable error messages. Tools will fail silently or return raw exceptions, leaving agents unable to self-correct.