Loading ToolBench
Production-grade permissions, hooks, and tool safety for AI agents. Works with any LLM provider.
AgentGate provides 7 tools with Zod schemas and descriptions, but quality is inconsistent. All tools have input schemas with type definitions and descriptions present. However, descriptions are brief (avg ~80 chars, below the 194-char baseline), lack actionable context for LLM selection, and omit critical safety guidance. Tool names lack action verbs (DatabaseQuery, ApiCall, Bash are generic; GitPush and SendEmail are better). Parameter descriptions exist but are minimal. Output schemas are not documented. Error handling is absent from visible code, no recovery guidance, categorization, or actionable error messages. The framework emphasizes permissions and safety classification (isReadOnly, isDestructive, isConcurrencySafe) but does not translate this into user-facing tool descriptions or error responses. No evidence of pagination, result limits, or chaining IDs in responses.
Make HTTP API calls with support for GET, POST, PUT, DELETE methods. Tracks read-only and destructive operations.
Execute bash commands with permission matching support. Classifies commands as read-only or destructive based on command type.
Execute database queries with built-in safety checks for read-only, destructive, and concurrency properties. Enforces production database read-only constraint.
Push git commits to a remote repository. Supports force push detection as destructive operation.
Read file contents from the filesystem. Read-only and concurrency-safe operation.
Send email messages with validation for mass emails and suspicious content detection.
Tool names lack action verbs. DatabaseQuery, ApiCall, Read, Write, Bash are generic or noun-based. LLMs cannot infer intent from names alone. Should be: execute_database_query, make_api_call, read_file, write_file, execute_bash_command.
Descriptions are too brief (avg 80 chars vs 194-char baseline) and lack context for LLM selection. E.g., 'Execute database queries with built-in safety checks' does not explain WHEN to use this vs a generic SQL tool, what safety checks apply, or what the output contains. Missing: prerequisites, return structure, error cases.
Output schemas are not documented. Tools return ToolResult<T> with a 'data' field, but the structure of T is not specified in tool definitions. LLMs cannot plan downstream calls or extract required fields (e.g., does DatabaseQuery return row count? Column names? Affected rows?). No pagination, result limits, or chaining IDs documented.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 49 | 2026-07-28+ | v2 |
Write content to a file. Supports permission matching on file paths.
No error handling guidance visible. Tools classify operations as destructive/read-only but do not document error responses, recovery steps, or categorization (retryable vs fatal). E.g., if DatabaseQuery fails on production, what should the LLM do? Retry? Ask user? No guidance.
Parameter descriptions are minimal. E.g., 'database' param for DatabaseQuery says 'Target database environment' but does not explain consequences of choosing production vs staging, or what queries are allowed on each. 'command' for Bash lacks format/constraint guidance. Missing: ranges, patterns, mutually exclusive params.