Loading ToolBench
Autonomous AI agent architecture for long-running learning and execution projects
Visioneer defines 4 tools with basic schemas and descriptions, but falls short of production quality. All tools have descriptions (10-50 chars, below the 50-200 char baseline for LLM optimization) and input schemas with typed parameters. However, descriptions lack actionable context, they state WHAT but not WHEN or WHY. No output schemas are documented. Error handling is absent: tools do not guide recovery or categorize failures. Parameter descriptions are minimal (e.g., 'Search query' for web_search.query). No tool annotations (readOnlyHint, destructiveHint, idempotentHint) despite clear risk profiles (web_search and web_fetch are READ_ONLY; write_artifact is WRITE). Naming is verb-first and clear (web_search, web_fetch, write_artifact, read_artifact), meeting baseline conventions. Composition is reasonable, each tool has one responsibility, but artifact tools lack pagination, limits, or path validation guidance.
Read content from an artifact file
Fetch and parse content from a web URL
Search the web for information
Write content to an artifact file
Descriptions are too brief (10-50 chars) and lack actionable context. 'Search the web for information' does not explain WHEN to use web_search vs. other discovery tools, what format results take, or prerequisites (e.g., SERPER_API_KEY required). LLMs cannot infer selection criteria from minimal text.
No output schemas documented. Tests show return types (WebSearchResult, WebFetchResult, WriteArtifactResult, ReadArtifactResult) but these are not declared in tool definitions. LLMs cannot plan downstream calls or extract required fields without knowing response structure.
No tool annotations despite clear risk profiles. web_search and web_fetch are READ_ONLY; write_artifact is WRITE. Annotations (readOnlyHint, destructiveHint, idempotentHint) enable agents to reason about safety and retry logic. Absence forces LLMs to guess.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 55 | <=2025-11-25 | v2 |
Parameter descriptions are minimal. 'Search query' and 'URL to fetch' lack format guidance, constraints, or examples. 'max_results' has no range (e.g., 1-100). 'filename' has no path validation rules or allowed characters. LLMs cannot validate inputs without explicit constraints.
No error handling guidance. Tests show error responses (e.g., 'Web search failed') but tool definitions do not document error cases, recovery steps, or categorization (retryable vs. user-fixable vs. fatal). Agents cannot self-correct without explicit error guidance.