Loading ToolBench
A powerful knowledge management system that forges wisdom from experiences, insights, and best practices
The server defines 2 tools with reasonable structure and detail. Both tools have descriptions (194 and 195 chars, within baseline range), explicit input schemas with properties and types, and clear enum constraints on knowledge_type. However, there are notable gaps: output schemas are undocumented (LLM cannot predict response structure), parameters lack comprehensive format/constraint descriptions in text (relying on JSON schema alone), and error handling guidance is missing. The schema definitions are thorough JSON structures but descriptions could better guide LLM selection and usage patterns.
Retrieve relevant knowledge and context for a given task or query. This tool helps LLM access its long-term memory and relevant context for better task execution.
Store various types of knowledge, insights, and experiences in a specific domain. This includes but is not limited to: best practices, lessons learned, understandings, experiences, and solutions.
Output schemas not documented. LLMs cannot predict what fields store_knowledge and retrieve_knowledge_context return, forcing trial-and-error or context re-reading. Handler code shows store_knowledge returns {success, documentId, domain, knowledgeType, message}, but retrieve_knowledge_context handler is truncated and return structure is unknown.
Parameter descriptions lack explicit format constraints. 'content' is described as 'The knowledge content to store (e.g., best practice, lesson learned, insight)' but no length limits, required format, or examples of bad input are stated. 'maxResults' has a default but no min/max bounds documented in description (schema shows default: 5, but description does not state it must be >0 or <1000). This forces LLMs to guess valid ranges.
No error handling guidance. Handlers do not document what failures can occur (e.g., database full, invalid domain, confidence out of range) or what LLM should do next (retry, ask user, fallback). Pattern:recovery-guide requires actionable error messages.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-21 | D | 58 | 2026-07-28+ | v2 |
| 2026-03-09 | D | 57 | - | v1 |
Confidence parameter in store_knowledge accepts 0-1 per description but no validation is visible in handler code. If LLM passes 1.5 or -0.5, will it error or silently clamp? Undocumented behavior invites incorrect usage.
retrieve_knowledge_context handler code is truncated in source snippet (ends at 'const { ... } = opti'), so actual return structure cannot be verified. Assume schema score penalty reflects this incompleteness.
No idempotency guidance. store_knowledge accepts a timestamp param but does not state whether calling twice with identical timestamp/content produces one record or two. Agents may retry on ambiguous failures and expect deduplication.