Loading ToolBench
MCP server that provides semantic search capabilities across multiple Pinecone vector indexes (LangChain/LangGraph, RetellAI, and Make.com documentation)
Three semantically similar search tools with identical schemas and minimal descriptions. All tools present proper input schemas with type annotations and defaults, but descriptions are generic and lack LLM-optimization guidance. No output schema documentation visible. Parameter descriptions are adequate but brief. Tools follow verb_noun naming convention ('lang_search', 'retell_search', 'make_search') but lack distinction clarity for when to use each variant. No error handling guidance, validation rules, or recovery paths documented. No parameter constraints (enums, ranges, or format specifications). The pattern of three identical tool signatures with only documentation differences suggests a composition opportunity, could be unified into a single search tool with a 'target' enum parameter.
Search the LangChain/LangGraph documentation.
Search the Make.com documentation and guides stored in Pinecone.
Search the RetellAI documentation stored in Pinecone.
Three semantically identical tools with no distinguishing guidance. LLM cannot determine which search tool to select without trial-and-error. Description does not state WHEN to use each variant or what documentation set each targets.
No output schema documented. LLM cannot plan downstream data extraction or know what fields are returned (score, uri, title, source_url, filename, preview). Without documented return types, LLMs waste tokens parsing unstructured output.
Tool descriptions are 34-46 characters. Below the rubric baseline (avg 194 chars, p10=34). Descriptions lack context: do not explain what documentation is indexed, do not state prerequisites (API keys must be configured), do not clarify when to call each tool, and do not describe result structure or use cases.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | D | 52 | 2026-07-28+ | v2 |
| 2026-03-09 | F | 42 | - | v1 |
Parameter 'top_k' has no validation rules documented. No statement of min/max bounds. Description does not clarify that values >100 may timeout or consume excessive tokens. Unbounded integers invite LLM to pass absurd values.
No error handling or recovery guidance. If Pinecone API fails, embedding service fails, or query returns no results, the LLM receives raw exception or empty list with no context. No error response instructs the LLM on retry, fallback, or alternative action.
No pagination support despite returning lists. Tool returns raw result list with no limit, total_count, or next_cursor. If Pinecone returns 1000 matches, all are returned to LLM, bloating context window and degrading reasoning.