Loading ToolBench
Solves the #1 problem with MCP servers: context window overload. Provides smart tool pruning, relevance scoring, context budget tracking, and recommendations for which tools to load for a given task. Reduces context usage by 40-60% while maintaining capability.
Two tools with German-language descriptions and basic schemas. analyze_task has a single string parameter with minimal description; estimate_context_usage accepts an array of server names. Both descriptions are present but lack actionable detail for LLM selection (no WHEN to use, no prerequisites, no output schema documentation). No error handling guidance, no parameter constraints (enums, ranges), no documented return types. Tool names follow verb_noun pattern (positive), but descriptions are generic and under-optimized for agent reasoning. No security considerations, no pagination, no idempotent guarantees documented.
Analysiere eine Aufgabe und empfehle die optimale Server-Kombination. Bestimmt welche MCP-Server für eine Aufgabe relevant sind, schätzt den Token-Verbrauch und gibt Empfehlungen zur Context-Optimierung.
Schätze den Context-Window-Verbrauch einer Server-Kombination. Hilft zu verstehen wie viel Context-Budget eine bestimmte Kombination von MCP-Servern verbraucht.
No documented output schemas. LLMs cannot plan downstream calls or extract required fields without knowing what analyze_task and estimate_context_usage return. Rubric requires 100% of A+ tools to have documented return types.
Descriptions lack WHEN/WHY context. Both descriptions state WHAT the tool does but omit WHEN to call it instead of alternatives, prerequisites, or use-case guidance. Rubric requires descriptions to answer: What does it do? When should the LLM call it? What does it return?
Parameter descriptions are minimal. task_description in analyze_task has only '(z.B. "Check SOL token safety")', an example, not a constraint. server_names in estimate_context_usage lacks any description of valid server names, format, or constraints. Rubric requires every parameter to have a non-empty description explaining what it controls.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 47 | 2026-07-28+ | v2 |
No error handling or recovery guidance. If analyze_task receives an unrecognized task or estimate_context_usage receives invalid server names, there is no documented error response or guidance for the LLM to retry or self-correct. Rubric requires error responses to tell the LLM what to do next.
No input validation or constraints. server_names array has no minItems, maxItems, or enum constraint. task_description has no length limit or pattern. Free-form strings invite hallucinated values. Rubric requires constrained input (enums, ranges, patterns) to prevent invalid LLM submissions.