Loading ToolBench
LLM-native debugging infrastructure for dynamic instrumentation and runtime tracing
Strobe has 15 tools with complete input schemas and descriptions, but quality is uneven. Tool names follow verb_noun convention (debug_*, test_*, ui_*), which is good. However, descriptions are terse (avg ~60 chars, well below the 194-char baseline), lacking context on WHEN to use each tool and what happens on error. Parameters are typed and mostly described, but lack constraints (enums, ranges, format hints). Output schemas are not documented, LLMs cannot predict what fields to expect. Error handling is absent from descriptions. The vision tool (ui_detect_elements) is a Python sidecar, not integrated into the Rust server, creating composition risk. Overall: functional but below production baseline.
Get the current call stack for a paused session
Set a breakpoint at a specific location to pause execution
Resume execution of a paused session
Launch a program under Strobe instrumentation with optional trace patterns
Get local variables at the current frame
Set a logpoint to emit a message when execution reaches a location
Query traced events from a session with filtering and pagination
Read memory at a specific address with optional type interpretation
Output schemas not documented. LLMs cannot predict what fields debug_query, debug_backtrace, debug_locals, or ui_detect_elements return, forcing them to guess or make follow-up calls.
Descriptions are terse (avg 50 chars vs 194-char baseline). Missing context on WHEN to use each tool, what happens on error, and prerequisites. E.g., debug_trace lacks explanation of pattern syntax or failure modes.
No error handling guidance. Descriptions do not explain what errors are retryable, user-fixable, or fatal. E.g., debug_launch does not mention what happens if the executable is not found or lacks debug symbols.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 48 | <=2025-11-25 | v2 |
Step execution (into, over, or out of functions)
Stop a debug session and clean up resources
Add or update trace patterns for function instrumentation in an active session
Watch a variable or expression and capture its value at each event
Write data to memory at a specific address
Run tests with Strobe instrumentation and capture results
Detect UI elements in a screenshot using vision AI
Parameters lack constraints. tracePatterns accepts free-form strings with no documented syntax (e.g., 'myapp::*' vs '@file:src/main.rs'). stepType has an enum, but others like 'condition' in debug_breakpoint lack format hints.
ui_detect_elements is a Python sidecar, not integrated into the Rust MCP server. Composition risk: unclear how vision results chain to debug tools, and whether the sidecar is discoverable or requires manual setup.