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RuvLTRA MCP Server for fast and low-cost vibe coding
RuvLTRA provides 13 tools with explicit JSON Schema definitions and descriptions, but quality is uneven. Naming follows verb_noun conventions well (generate, review, refactor, explain, etc.). Descriptions are present and moderately detailed (50-150 chars typical), exceeding the 20-char floor. However, parameter descriptions are sparse or generic in several tools. Output schemas are NOT documented, critical for agent composition and chaining. Error handling returns text responses but lacks structured recovery guidance. Security design is sound (read-only API, no credentials exposed). Composition is good: each tool has a single clear purpose, though no documented response schemas make chaining harder than it should be.
Complete partial code from prefix/suffix. For best output quality, provide instructions and context in English.
Explain code clearly for a given audience. For best output quality, provide instructions and context in English.
Fix code using error details and optional guidance. For best output quality, provide instructions and context in English.
Generate code from instruction and context. For best output quality, provide instructions and context in English.
Refactor code while preserving behavior. For best output quality, provide instructions and context in English.
Review code for bugs, security, performance, correctness, and maintainability. For best output quality, provide instructions and context in English.
Output schemas are not documented. Tools return results but agents cannot predict response structure for downstream composition. Critical for tool chaining.
Parameter descriptions are inconsistent and sometimes generic. 'language' appears in many tools but is described identically without specifying format, constraints, or examples. 'focus' array in ruvltra_code_review lacks description of valid values (security? performance? both?). Generic descriptions force LLMs to guess valid inputs.
Inferred effective spec: 2025-06-18+.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | D | 55 | 2025-06-18+ | v2 |
| 2026-03-09 | F | 43 | - | v1 |
Generate tests for provided code. For best output quality, provide instructions and context in English.
Translate code between programming languages. For best output quality, provide instructions and context in English.
Generate multiple files concurrently through the worker pool. For best output quality, provide instructions and context in English.
Scale worker pool size within configured min/max.
Return SONA learning statistics for all workers or a specific worker.
Return server, worker, and backend runtime status.
Run multi-perspective parallel code reviews (up to 8 perspectives). For best output quality, provide instructions and context in English.
Numeric parameter constraints are sparse. 'maxTokens' in ruvltra_code_generate has no min/max bounds; 'temperature' has no documented range (0 - 1? 0 - 2?). 'timeoutMs' across all tools has minimum: 1 but no maximum, allowing LLMs to pass unreasonable values like 999999. Unbounded parameters invite agent errors and service timeouts.
ruvltra_status and ruvltra_sona_stats have minimal descriptions (65, 60 chars respectively). 'Return SONA learning statistics for all workers or a specific worker.', SONA is unexplained jargon. What are learning statistics? When should an agent call this vs ruvltra_status? Vague descriptions reduce tool discoverability.
No error handling documentation. Tools return text via ToolExecutionResult but rubric requires error responses to guide LLM recovery (retry, user-fixable, fatal classification). Handler catches ToolInputError and generic exceptions but returns unstructured error text.
ruvltra_code_complete has ambiguous naming. 'Complete' is vague, does it finish a line, a function body, or entire code block? Parameter names 'prefix' and 'suffix' are clearer but description is generic.
ruvltra_parallel_generate and ruvltra_swarm_review work on arrays of tasks but return text responses. No documentation of per-item success/failure. If one of 5 generation tasks fails, does the entire tool fail or return partial results? Ambiguity breaks agent retry logic.
ruvltra_scale_workers description says 'Scale worker pool size within configured min/max' but does not explain what happens on success (how long? immediate? queued?), whether scaling is reversible, or what the return value is. Agents cannot reason about state changes without clear postconditions.