MCP Server for Prompt Compression Token Pruning Skill - Prunes low-information tokens from long prompts to save context window and cost
Single tool with minimal schema documentation. Tool name 'compress_prompt' is clear and verb-based, but input schema lacks parameter descriptions entirely. The schema object shows properties but no 'description' fields for 'text' or 'target_ratio' parameters. Tool description is present (58 chars) but generic, does not explain WHEN to use it, WHAT it returns, or any prerequisites. No output schema documented. No error handling guidance. Fails multiple critical checks from pattern:tool and pattern:tool-description.
Prune low-information tokens from long prompt to save context window and cost
Input parameters lack descriptions. 'text' and 'target_ratio' have no description fields in the schema, violating pattern:tool-description. LLMs cannot infer what 'target_ratio' means (is it 0-1 or 0-100?) or when to adjust it.
No output schema documented. The tool returns a dict with 'compressed_text', 'original_tokens', 'compressed_tokens', 'compression_ratio', 'tokens_saved', but the MCP response wraps it as JSON text in a content block. LLMs cannot parse the structure without explicit schema.
Tool description is too generic (58 chars). Does not explain WHEN to use compression, what 'target_ratio' does numerically, or what the output fields mean. Baseline for A+ tools is 50-200 chars with explicit WHAT/WHEN/RETURN guidance.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 46 | 2026-07-28+ | v2 |
No error handling or recovery guidance. If compression fails (e.g., empty text, invalid target_ratio), the tool returns a generic exception. No actionable error messages to guide the LLM's next step.
target_ratio parameter has a default (0.5) but no constraints documented. LLMs may pass invalid values (negative, >1.0, or absurd like 0.001). Description should state: 'Compression ratio as decimal 0.0 - 1.0 (default 0.5). Lower values = more aggressive compression.'