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A utility server for formatting and updating social media bio text with current MRR (Monthly Recurring Revenue) values
Single tool 'format_bio' has a basic schema with proper input types and a concise description. However, the server lacks fundamental production-quality characteristics: no error handling guidance, no output schema documentation, no consideration of edge cases (null MRR, missing placeholders, malformed templates), and no recovery hints for LLM agents. The tool is extremely simple (currency formatting) but the definition quality falls short of the patterns baseline.
Formats a bio template by replacing the {MRR} placeholder with a formatted currency value
No output schema documented. The tool returns a dict with 'updated_bio_text' key, but this is not explicitly documented in the tool definition. LLMs cannot plan downstream operations without knowing the response structure.
No error handling or recovery guidance. The tool has no documented behavior for edge cases: what if current_mrr is None/negative? What if base_bio_template does not contain '{MRR}'? What if it contains multiple placeholders? Silent failures or unexpected output will confuse agents.
Tool name 'format_bio' is generic and does not clearly signal the MRR-specific currency formatting action. A more specific name like 'format_bio_with_mrr' or 'update_bio_mrr_placeholder' would better convey the tool's purpose to LLMs at the name level alone.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 46 | 2026-07-28+ | v2 |
Parameter descriptions lack actionable detail. The 'base_bio_template' description says it contains '{MRR} placeholder' but does not specify what happens if the placeholder is missing, duplicated, or malformed. Format constraints and expected structure should be explicit.
No validation guidance for numeric input. The 'current_mrr' parameter accepts a float but has no documented range, bounds, or validation rules. Can it be negative? Zero? Very large? LLMs need explicit constraints.