A collection of AI and machine learning projects including deployment, testing, and agentic flow examples
Scoring was not performed
Output schema completely absent. Tool returns JSON.dumps(result) as plain text without documenting response structure. LLMs cannot predict what fields to expect in shared_data or plan downstream operations.
Date parameter lacks format constraint in description. Parameter says 'Date to check (YYYY-MM-DD)' but no validation or regex pattern enforcement visible. Should declare format: date in schema and validate input.
contextual_integrity_enabled parameter is underspecified. Description only states 'Whether to apply contextual integrity filtering' but does not explain what data is filtered, which fields are redacted, or what the user should pass. Missing dependency hint linking to context detection behavior.
No error handling documented. Code path references ci_filter.detect_context() and ci_filter.apply_filter() but no error recovery guidance. If user_message is malformed or date is invalid, LLM receives no guidance on what to do next.
Tool description does not clarify when to use it vs alternatives. Phrase 'filtered by contextual integrity based on user's request' is vague, does this filter by visibility, by event type, by privacy level? Incomplete WHAT/WHEN/THEN specification.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | F | 0 | 2026-07-28+ | v2 |
| 2026-03-09 | F | 45 | - | v1 |