AI Layoffs

{'type': 'object', 'properties': {}}

{'type': 'object', 'properties': {}}

{'type': 'object', 'required': ['company'], 'properties': {'company': {'type': 'string', 'pattern': '\\S', 'maxLength': 120, 'minLength': 1, 'description': "Company name, e.g. 'Klarna', 'IBM', 'Salesforce'. Partial names work."}}, 'additionalProperties': False}

{'type': 'object', 'properties': {'role': {'type': 'string', 'pattern': '\\S', 'maxLength': 80, 'description': "Affected function or occupation, partial match, e.g. 'customer service', 'engineering'."}, 'sort': {'enum': ['newest', 'oldest', 'largest'], 'type': 'string', 'description': 'newest first (default), oldest first, or the largest disclosed cut first.'}, 'limit': {'type': 'integer', 'maximum': 50, 'minimum': 1, 'description': 'Maximum events to return (default 10, at most 50).'}, 'query': {'type': 'string', 'pattern': '\\S', 'maxLength': 200, 'description': "Free text matched against the company, the stated reason, the context paragraph, sector, country, affected roles and source name. Every word must appear. Example: 'customer service'."}, 'since': {'type': 'string', 'pattern': '^\\d{4}(-\\d{2}(-\\d{2})?)?$', 'description': 'Earliest event date, inclusive: YYYY, YYYY-MM or YYYY-MM-DD.'}, 'until': {'type': 'string', 'pattern': '^\\d{4}(-\\d{2}(-\\d{2})?)?$', 'description': 'Latest event date, inclusive: YYYY, YYYY-MM or YYYY-MM-DD.'}, 'sector': {'type': 'string', 'pattern': '\\S', 'maxLength': 80, 'description': "Sector, partial match, e.g. 'Financial', 'Software'."}, 'company': {'type': 'string', 'pattern': '\\S', 'maxLength': 120, 'description': "Company name or part of it, e.g. 'Klarna'."}, 'country': {'type': 'string', 'pattern': '\\S', 'maxLength': 80, 'description': "Country as recorded, partial match, e.g. 'United States', 'India', 'Sweden'. For US-based roles use us_only."}, 'us_only': {'type': 'boolean', 'description': 'Only events whose affected roles are US-based.'}, 'execution': {'type': 'array', 'items': {'enum': ['executed', 'partial', 'announced', 'reversed', 'unknown'], 'type': 'string'}, 'description': 'Keep only these execution statuses. executed: The reduction has been carried out. partial: Some of the cut is done, the rest pending. announced: A stated plan, not yet carried out (often multi-year). unknown: Execution status not established. reversed: The cut was rolled back or rehired against (e.g. Commonwealth Bank).'}, 'attribution': {'type': 'array', 'items': {'enum': ['explicit', 'mixed', 'blamed'], 'type': 'string'}, 'description': "Keep only these attribution levels. explicit: The company itself declared the layoff AI-related. blamed: A credible source named AI, but the company did not. Shown as context and never counted: prong 1 of our standard requires the employer's own source to name AI, so a blamed event is a failed claim, not a discounted one. mixed: AI was cited alongside other material factors (cost, demand)."}, 'counted_only': {'type': 'boolean', 'description': 'Only events whose roles the register counts as AI-attributed (drops events that are reported but not counted).'}, 'full_context': {'type': 'boolean', 'description': "Also return each event's context paragraph. Several times longer, so best with a small limit; get_company_ai_layoffs always includes it for one company."}, 'evidence_tier': {'type': 'array', 'items': {'enum': ['tier1', 'tier2', 'tier3'], 'type': 'string'}, 'description': "Keep only these evidence tiers. tier1 (Primary-source attributed): AI named as a workforce driver in the company's own SEC filing, on-record earnings call, or official statement, with the event corroborated by a structured source. tier2 (Reputable-press attributed): AI named as a cause by credible journalism quoting a named company source, but not yet in a company filing. tier3 (Inferred / single-source): Attribution from one secondary tracker, an unnamed source, or vague forward-looking language."}}, 'additionalProperties': False}