The daily forecast:llm-overlay command was being skipped because the previous
single-conversation flow consumed more than Tier-1's 50,000 input-tokens-per-
minute Anthropic bucket. The web_search tool auto-caches its results (~55k
tokens) and requires `encrypted_content` intact when those blocks are resent,
so the prior retry-on-missing-citations path either 429'd or 400'd on the
second call.
LlmOverlayService now runs two independent API calls. Phase 1 invokes the
web_search tool and we discard the transcript after harvesting the URLs +
titles from the returned web_search_tool_result blocks. Phase 2 is a fresh
conversation containing the forecast context and the harvested headlines as
plain text, with a forced submit_overlay tool call. events_cited is now
optional in the tool schema — Haiku's flaky compliance no longer matters
because citations come from the search results, not the model's transcription.
Model-tagged events (with directional impact) merge with harvested-only
entries (impact: 'neutral'), deduped by URL.
Between phases the service reads anthropic-ratelimit-input-tokens-remaining /
…-reset from Phase 1's headers and sleeps proportionally — only long enough
for the SUBMIT_TOKEN_BUDGET worth of refill, not for the full bucket reset,
capped at 65 seconds.
ApiLogger now captures usage.input_tokens, usage.output_tokens,
cache_read_input_tokens, cache_creation_input_tokens, plus the rate-limit
remaining/reset headers on every Anthropic response. New nullable columns on
api_logs make rate-limit diagnostics directly queryable.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
07e0789044