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feat(skills): add int-gemini skill (Google Gemini API offload)#112

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feat(skills): add int-gemini skill (Google Gemini API offload)#112
mt-alarcon wants to merge 1 commit into
evolution-foundation:mainfrom
mt-alarcon:feat/int-gemini-skill

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What

New integration skill int-gemini to offload cheap / high-volume tasks from the main models to the Google Gemini API (AI Studio), via GEMINI_API_KEY.

Why

A large, low-cost model with a 1M-token window and native Google Search grounding is a natural fit for high-volume, low-stakes work (classification, summarization, first drafts, web research) — letting the primary model focus on reasoning. This skill wraps the Gemini API behind the repo's standard skill conventions.

Design

  • Commands: ask (--allow-sensitive, --fallback, --system-file, --grounding), scan, route, models, smoke, --version.
  • Confidentiality guard — a partial guard-rail, documented honestly as such (the free tier trains on prompts): blocks structured PII by default (CPF/CNPJ/card/CEP/email/BRL/phone/address/PIX/contract/secret) + best-effort name+context. Free-text names without a role term are a known false-negative, documented in the SKILL and pinned by a regression test; --allow-sensitive is the conscious override. The SKILL recommends redaction / a no-train tier for inputs that carry user data by nature.
  • Robust HTTP: retry on 429/5xx; --fallback (flash-lite 503 → flash) that reports which model actually answered and never masks a real error; type-safe responses.
  • smoke: exit-0 + JSON {overall, steps[], duration_ms}, including a guard step exercised offline.

Tests

105 tests, network fully blocked in the suite (autouse). Includes a documented false-negative corpus (asserts what the guard does not catch, with rationale) so the guard-rail's real limits are visible, not hidden.

Notes

  • Stdlib-only (no new dependencies).
  • Instance/auth via env only (GEMINI_API_KEY) — nothing hardcoded.

🤖 Generated with Claude Code

New integration skill to offload cheap/high-volume tasks from the main
models to the Google Gemini API (AI Studio), via GEMINI_API_KEY.

- Commands: ask (with --allow-sensitive, --fallback, --system-file,
  --grounding), scan, route, models, smoke, --version.
- Use cases: classification, summarization, first drafts, and web research
  with Google Search grounding — anywhere a large/cheap model fits.
- Confidentiality guard: a PARTIAL guard-rail (documented honestly as such)
  that blocks structured PII by default (CPF/CNPJ/card/CEP/email/BRL/phone/
  address/PIX/contract/secret) and best-effort name+context. Free-text names
  without a role term are a known false-negative, documented + regression-
  tested; --allow-sensitive is the conscious override.
- Robust HTTP: retry on 429/5xx, --fallback (flash-lite 503 -> flash) that
  never masks a real error, type-safe responses.
- 105 tests, network fully blocked in the suite. smoke is exit-0 + JSON
  {overall, steps[], duration_ms}. Stdlib-only; instance/auth via env.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

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