reflect-skills-from-me…
This skill should be used when the user asks to "reflect on skills from memory", "audit marketplace skills against memory",…
Runs a deep-research query on Google Gemini's deep-research managed agent and returns a cited report. This skill should be used when the user asks to "deep research with Gemini", "run Gemini deep research", "have Antigravity research X", or wants a thorough, multi-source web
$ npx -y skills add FradSer/dotclaude --skill research --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
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Runs a deep-research query on Google Gemini's deep-research managed agent and returns a cited report. This skill should be used when the user asks to "deep research with Gemini", "run Gemini deep research", "have Antigravity research X", or wants a thorough, multi-source web
name: research description: Runs a deep-research query on Google Gemini's deep-research managed agent and returns a cited report. This skill should be used when the user asks to "deep research with Gemini", "run Gemini deep research", "have Antigravity research X", or wants a thorough, multi-source web research report produced by a remote Gemini agent. Invoked via "/antigravity:research". Supports a higher-effort max mode via "--max". argument-hint: "<research question> [--max] [--collaborative-planning] [--visualization off|auto] [--thinking-summaries auto|none] [--bigquery] [--system TEXT] [--tier flex|standard|priority|deferred] [--label k=v]" allowed-tools: ["Bash(uv:*)", "Monitor", "Read"] user-invocable: true
Run `$ARGUMENTS` as a deep-research query on Gemini's deep-research managed agent, wait for it to finish, and report the cited result. Two models are available: `deep-research-preview-04-2026` (default) and `deep-research-max-preview-04-2026` (max mode — slower, higher effort), selected with `--max`.
The script is at `${CLAUDE_PLUGIN_ROOT}/scripts/antigravity.py`. It is self-daemonizing: `research` returns immediately with a `run_id`, a detached worker runs the research, and a `status` file flips to `completed` / `failed` when done. Requires credentials and `uv` on PATH. Two credential paths are supported: Vertex AI via ADC plus `ANTIGRAVITY_PROJECT` / `ANTIGRAVITY_LOCATION`, or an API key (`GEMINI_API_KEY` / `GOOGLE_API_KEY`); see the Authentication section of `../delegate/references/usage.md`. Deep research can take several minutes.
**Goal**: Turn `$ARGUMENTS` into a clear research question.
**Actions**: 1. Use the full `$ARGUMENTS` text (minus a `--max` flag) as the research question. Pass `--max` through to the script when the user wants max mode (deeper, slower). 2. If it is empty or too vague to research (no subject, scope, or constraints), ask the user one or two clarifying questions, then proceed.
**Goal**: Start the detached research worker.
**Actions**: 1. Run the script:
uv run "${CLAUDE_PLUGIN_ROOT}/scripts/antigravity.py" research --query "<question>" [--max]2. Capture `run_id`, `output_file`, and `wait_command` from stdout. 3. If stdout reports an error (for example no credentials configured, or a forced `ANTIGRAVITY_AUTH` path that is incomplete), surface it and stop. Note: deep research has **no** token cap (`DeepResearchAgentConfig` accepts no `max_total_tokens`), so `--max-tokens` is deliberately absent here — never imply to the user that a research run is bounded.
**Goal**: Block until the research finishes without busy-looping the model.
**Actions**: 1. Start a Monitor on the captured `wait_command`. It emits one line — `antigravity run <id>: completed` / `failed` / `timeout` — then exits:
uv run "${CLAUDE_PLUGIN_ROOT}/scripts/antigravity.py" wait --run <run_id> --timeout 1800Deep research is slow: set the Monitor `timeout_ms` to 3600000 (60 min, 2x the wait timeout) and pass `--timeout 1800` to the wait command. Use a clear description like "antigravity research <run_id>". 2. When the Monitor event arrives, check if the line contains `: completed`, `: failed`, or `: timeout`:
Start the Monitor on the same `wait_command` again to keep waiting. After **four** consecutive timeouts (4 hours total), tell the user it is still running and give them the full command to fetch it later:
uv run "${CLAUDE_PLUGIN_ROOT}/scripts/antigravity.py" status --run <run_id> --fullthen stop. Never present a `timeout` / still-running state as the report.
**Goal**: Present the research report.
**Actions**: 1. Fetch the full result:
uv run "${CLAUDE_PLUGIN_ROOT}/scripts/antigravity.py" status --run <run_id> --fullOr read the rendered `output_file` directly. 2. Present the report text to the user, preserving any citations and sources. 3. If the status is `failed`, report the recorded error and likely cause.
browsing. No sandbox tools or network flags apply here.
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