Gemini Deep Research

PassAudited by VirusTotal on May 12, 2026.

Overview

Type: OpenClaw Skill Name: gemini-deep-research Version: 1.0.0 The skill is designed to interact with the Gemini Deep Research API for complex research tasks. It correctly handles the `GEMINI_API_KEY` by reading it from environment variables or CLI arguments and uses it to authenticate with the legitimate Google API endpoint (`generativelanguage.googleapis.com`). The script saves research reports locally to user-specified or default directories, which is a core function. There is no evidence of unauthorized data exfiltration, malicious execution, persistence mechanisms, prompt injection attempts against the OpenClaw agent, or obfuscation. All observed behaviors are aligned with the stated purpose.

Findings (0)

Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.

What this means

You must base trust mainly on the provided files rather than a verifiable upstream project.

Why it was flagged

The bundled code is visible and no remote installer is present, but the registry metadata does not identify an upstream source or homepage for independent provenance checks.

Skill content
Source: unknown; Homepage: none
Recommendation

Review the included script before use and prefer a verified upstream source if one becomes available.

What this means

The key can access or bill your Gemini account according to its permissions and quota; command-line entry may expose it in shell history or process listings on shared systems.

Why it was flagged

The script uses a Gemini API key for authenticated calls, which is expected for this service, and also permits passing the key on the command line.

Skill content
parser.add_argument("--api-key", help="Gemini API key (overrides GEMINI_API_KEY env var)") ... api_key = args.api_key or os.environ.get("GEMINI_API_KEY") ... "x-goog-api-key": api_key
Recommendation

Prefer the GEMINI_API_KEY environment variable or a secret manager, avoid using --api-key on shared machines, and consider a restricted or quota-limited key.

What this means

Research prompts and any selected file-search context may be processed by Google's service outside your local environment.

Why it was flagged

User research queries, and optionally a Gemini file-search store reference, are sent to Google's Gemini Deep Research endpoint.

Skill content
API_BASE = "https://generativelanguage.googleapis.com/v1beta" ... payload = {"input": query, "agent": AGENT_MODEL, "background": True} ... payload["tools"] = [{"type": "file_search", "file_search_store_names": [file_search_store]}] ... requests.post(f"{API_BASE}/interactions", headers=headers, json=payload)
Recommendation

Do not include confidential data or attach a file-search store unless you intend Gemini to process that material.

What this means

Local output files may contain sensitive prompts, report contents, retrieved context, or metadata that remains after the run.

Why it was flagged

The script intentionally saves both the final report and full interaction metadata to local files.

Skill content
md_path.write_text(report); json_path.write_text(json.dumps(result, indent=2))
Recommendation

Use a private output directory and delete or redact saved markdown/JSON files when they are no longer needed.

NoteHigh Confidence
ASI10: Rogue Agents
What this means

A research job can run for minutes or hours and may consume API quota while it is active.

Why it was flagged

The code starts a background Gemini interaction and polls until it completes or fails, matching the disclosed long-running research purpose.

Skill content
payload = {"input": query, "agent": AGENT_MODEL, "background": True} ... while True: ... time.sleep(10)
Recommendation

Start runs deliberately, monitor Gemini API usage, and stop or cancel provider-side work if you no longer need the research.