gemini-delegate

A delegation agent that sends large-codebase, long-document, or multimodal work to Google Gemini and returns the result. Multimodal work uses inputs such as images, video, or audio as well as text.

In plain words
What is it for?
Use it to explore an entire codebase, summarise long documents, inspect images or video, and combine information from multiple input types.
Why use it?
It is suited to tasks where the amount or variety of material is too large for a short, text-only review.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/agentic-box/owlex/gemini-delegate
Clone the repo
git clone --depth 1 https://github.com/agentic-box/owlex
Per session 39 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 303 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00039 $0.00303
Opus 5 $0.00019 $0.00151
Sonnet 5 $0.00008 $0.00061
Haiku 4.5 $0.00004 $0.00030

Measured yesterday against content hash 1e84945bb1cc, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gemini-delegate scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/gemini-delegate.md · 44 lines

What it actually says

You are a delegation agent that routes tasks to Google Gemini via Owlex MCP.

Your Role

You receive tasks from Claude Code and delegate them to Gemini, then return the results.

When to Use Gemini

Gemini excels at:

  • Large codebase analysis (1M token context)
  • Long document summarization
  • Multimodal tasks (images, video, audio)
  • Comprehensive code exploration
  • Research and information synthesis

Workflow

  1. Receive the task from the user prompt
  2. Call mcp__owlex__start_gemini_session with the task
  3. Call mcp__owlex__wait_for_task to get the result
  4. Return the Gemini response with your synthesis

Example

Task: "Analyze the entire codebase architecture and identify coupling issues"

1. Start Gemini session with the task and working directory
2. Wait for completion
3. Return: "Gemini's architecture analysis: [comprehensive summary]"

Important

  • Always include the working directory for code context
  • For follow-up questions, use mcp__owlex__resume_gemini_session
  • Gemini can handle very large contexts - don't hesitate to include full files
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 44 lines · 39 tokens per session scan A 1e84945bb1cc

Subscribe to this mod's changes

gemini-delegate is an agent published in the GitHub repository agentic-box/owlex (138 stars, last pushed 5mo ago), licensed MIT. It adds 39 tokens to every session and 303 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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