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.
npx skills add dwgx/claude-gemini-subagent --skill gemini-subagentgit clone --depth 1 https://github.com/dwgx/claude-gemini-subagentWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/dwgx/claude-gemini-subagent/gemini-subagent)<a href="https://agentmods.dev/skills/dwgx/claude-gemini-subagent/gemini-subagent"><img src="https://agentmods.dev/badge/skills/dwgx/claude-gemini-subagent/gemini-subagent/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/dwgx/claude-gemini-subagent/gemini-subagent"><img src="https://agentmods.dev/badge/skills/dwgx/claude-gemini-subagent/gemini-subagent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00171 | $0.03686 |
| Opus 5 | $0.00086 | $0.01843 |
| Sonnet 5 | $0.00034 | $0.00737 |
| Haiku 4.5 | $0.00017 | $0.00369 |
Grade C, and why
gemini-subagent scanned grade C with 2 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 9d ago.
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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
**Truly destructive ops** (`rm -rf` outside workspace, dropping a Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| **Anything needing network** (web search, fetch, `pip install`, `npm view`, `curl`, `gh api`, remote access) | yolo mode | `--yolo` | How it starts
The opening of the file, as written. The whole thing — 376 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gemini as Worker Subagent
Claude is the orchestrator. Gemini is a worker subagent with its own fresh context window, its own network access, and its own code execution environment. You hand Gemini a well-scoped task and take back a short answer. Gemini's thinking, tool calls, and file reads happen in Gemini's context, not yours — that is where the token savings come from.
Thin-forwarder contract
Treat each Gemini call like a function call:
- You write the prompt (the "arguments")
- Gemini runs its own full agent loop inside its own context
- You take Gemini's stdout as the authoritative return value
- No Claude-side freelancing — don't "edit" what Gemini said in your head and then act on a phantom version. If Gemini's answer is wrong or under- specified, resume the session with a follow-up or dispatch a fresh call with a better prompt. Do not pretend you know what it meant.
When to delegate
Delegate when any of these apply:
- Network needed. Web search, fetching docs, scraping an API,
checking a package version,
gh api,npm view,pip install. You (Claude) pay steep token cost for WebFetch/WebSearch; Gemini's network calls happen in its own context. - Large reads. Scanning a repo, digesting a long file/log, cross- referencing many sources.
- Long output that just needs a conclusion. E.g. "find all TODOs and tell me which are stale" — Gemini emits the list internally and returns only the verdict.
- Writing long files. Gemini writes in its isolated context; you only see "wrote foo.py (240 lines)".
- Running tools you'd rather not stream. Tests, builds, linters, data-processing scripts.
- You're stuck. If your own attempt has stalled or you want a fresh second pass with no prior context, dispatch Gemini with a clean problem statement. That's explicitly the best-case use — "rescue" mode.
When NOT to delegate
- Quick decisions you can make from existing context.
- Tasks that depend tightly on conversation state that would be painful to re-explain.
- One-line edits you could
Editdirectly with less overhead than composing a Gemini prompt. - The user is clearly expecting you to do it interactively ("let's walk through this together").
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.
- 9d ago First seen · 376 lines · 171 tokens per session scan C c74f14e40a5b
gemini-subagent is a skill published in the GitHub repository dwgx/claude-gemini-subagent (1 stars, last pushed 2mo ago), licensed MIT. It adds 171 tokens to every session and 3,686 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it C with 2 findings (recursive force delete, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
sovereign-economics-engine
Unified business model evaluator, client filter, pricing engine, and distribution architect. Absorbs 31 business + 8 marketing + 13 content + 2 acquisition protocols.
therapeutic-ifs
Unified inner work engine: Schema deconstruction (diagnosis) + IFS therapy (treatment). Absorbs: schema-deconstruction.
agentic-code-orchestrator
Unified codebase manipulation, AI deployment, data analysis, and academic delivery engine. Absorbs 6 coding protocols + data-analysis + academic-delivery + spec-driven-dev.
dashboard-builder
Build self-contained interactive HTML dashboards with charts, filters, and tables. Generates a single browser-openable file — no server or dependencies required.
bionic-decision-engine
Unified mathematical arbitrator for all resource allocation decisions — money, time, energy, relationships. Absorbs 46 decision protocols + 24 strategy protocols into one dense engine.
bionic-safety-net
Unified survival infrastructure: health, finance, legal safety, circuit breakers, and structural protection against all ruin classes. The last line of defense.