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 manishiitg/coding-agent-loop --skill google-aigit clone --depth 1 https://github.com/manishiitg/coding-agent-loopWrote 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/manishiitg/coding-agent-loop/google-ai)<a href="https://agentmods.dev/skills/manishiitg/coding-agent-loop/google-ai"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/google-ai/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/manishiitg/coding-agent-loop/google-ai"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/google-ai.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 | $0.00000 | $0.01990 |
| Opus 5.5 | $0.00000 | $0.00796 |
| Sonnet 5.5 | $0.00000 | $0.00398 |
| Haiku 4.5 | $0.00000 | $0.00199 |
Grade A, and why
google-ai 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 1mo 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.
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.
How it starts
The opening of the file, as written. The whole thing — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Google Gemini stills and narration
Google's own Gemini image generation (publicly nicknamed “Nano Banana”) and
Gemini TTS are reached directly through Google's Gemini API, not through
fal.ai. In Video Studio, use this skill only for optional still-image work or
off-camera narration. Never generate footage with Veo, Gemini Omni, or any
other Google video model: all paid video uses MiniMax H3 through fal-ai.
This skill owns the client call after the still-image or narration direction is
decided. Read video-look-sound for narration choices and
video-cinematography for an optional reference-image brief.
Never invent a model ID
Google image and TTS product names are not API model identifiers. Do not guess the exact model string from memory. Before the first still-image or narration call in a new production:
- Resolve the current Google model ID and required request shape from Google's own Gemini API reference -- not from this skill, which is deliberately silent on exact IDs and changes on Google's own schedule.
- Record the resolved model ID and exact request in the production record so a revision reuses the same asset setup rather than whatever is current later.
A run whose model ID cannot be confirmed is a blocker to report, not a guess to make.
Authentication
The user stores the key as a workflow secret named GEMINI_API_KEY (via
set_workflow_secret) -- the same env var name this platform's own LLM
provider configuration already uses for Gemini, kept consistent rather than
introducing a second name for the same kind of credential. The
secret-injection mechanism prefixes every secret name with SECRET_ in the
shell environment, so the variable actually present is
$SECRET_GEMINI_API_KEY, not $GEMINI_API_KEY. Bridge the two explicitly:
export GEMINI_API_KEY="$SECRET_GEMINI_API_KEY"
node generate.mjs
or pass it directly to the client instead of relying on ambient env:
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({
apiKey: process.env.SECRET_GEMINI_API_KEY ?? process.env.GEMINI_API_KEY,
});
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.
- 1mo ago Changed · -20 lines · -99 tokens per session 3d5d9f8b6a85
- 1mo ago First seen · 229 lines · 99 tokens per session scan A 29ff1940a361
google-ai is a skill published in the GitHub repository manishiitg/coding-agent-loop (13 stars, last pushed 19d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,990 tokens. 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.
Other skills, from other repositories
fiber-rest-api
Use when adding or changing a Go HTTP endpoint — Fiber v2 or v3 (detect which), thin handlers, central error mapping, boundary validation; the same rules apply to net/http, chi, echo or gin.
go-hexagonal-architecture
Use when adding a use case, port, repository or adapter in a Go service — where each piece goes, how errors and transactions cross layers, and how to check the import direction.
zerolog-observability
Use when adding logging to Go code - the repository's logger with structured fields, request-scoped correlation, correct levels, no secrets or double-logging.
backend-language-decision
Use when starting a backend task that could be built in more than one language - follow the repository's stack, or for a greenfield service choose between Go, Java, C#/.NET, TypeScript on Node.js and Rust from the task's shape.
goga-cell-go
Golang rules for implementing CODEMANIFEST contracts.
go-add-entity
Add a full CRUD vertical slice (domain, DTO, repository, service, handler, migration, factory wiring) to an existing GOB Go microservice.