Indexing

Community

austintgriffith

indexing

Use when building anything that reads past onchain activity: feeds, leaderboards, dashboards, analytics. Also when someone proposes scanning logs or blocks for history, when deciding which events a contract emits, or when deploying a subgraph or indexer to production.

Overview

Publisher	austintgriffith
Repository	`ethskills`
Skill name	`indexing`
Stars	298
Forks	64
Bundled files	Instructions only
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by austintgriffith on GitHub. Read the source before you install it.

Installation

Install the Indexing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/austintgriffith/ethskills/tree/master/indexing
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/austintgriffith/ethskills.git /tmp/ethskills
mkdir -p .claude/skills
cp -r /tmp/ethskills/indexing .claude/skills/indexing

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Indexing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Indexing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Indexing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Onchain Data and Indexing

Historical onchain data comes from an indexer, never from a scan at request time. Public RPCs cap each eth_getLogs call by block span and by matched-log count, so a full-history scan is thousands of paginated calls that grow with every block and fail on rate limits, timeouts or credits. Back a feed, streak, ranking or dashboard with a one-time backfill into a persistent indexed store that then tails new events — a subgraph, Ponder, a provider data API, or your own indexer. Rebuilding past state from archive-node reads is the same mistake in another shape.

Design contracts event-first: every state change emits an event carrying what the read side needs, because a change with no event is invisible to every indexer, frontend and explorer. Keep aggregation, ranking and pagination offchain; if a result must be committed onchain, store a hash.

Current state is not indexing work. Balances, allowances, ownership and other "as of now" reads are direct contract calls, batched into one request with Multicall3 (0xcA11bde05977b3631167028862bE2a173976CA11, same address on most chains) or a provider balances endpoint. Do not build or operate a subgraph to track a number the chain returns on request.

The read side is not designed until its production home is named. Decide where the indexer runs in production and by which command or service, and write that down next to the architecture — this is the decision that silently stays open, leaving a read side that only ever ran on a laptop.

On The Graph, deploying is not publishing, and the free hosted service is gone (sunset June 2024), so there is no free public endpoint to deploy to:

bash
graph init <slug>          # then codegen/build
graph auth <deploy-key>
graph deploy <slug>        # -> Subgraph Studio: testing only

Publish the subgraph from Studio to the network to get the production endpoint, and query it with a Studio API key. Production queries are metered: about 100K free per month, then about $2 per 100K (checked 2026-08-18 — re-read the live pricing page before quoting a budget). Self-hosting a Graph Node or a Ponder process is a fine alternative, but then the host, the persistent store and the process supervision are yours to name.

Frequently asked questions

What does the Indexing AI skill do?

Why use Indexing on TypingMind?

Because you install it once and use it with any model. Indexing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Indexing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/austintgriffith/ethskills/tree/master/indexing. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Indexing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Indexing?

As many as you like. As long as a model supports skills, you can use Indexing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Indexing AI skill free?

It is published on GitHub by austintgriffith. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Onchain Data and Indexing

Frequently asked questions

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