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Query Dune Blockchain Analytics

ASecurity

Dune Analytics API skill for querying, analyzing, and uploading blockchain data. Use this skill whenever the user mentions Dune, on-chain data, blockchain analytics, token trading volume, DEX activity, wallet tracking, Solana/EVM transaction analysis, or wants to explore crypto…

19 stars
0 votes
0 copies
1 views
Added 9/19/2026
ai-agentspythongobashsqlapiperformancedocumentation

Works with

cliapi

Security Analysis

A96/100
mediumInstalls packages at runtime which could introduce malicious dependencies

Scanned 9/19/2026

Install to Claude Code

$npx -y skills add rondoflow/rondoflow --skill query-dune-blockchain-analytics --agent claude-code

Installs into .claude/skills of the current project.

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Files
SKILL.md
---
name: query-dune-blockchain-analytics
description: "Dune Analytics API skill for querying, analyzing, and uploading blockchain data. Use this skill whenever the user mentions Dune, on-chain data, blockchain analytics, token trading volume, DEX activity, wallet tracking, Solana/EVM transaction analysis, or wants to explore crypto…"
category: "Finance & Crypto"
author: community
version: "2.0.0"
icon: coins
---

# Dune Analytics API

A skill for querying and analyzing blockchain data via the [Dune Analytics](https://dune.com) API.

## Setup

```bash
pip install dune-client
```

Set `DUNE_API_KEY` via environment variable, `.env` file, or agent config.

## Best Practices

1. **Read references first** — The reference files contain critical table names, anti-patterns, and chain-specific gotchas that aren't obvious from table names alone. Reading the right reference before writing SQL prevents common mistakes like using `dex.trades` for wallet analysis (which inflates volume ~30%) or missing Solana's dedup requirement.

2. **Prefer private queries** — Creating queries with `is_private=True` keeps the user's workspace clean and avoids polluting the public Dune namespace. Fall back to public if it fails (free plan limitation), and let the user know.

3. **Reuse before creating** — Dune charges credits per execution. Reusing or updating an existing query avoids unnecessary duplicates and makes credit tracking easier. Only create new queries when the user explicitly asks.

4. **Confirm before updating** — Modifying an existing query's SQL is destructive (previous version isn't saved by default). A quick confirmation avoids overwriting work the user might want to keep.

5. **Track credits** — Each execution costs credits depending on the performance tier and data scanned. Reporting credits consumed helps the user manage their budget. See [query-execution.md](references/query-execution.md#credits-tracking).

## Scripts — Common Operations

For common operations, use the scripts in `scripts/` to avoid writing boilerplate code every time. All scripts read `DUNE_API_KEY` from the environment automatically.

| Script | Command | What it does |
|--------|---------|-------------|
| `dune_query.py` | `execute --query-id ID` | Execute a saved query (supports `--params`, `--performance`, `--format`) |
| `dune_query.py` | `get_latest --query-id ID` | Get cached result without re-execution |
| `dune_query.py` | `get_sql --query-id ID` | Print query SQL |
| `dune_query.py` | `update_sql --query-id ID --sql "..."` | Update query SQL |
| `dune_discover.py` | `search --keyword "uniswap"` | Search tables by keyword |
| `dune_discover.py` | `schema --table "dex.trades"` | Show table columns and types |
| `dune_discover.py` | `list_schemas --namespace "uniswap_v3"` | List tables in a namespace |
| `dune_discover.py` | `contract --address "0x..."` | Find decoded tables by contract address |
| `dune_discover.py` | `docs --keyword "dex"` | Search Dune documentation |
| `dune_upload.py` | `upload_csv --file data.csv --table-name tbl` | Quick CSV upload (overwrites) |
| `dune_upload.py` | `create_table --table-name tbl --namespace ns --schema '[...]'` | Create table with explicit schema |
| `dune_upload.py` | `insert --file data.csv --table-name tbl --namespace ns` | Append data to existing table |

**Example:**
```bash
# Execute query with parameters
python scripts/dune_query.py execute --query-id 123456 --params '{"token":"ETH"}' --format table

# Upload a CSV privately
python scripts/dune_upload.py upload_csv --file wallets.csv --table-name my_wallets --private
```

## Reference Selection

**Before writing any SQL, route to the correct reference file(s) based on your task:**

| Task involves... | Read this reference |
|-----------------|-------------------|
| Finding tables / inspecting schema / discovering protocols | [table-discovery.md](references/table-discovery.md) |
| Finding decoded tables by contract address | [table-discovery.md](references/table-discovery.md#search-tables-by-contract-address) |
| Searching Dune documentation / guides / examples | [table-discovery.md](references/table-discovery.md#search-dune-documentation) |
| Wallet / address tracking / router identification | [wallet-analysis.md](references/wallet-analysis.md) |
| Table selection / common table names | [common-tables.md](references/common-tables.md) |
| SQL performance / complex joins / array ops | [sql-optimization.md](references/sql-optimization.md) |
| API calls / execution / caching / parameters | [query-execution.md](references/query-execution.md) |
| Uploading CSV/NDJSON data to Dune | [data-upload.md](references/data-upload.md) |

If your task spans multiple categories, read **all** relevant files. The references contain critical details (e.g., specialized tables, anti-patterns) that aren't covered in this overview — guessing table names or query patterns leads to subtle bugs.

## Quick Start

```python
from dune_client.client import DuneClient
from dune_client.query import QueryBase
import os

client = DuneClient(api_key=os.environ['DUNE_API_KEY'])

# Execute a query
result = client.run_query(query=QueryBase(query_id=123456), performance='medium', ping_frequency=5)
print(f"Rows: {len(result.result.rows)}")

# Get cached result (no re-execution)
result = client.get_latest_result(query_id=123456)

# Get/update SQL
sql = client.get_query(123456).sql
client.update_query(query_id=123456, query_sql="SELECT ...")

# Upload CSV data (quick, overwrites existing)
client.upload_csv(
    data="col1,col2\nval1,val2",
    description="My data",
    table_name="my_table",
    is_private=True
)

# Create table + insert (supports append)
client.create_table(
    namespace="my_user",
    table_name="my_table",
    schema=[{"name": "col1", "type": "varchar"}, {"name": "col2", "type": "double"}],
    is_private=True
)
import io
client.insert_data(
    namespace="my_user",
    table_name="my_table",
    data=io.BytesIO(b"col1,col2\nabc,1.5"),
    content_type="text/csv"
)
```

## Subscription Tiers

| Method | Description | Plan |
|--------|-------------|------|
| `run_query` | Execute saved query (supports `{{param}}`) | Free |
| `run_sql` | Execute SQL directly (no params) | Plus |

## Key Concepts

### dex.trades vs dex_aggregator.trades

| Table | Use Case | Volume |
|-------|----------|--------|
| `dex.trades` | Per-pool analysis | ⚠️ Inflated ~30% (multi-hop counted multiple times) |
| `dex_aggregator.trades` | User/wallet analysis | Accurate |

> **Why this matters:** If you're analyzing a specific wallet's trading activity and use `dex.trades`, you'll see inflated volume because a single swap through an aggregator gets split into multiple pool-level trades. `dex_aggregator.trades` captures the user-level intent — one row per user swap. See [wallet-analysis.md](references/wallet-analysis.md) for full patterns.

Solana has no `dex_aggregator_solana.trades`. Dedupe by `tx_id`:
```sql
SELECT tx_id, MAX(amount_usd) as amount_usd
FROM dex_solana.trades
GROUP BY tx_id
```

### Data Freshness

| Layer | Delay | Example |
|-------|-------|---------|
| Raw | < 1 min | `ethereum.transactions`, `solana.transactions` |
| Decoded | 15-60 sec | `uniswap_v3_ethereum.evt_Swap` |
| Curated | ~1 hour+ | `dex.trades`, `dex_solana.trades` |

Query previous day's data after **UTC 12:00** for completeness.

## References

Detailed documentation is organized in the `references/` directory:

| File | Description |
|------|-------------|
| [table-discovery.md](references/table-discovery.md) | Table discovery: search tables by name, inspect schema/columns, list schemas and uploads |
| [query-execution.md](references/query-execution.md) | API patterns: execute, update, cache, multi-day fetch, credits tracking, subqueries |
| [common-tables.md](references/common-tables.md) | Quick reference of commonly used tables: raw, decoded, curated, community data |
| [sql-optimization.md](references/sql-optimization.md) | SQL optimization: CTE, JOIN strategies, array ops, partition pruning |
| [wallet-analysis.md](references/wallet-analysis.md) | Wallet tracking: Solana/EVM queries, multi-chain aggregation, fee analysis |
| [data-upload.md](references/data-upload.md) | Data upload: CSV/NDJSON upload, create table, insert data, manage tables, credits |

Attribution

rondoflowrondoflow
View sourceMore from rondoflow →
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