Databento C++ Extension
Python bindings for Databento's C++ Historical API.
Install / Use
npx skills add quantDIY/QuanuX --skill databentoInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
Our assessment of Databento C++ Extension
Databento C++ Extension scores 47/100 on our quality scale, 4287th of 4,595 Development & Engineering skills we index.
Its SKILL.md is 930 bytes long, split into 7 sections with 1 code example: fairly brief, so expect to fill in details yourself.
It has no GitHub stars yet, so there is no community track record; judge it on its content.
Maintenance, license and trust
- The repository was last updated about 6 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
- Our last check on 2026-10-18 found the source still online.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 74/100, with 3 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-10-09. Automated pattern scan on 2026-10-09. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
Databento C++ Extension compared with similar skills
All 4 of these similar skills score higher than Databento C++ Extension; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| Databento C++ Extension (this skill)by quantDIY | 47 | 0 | 6mo ago | SKILL.md |
| taste-skillby Leonxlnx | 100 | 101.6k | 3d ago | CLAUDE.md |
| Agent-Reachby Panniantong | 100 | 101.3k | today | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 77.6k | 1d ago | CLAUDE.md |
| ai-job-searchby ai-job-search-dev | 100 | 64.0k | 2d ago | CLAUDE.md |
Frequently asked questions
- How do I install Databento C++ Extension?
- Run
npx skills add quantDIY/QuanuX --skill "Databento C++ Extension". The install tabs above show the steps for each supported agent. - Which AI agents does Databento C++ Extension work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is Databento C++ Extension safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 74/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is Databento C++ Extension still maintained?
- The repository was last updated about 6 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
Skill content
View source on GitHubname: Databento C++ Extension description: Python bindings for Databento's C++ Historical API.
Databento C++ Extension (databento_ext)
High-performance Cython bindings for Databento's C++ API.
Installation
Run python3 setup.py build_ext --inplace in extensions/cpp/databento/cython/.
Requires cmake to fetch dependencies first.
Usage
import databento_ext
# 1. Historical Client
builder = databento_ext.PyHistoricalBuilder().set_key_from_env()
client = builder.build()
# Client is now a valid C++ Historical client wrapper.
Status
- Historical Builder: ✅ Implemented (Cython)
- Historical Client: ✅ Implemented (Cython)
- Live Data: 🚧 Pending Migration
- DuckDB Connector: 🚧 Pending Migration (Requires re-implementing
timeseries_to_duckdbwith new Cython types)
Dependencies
libdatabento(Static)zstd,openssl,curl,brotli(System libraries)
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.