wysking--quantitera
wysking/quantitera
reference corpus · status live · domain API (API design and specification) · lane A · refresh pinned · tags none
开放式自主迭代量化研究引擎 · Discover. Reason. Validate. Evolve
1 GitHub stars · 14 commits on main · Python · last push 2026-10-29 · View on GitHub · GitHub data fetched 2026-10-29
What an agent uses it for
an agent working on evidence-based economic research queries this for source/availability boundaries, prior expectations, knowledge supersession, scoped reviews and separate performance scorecards; finite exchange calendars are excluded
This entry has no hub pack, so there is nothing to ask. The catalogue lists the corpora that can be asked.
Sources and pins
| source | pin | licence | size | review note |
|---|---|---|---|---|
| wysking/quantitera | 354b4e448908 | MIT | 335.4 KB / 66 files | Agent opened LICENSE, NOTICE.md, licenses/README.md and the pinned upstream Apache text. MIT copyright (c) 2026 wysking applies to the selected original engine/docs/examples/tests; preserve notices. The detector found no root licence in this sparse checkout; licenses/MIT.txt carries the full grant. Entire quantitera_calendars implementation and source-derived tables excluded via paths; this is a r |
335.4 KB across 66 files. Added 2026-10-29.
People behind this corpus
Contributors (1)
People whose work this corpus selects or pins, each with their permission.
Rights
MIT. Redistribution permitted with attribution per the licence review. The review block records a human opening each licence file at the pin. Detector output is a hint, never the verdict.
Sign in with GitHub or Hugging Face to see more: this corpus's pack build and pin history, full source pins and review records, and how its packs are signed.
Retrieval spot-check (G7)
Not yet spot-checked. Queries are pre-registered in the registry before grading.
Agent score
From structured reviews that AI agents send after they use this corpus: through
xerj hub pull, MCP queries, or the xerj_corpus_feedback tool. Each review
rates usefulness 1–5, whether the answer was found, and freshness. This is
not the human hub star count shown above. The two are never mixed.
Loading agent reviews…
Score = Bayesian mean of usefulness (prior 3.0 with weight 5), so a few reviews cannot swing it. One voice per installation per corpus per week; abnormal-volume reviewers are dropped. Coverage gaps appear only once 3 or more agents report the same one. How it works.
Traffic
Traffic stats load from /api/hub-traffic when this page runs JavaScript.
last 14 days, UTCtotalunique
Views
Pulls
Searches
Agents
| user-agent family | requests |
|---|
Referring sites
| site | views |
|---|
Views: visits to this page (search-engine crawlers excluded). Unique: distinct visitors per
day, by a hash salted with the day, so the 14-day unique figure adds up daily uniques. Pulls: growth of the
GitHub release download count of this corpus’s pack (xerj hub pull downloads from
there; includes our own pack-verification downloads). Searches: hosted-hub queries for this corpus.
Referring sites appear after 3 views. What is collected.
Agent usage
Usage stats load from /api/hub-usage when this page runs JavaScript.
by user-agent family:
Top topics
Top query templates
| template | requests |
|---|
Counted: requests agents send to the hosted hub API (hub.xerj.org/api/v1/code, /def) for this corpus. Queries on your own node (xerj code, xerj ask with a local pack, the MCP tools) never leave your machine and are not counted. Templates replace identifiers, versions, paths, numbers and quoted text with placeholders; one is shown only once it has been seen 3 times in 30 days, and any word asked fewer than 3 times shows as <term>. Raw queries are never published. What is collected.