What is qveris-a-stock-data-layer?

A data workflow for researching companies listed on China’s mainland stock exchanges, known as A-shares. It covers market data, company information, financial statements, news, research, ownership events, and related market activity.

Use it for A-share quotes and history, company and financial research, news and announcements, sector reports, ownership changes, price-limit events, ETFs, and investor activity.

It gathers these different sources into one evidence-based process while keeping missing information visible and avoiding investment advice.

qveris-a-stock-data-layer — Skill for Codex by QVerisAI

Install

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.

Any agent

npx skills add QVerisAI/open-qveris-skills --skill qveris-a-stock-data-layer

Clone the repo

git clone --depth 1 https://github.com/QVerisAI/open-qveris-skills

Made for: Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/qverisai/open-qveris-skills/qveris-a-stock-data-layer/github.svg)](https://agentmods.dev/skills/qverisai/open-qveris-skills/qveris-a-stock-data-layer)

Your own site

<a href="https://agentmods.dev/skills/qverisai/open-qveris-skills/qveris-a-stock-data-layer"><img src="https://agentmods.dev/badge/skills/qverisai/open-qveris-skills/qveris-a-stock-data-layer/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/qverisai/open-qveris-skills/qveris-a-stock-data-layer"><img src="https://agentmods.dev/badge/skills/qverisai/open-qveris-skills/qveris-a-stock-data-layer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 3,145 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

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	$0.00077	$0.03145
Opus 5	$0.00039	$0.01572
Sonnet 5	$0.00015	$0.00629
Haiku 4.5	$0.00008	$0.00314

Measured 12d ago against content hash 2f1baf035f75, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

qveris-a-stock-data-layer 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 12d ago.

The scan reads SKILL.md. This mod also ships 6 executable files (scripts/qveris_finance_adapter.mjs, scripts/qveris_finance_client.mjs, scripts/qveris_finance_tool.mjs, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

qveris-a-stock-data-layer/SKILL.md · 118 lines

How it starts

The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.

QVeris A-Stock Data Layer

Use this skill to preserve the A-Stock Data candidate's broad A-share data-layer intent while replacing legacy endpoints, scraping, and provider-specific dependencies with QVeris finance CAP calls plus a narrow audited Web lane for news and qualitative sentiment.

Source record:

Field	Value
Candidate number	58
Original repository	A-Stock Data
GitHub URL	https://github.com/simonlin1212/a-stock-data
License	Apache-2.0
Evaluation recent activity	2026-06-28
Local source snapshot	`third_party/source_repos/58-a-stock-data`
Snapshot latest commit	`bcda405` on 2026-06-28

Source Adaptation

Preserve the original ten-layer research/data intent: market data, research reports, signals, capital/ownership, news, fundamentals, filings, limit-up/limit-down, ETF options, and investor interaction.
Replace the original embedded Python and direct source routing with QVeris CAP calls. The source repo's endpoints, headers, anti-ban rules, mootdx, requests, stockstats, and optional iwencai key are migration context only.
Convert original valuation flows to evidence-gated trailing or consensus-input notes; do not output target prices, upside/downside, trade setups, or option strategies.
Convert limit-up, LHB, unlock, capital-flow, ETF-option, hot-list, and investor-Q&A layers to conditional capabilities: call them only after current cap-detail confirms a QVeris finance CAP and matching fields.
Keep broad data-layer reports concise for users; put full call details and rejected payloads in the trace appendix.

Runtime Contract

Use only qveris_finance.* CAP tools and QVERIS_API_KEY.
Execute every finance data call through this Skill's scripts/qveris_finance_adapter.mjs, or through a native wrapper that runs the byte-identical adapter; never call /capabilities/query directly from the workflow.
Default natural-language output to a Markdown user report, not a JSON object.
Accept dry_run, max_calls, max_age, and budget_note; if omitted, default to dry_run=false, no hard max_calls limit, max_age=P1D, and a conservative budget note, then echo those controls.
Read references/qveris-finance-data-quality-rubric.md before using QVeris payloads as evidence.
Use references/qveris-finance-retry-policy.md for 5xx, fetch failures, 404s, payload truncation, and semantic mismatches.
Read references/qveris-finance-capability-fallbacks.json before replacing a failed CAP. Use only a listed same-claim fallback, preserve its declared evidence downgrade, and keep unlisted capabilities missing.
Build trace, call counts, retries, and timestamps only from saved observed_calls. Never invent an execution ID or a call that was only planned; use execution_id=null when an observed call returned no ID.
Sanitize every output surface, including Evidence, Sources, prose, params, responses, and Trace. Strip provider names, provider API URLs, raw route/tool IDs, candidates, failover, credentials, and routing metadata recursively; the Trace row remains exactly tool_name, params, status, execution_id, fallback_used, and missing_fields.
Sanity-check entity, market, exchange, asset type, currency, date window, fiscal period, and payload shape before using data.
Treat a successful transport response with wrong A-share identity, wrong date window, wrong fiscal period, or too-thin bars as rejected evidence.
Suppress target prices, upside/downside, ratings, buy/sell wording, rebalancing instructions, and trade execution plans even if present in a QVeris payload.
Read and follow references/qveris-web-news-sentiment-policy.md. Never call qveris_finance.news_fin_tagged or qveris_finance.sentiment_text_signals; use its audited Web lane in every run mode, including benchmark and replay.

Read the full file on GitHub · 118 lines

Files

What ships with it

25 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

12d ago First seen · 118 lines · 77 tokens per session scan A 2f1baf035f75

Subscribe to this mod's changes

qveris-a-stock-data-layer is a skill published in the GitHub repository QVerisAI/open-qveris-skills (21 stars, last pushed 8d ago), licensed MIT. It adds 77 tokens to every session and 3,145 once invoked, about $0.0004 per session on Opus 5. 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.

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qveris-a-stock-data-layer