What is qveris-alphaear-market-intelligence?

A market-intelligence workflow adapted for QVeris data, covering stock lookups, company fundamentals, finance news, sentiment coverage, signal changes, and structured reports.

Use it to check tickers, prices, fundamentals, news, sentiment coverage, and monitoring signals, then produce evidence-based market reports without presenting forecasts as investment advice.

It replaces direct feeds, local databases, downloaded models, and forecasting tools with traceable QVeris evidence and audited web evidence, while keeping conclusions descriptive.

qveris-alphaear-market-intelligence — 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-alphaear-market-intelligence

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-alphaear-market-intelligence/github.svg)](https://agentmods.dev/skills/qverisai/open-qveris-skills/qveris-alphaear-market-intelligence)

Your own site

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

Per session 78 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 3,048 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	$0.00078	$0.03048
Opus 5	$0.00039	$0.01524
Sonnet 5	$0.00016	$0.00610
Haiku 4.5	$0.00008	$0.00305

Measured 12d ago against content hash f6a333135260, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

qveris-alphaear-market-intelligence 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 5 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-alphaear-market-intelligence/SKILL.md · 122 lines

How it starts

The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.

QVeris AlphaEar Market Intelligence

Use this skill to preserve AlphaEar's stock, news, sentiment, signal-tracking, and reporting workflows while replacing direct public feeds, local databases, model downloads, and prediction tooling with QVeris structured-data CAP evidence plus audited Web news/sentiment evidence.

Source record:

Field	Value
Candidate number	42
Original repository	Awesome Finance Skills / AlphaEar
GitHub URL	https://github.com/RKiding/Awesome-finance-skills
License	Apache-2.0
Evaluation recent activity	2026-03-29
Local source snapshot	`third_party/source_repos/42-awesome-finance-skills`
Snapshot latest commit	`853f09b` on 2026-03-29

Source Adaptation

Preserve the original AlphaEar intent: ticker lookup, stock price context, financial fundamentals, finance news, sentiment coverage checks, signal evolution, and structured reporting.
Treat original scripts, local models, local databases, prediction-market feeds, and time-series forecast logic as migration context only.
Convert forecasts and "investment signal" wording into descriptive monitoring: evidence can show what changed, but not whether to act.
Use audited opened Web pages for issuer news and qualitative sentiment; do not use the disabled tagged-news or text-sentiment CAPs.
Keep reports user-readable by default; put full machine-readable trace JSON only in the appendix, fixtures, or when explicitly requested.

Runtime Contract

Use qveris_finance.* CAP tools and QVERIS_API_KEY for structured finance data. The only non-CAP exception is the audited Web news/sentiment lane.
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 Markdown, not a large 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.
Read references/qveris-finance-data-quality-rubric.md before using any payload as evidence.
Read references/qveris-workflow-semantic-guards.md before any derived, comparative, ranking, sentiment, or multi-layer workflow. Use scripts/qveris_workflow_guards.mjs for the applicable pre-prose gates.
Use references/qveris-finance-retry-policy.md for 5xx, fetch failures, 404s, payload truncation, and semantic mismatches.
Build trace, call counts, retries, and timestamps only from saved observed_calls. Never invent an execution ID or planned call; 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, models, and routing metadata recursively; the Trace row remains exactly tool_name, params, status, execution_id, fallback_used, and missing_fields.
Reject transport-success payloads that return the wrong entity, wrong benchmark, wrong date window, wrong fiscal period, too-thin bars, empty relevant fields, or corrupted text.
Suppress target prices, upside/downside, ratings, buy/sell wording, rebalancing instructions, trade triggers, automated execution plans, and prediction commitments.
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 · 122 lines

Files

What ships with it

22 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 · 122 lines · 78 tokens per session scan A f6a333135260

Subscribe to this mod's changes

qveris-alphaear-market-intelligence is a skill published in the GitHub repository QVerisAI/open-qveris-skills (21 stars, last pushed 8d ago), licensed MIT. It adds 78 tokens to every session and 3,048 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.

Analytics and metrics Finance and fintech

sector-rotation

An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.

HKUDS/Vibe-Trading · 39 tokens

strategy-pivot-designer

Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.

tradermonty/claude-trading-skills · 28 tokens

twitter-reader

Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my…

himself65/finance-skills · 161 tokens

qveris-alphaear-market-intelligence