What is qveris-uzi-equity-research?

An equity-research workflow for companies listed in mainland China, Hong Kong, or the United States, covering valuation methods, trading activity, business risks, and data quality.

Use it to create research notes, quick scans, valuation-method and assumption audits, large-trader activity reviews, flow analysis, trap-risk checks, and investment-committee-style memos.

It organizes broad research while checking the quality of the evidence and avoiding unsupported investment conclusions.

qveris-uzi-equity-research — 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-uzi-equity-research

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-uzi-equity-research/github.svg)](https://agentmods.dev/skills/qverisai/open-qveris-skills/qveris-uzi-equity-research)

Your own site

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

Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,661 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	$0.00084	$0.02661
Opus 5	$0.00042	$0.01331
Sonnet 5	$0.00017	$0.00532
Haiku 4.5	$0.00008	$0.00266

Measured 12d ago against content hash 30e17514b1dc, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

qveris-uzi-equity-research 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 4 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-uzi-equity-research/SKILL.md · 111 lines

How it starts

The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.

QVeris UZI Equity Research

Use this skill to preserve UZI's broad equity-research, valuation, hot-money, and trap-risk review workflows while removing action-oriented conclusions and replacing scripts, persona scoring, and direct data routes with QVeris structured-data CAP evidence plus audited Web news/sentiment evidence.

Source record:

Field	Value
Candidate number	34
Original repository	UZI-Skill
GitHub URL	https://github.com/wbh604/UZI-Skill
License	MIT
Evaluation recent activity	2026-07-07
Local source snapshot	`third_party/source_repos/34-uzi-skill`
Snapshot latest commit	`fce996c` on 2026-07-07

Source Adaptation

Preserve the original coverage surface: deep equity research, quick scans, valuation frameworks, LHB/hot-money context, trap-risk review, and IC-style memos.
Remove persona voting, colorful action conclusions, browser fallbacks, local caches, and command scripts from runtime behavior.
Convert DCF, comps, LBO, and 3-statement work into method and assumption audits only. Do not output target prices, upside/downside, or investment conclusions.
Convert LHB and flow reads into conditional monitoring evidence; if QVeris specialty CAPs are absent or mismatched, mark them missing.
Convert trap detection into evidence-backed risk review: flag observable data-quality or promotion-risk signals only when QVeris evidence supports them.

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 Markdown, not a large JSON object or HTML report.
Accept dry_run, max_calls, max_age, budget_note, symbol, market, and review_type; echo the effective controls.
Read references/qveris-finance-data-quality-rubric.md before using any payload as evidence.
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, personas, 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 market, wrong asset type, 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 "safe to trade" conclusions.
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 for issuer news and qualitative sentiment in every run mode, including benchmark and replay.

Read the full file on GitHub · 111 lines

Files

What ships with it

20 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 · 111 lines · 84 tokens per session scan A 30e17514b1dc

Subscribe to this mod's changes

qveris-uzi-equity-research is a skill published in the GitHub repository QVerisAI/open-qveris-skills (21 stars, last pushed 8d ago), licensed MIT. It adds 84 tokens to every session and 2,661 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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