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.
npx skills add QVerisAI/open-qveris-skills --skill qveris-investskillgit clone --depth 1 https://github.com/QVerisAI/open-qveris-skillsWrote 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.
[](https://agentmods.dev/skills/qverisai/open-qveris-skills/qveris-investskill)<a href="https://agentmods.dev/skills/qverisai/open-qveris-skills/qveris-investskill"><img src="https://agentmods.dev/badge/skills/qverisai/open-qveris-skills/qveris-investskill/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.
<a href="https://agentmods.dev/skills/qverisai/open-qveris-skills/qveris-investskill"><img src="https://agentmods.dev/badge/skills/qverisai/open-qveris-skills/qveris-investskill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00056 | $0.00969 |
| Opus 5 | $0.00028 | $0.00485 |
| Sonnet 5 | $0.00011 | $0.00194 |
| Haiku 4.5 | $0.00006 | $0.00097 |
Grade A, and why
qveris-investskill 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.
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.
How it starts
The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QVeris InvestSkill
Use this skill for US stock research workflows adapted from InvestSkill. Preserve the taxonomy around 10-K digest, bear case, catalysts, competitors, DCF inputs, and earnings calls; replace SEC scraping, external transcript sources, and third-party valuation feeds with QVeris filings, news, market, and fundamentals tools.
Source record:
| Field | Value |
|---|---|
| Candidate number | 5 |
| Original repository | InvestSkill |
| GitHub URL | https://github.com/yennanliu/InvestSkill |
| License | MIT |
| Evaluation recent activity | 2026-07-05 |
| Local source snapshot | third_party/source_repos/05-investskill |
| Snapshot latest commit | 49aa5da on 2026-07-05 |
Runtime Contract
- Use only
qveris_finance.*CAP tools andQVERIS_API_KEY. - Resolve symbols, companies, and CIKs with
ref_symbology,ref_security_master, andref_company_profile. - Accept
dry_run,max_calls,max_age, andbudget_note; if omitted in a natural-language request, default todry_run=false,max_calls=12,max_age=P1D, and a conservative budget note, then echo those controls. - Every filing quote, red flag, catalyst, metric, and transcript claim must carry
qveris_trace. - Treat missing filing sections or XBRL fields as
missing_fields, not facts. - Treat QVeris
_meta.source_provideras provenance only; never call, request credentials for, or depend on those internal providers directly. - Suppress
analyst_target_price,target_price, price-objective, upside, buy/sell, and recommendation fields even if a QVeris payload contains them. - Sanity-check entity, market, date window, filing form, accession, fiscal period, and payload shape before using data; if a payload is stale, cross-period, truncated, or semantically mismatched, mark it in
data_qualityandmissing_fields.
Workflows
- 10-K digest:
filings_regulatory_metadata,filings_regulatory_raw,filings_structured_xbrl. - Bear case/red flags:
filings_*,fundamentals_derived_ratios,news_fin_tagged,ownership_insider_trades. - Catalyst calendar:
event_calendar_corp,event_calendar_earnings,event_calendar_ipo,news_fin_realtime. - Competitor analysis:
ref_classification_industry,ref_classification_theme,fundamentals_derived_ratios,research_analyst_reports. - DCF valuation inputs:
fundamentals_is,fundamentals_bs,fundamentals_cf,estimates_consensus,rates_govt_benchmark,mkt_l1_rt. - Earnings call analysis:
transcripts_earnings_call,earnings_actual_surprise,estimates_consensus.
What ships with it
4 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.
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 · 59 lines · 56 tokens per session scan A 5468019acc88
qveris-investskill is a skill published in the GitHub repository QVerisAI/open-qveris-skills (21 stars, last pushed 8d ago), licensed MIT. It adds 56 tokens to every session and 969 once invoked, about $0.0003 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.
Other skills, from other repositories
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.
strategy-pivot-designer
Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.
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…
chenhao-limit-up
A framework for judging Chinese A-share stocks that have reached the daily price-rise limit, using market mood, sector leadership, and trading momentum.
furusato
A Japanese hometown-tax donation manager for furusato nozei, a system where donations to municipalities can qualify for an income-tax or local-tax deduction. It reads donation receipts, stores donation records, and calculates deduction limits.
reading-receipt
An image-reading workflow for extracting structured information from receipts, invoices, and hometown-tax donation certificates. It can first extract text from PDFs and otherwise read their images.