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 Day1Labs/OpenAva --skill equity-researchgit clone --depth 1 https://github.com/Day1Labs/OpenAvaWrote 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/day1labs/openava/equity-research)<a href="https://agentmods.dev/skills/day1labs/openava/equity-research"><img src="https://agentmods.dev/badge/skills/day1labs/openava/equity-research.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00050 | $0.01589 |
| Opus 5 | $0.00025 | $0.00794 |
| Sonnet 5 | $0.00010 | $0.00318 |
| Haiku 4.5 | $0.00005 | $0.00159 |
Grade A, and why
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 6d 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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Equity Research Analyst
Inputs
target: Company name or stock ticker (required)market: Trading venue (optional, e.g.US/HK/CN)report_language: Report language (optional, defaults to the user's language)
Skill Goals
- Deliver a traceable, explainable, and structured deep research report.
- Keep data, facts, and inference aligned to avoid unsupported conclusions.
- Make uncertainty and risk boundaries explicit; avoid absolute claims.
Core Execution Principles
- Stay goal-oriented: dynamically choose equivalent runtime capabilities instead of hard-binding to one fixed method.
- Facts first, judgment second; every key conclusion must be evidence-backed.
- Source priority: official IR/earnings disclosures > top-tier financial media > community discussions.
- If critical data is missing, explicitly state the gap and its impact on conclusions.
- Separate structural drivers from event-driven shocks, and label their time horizon impact (short/mid term).
- For policy or geopolitical topics, use multiple sources and avoid single-source narratives.
Goal 1: Build a Reliable Data Baseline (Required)
You must collect and verify the following data (Yahoo Finance basis):
- Real-time/near real-time market snapshot: current price, daily % change, market cap.
- Core financial indicators: P/E ratio, EPS.
- Historical daily series:
- 5-year price and volume;
- 12-month price and volume.
Requirements:
- You must explicitly state: market data may be delayed and is for reference only.
- If anomalies appear (missing points, trading halt, extreme spikes), explain how they are handled.
Goal 2: Deliver Fundamental Analysis from the Latest Earnings (Required)
Extract key information centered on the latest quarterly earnings, including:
- Revenue and YoY/QoQ trend;
- Net income and earnings quality;
- Performance by key business segments;
- Management guidance.
Output must include two sections:
- Highlights
- Risks
Source priority:
What ships with it
1 file 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.
- 6d ago First seen · 175 lines · 50 tokens per session scan A 0394a5e480ce
equity-research is a skill published in the GitHub repository Day1Labs/OpenAva (10 stars, last pushed 1mo ago), licensed MIT. It adds 50 tokens to every session and 1,589 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 2026-08-31.
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