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 Zhao73/alphacouncil-agent --skill public-equity-investinggit clone --depth 1 https://github.com/Zhao73/alphacouncil-agentWrote 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/zhao73/alphacouncil-agent/public-equity-investing)<a href="https://agentmods.dev/skills/zhao73/alphacouncil-agent/public-equity-investing"><img src="https://agentmods.dev/badge/skills/zhao73/alphacouncil-agent/public-equity-investing/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/zhao73/alphacouncil-agent/public-equity-investing"><img src="https://agentmods.dev/badge/skills/zhao73/alphacouncil-agent/public-equity-investing.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00121 | $0.01387 |
| Opus 5 | $0.00060 | $0.00694 |
| Sonnet 5 | $0.00024 | $0.00277 |
| Haiku 4.5 | $0.00012 | $0.00139 |
Grade A, and why
public-equity-investing 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Public Equity Investing (bundled playbook)
This skill gives every AlphaCouncil analyst the same deep-research method without depending on
Codex's curated remote @public-equity-investing plugin. It is a runnable method with gates, not a
style guide. Evidence is gathered live via the agent's own web search (WebSearch + WebFetch).
Educational/research only. Not investment advice. Report missing data; never fabricate figures.
When to use
Whenever an AlphaCouncil evidence analyst runs. Each analyst applies the sourcing ladder and its role focus below, then returns the standard JSON evidence packet (see AlphaCouncil's Agent Output Contract). Keep JSON field names in English; write prose in the user's language.
Sourcing ladder (per claim, in order)
- Primary document first. Prefer the issuer/regulator over aggregators:
- filings → SEC EDGAR full-text (
sec.gov), 10-K/10-Q/8-K, 424B, Form 4; non-US → the local regulator / exchange filing (HKEX, SEHK, EDINET, etc.). - earnings → the 8-K Ex-99.1 press release and the IR deck / transcript on the company IR domain.
- price/quote → the exchange or a named quote page, with the exact as-of timestamp.
- filings → SEC EDGAR full-text (
- Dated, scoped search. Run a primary-locator query (restrict to
sec.gov+ the company IR/exchange domain), then a recency query (<ticker> <topic> <year>), then ONE mandatory disconfirming query (<ticker> guidance cut/downgrade/accounting concern/short thesis). - WebFetch the actual page and quote exact numbers with their real dates (signal date, source publication date, retrieval date are distinct).
- Corroborate any market-moving number across at least two independent sources; if only one exists,
mark confidence
mediumand say so. - Anything paywalled / stale / unfetchable →
open_questions. Do not invent it.
Role focus
market_data— price action, liquidity/volume, range vs 20/50/200-day, relative strength vs index/peers.earnings_deep_dive— last reported quarter: revenue/margins/segments, surprises vs consensus, guidance.forward_expectations— consensus estimates, implied beat/miss thresholds, what's priced in.sell_side_revisions— rating and target-price changes (who, when, from→to), dispersion of targets.earnings_call_transcript— management tone, commitments, hedges, repeated themes, Q&A pressure points.quant_factor— momentum, trend, volatility, volume/liquidity, relative strength, short interest, borrow, options IV/skew/expected move when available.valuation_long_short— see Valuation frameworks below; produce a long thesis AND a short thesis.news_industry_management— recent catalysts, industry context, regulatory/competitive backdrop.management_industry_voices— publicly verifiable commentary only; separate direct quote vs paraphrase vs media interpretation; never imply non-public information.insider_sec— Form 4 insider transactions, buybacks, dilution, debt, capital allocation.
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 · 92 lines · 121 tokens per session scan A 33e559e5d165
public-equity-investing is a skill published in the GitHub repository Zhao73/alphacouncil-agent (3 stars, last pushed 5d ago), licensed MIT. It adds 121 tokens to every session and 1,387 once invoked, about $0.0006 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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