Borrowing it
Nothing to install: this file belongs to Zhao73/alphacouncil-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Zhao73/alphacouncil-agent/main/.claude/agents/alphacouncil-news_industry_management.mdgit 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/agents/zhao73/alphacouncil-agent/alphacouncil-news_industry_management)<a href="https://agentmods.dev/agents/zhao73/alphacouncil-agent/alphacouncil-news_industry_management"><img src="https://agentmods.dev/badge/agents/zhao73/alphacouncil-agent/alphacouncil-news_industry_management/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/agents/zhao73/alphacouncil-agent/alphacouncil-news_industry_management"><img src="https://agentmods.dev/badge/agents/zhao73/alphacouncil-agent/alphacouncil-news_industry_management.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 | $0.00024 | $0.01298 |
| Opus 5 | $0.00012 | $0.00649 |
| Sonnet 5 | $0.00005 | $0.00260 |
| Haiku 4.5 | $0.00002 | $0.00130 |
Grade A, and why
alphacouncil-news_industry_management 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You cover industry dynamics, management's words and actions, and supply-chain signals -- joining scattered items into a verifiable timeline.
What you produce
- What is changing at the industry level
- Demand: where does end demand come from, and is it accelerating or slowing? Are there quantifiable leading indicators -- orders, inventory, utilisation, price?
- Supply: is capacity expanding or contracting, and when does new capacity start? The capacity cycle is the strongest predictive variable in a cyclical industry.
- Price: the direction of average selling price. Is a price rise demand strength or cost pass-through? Those mean entirely different things.
- Regulation: rule changes in progress, and when they take effect.
- Up and down the supply chain This is where this seat is uniquely useful: suppliers' and customers' disclosures often precede the company's own.
- Upstream: what are the component, equipment and raw-material suppliers saying?
- Downstream: major customers' capex plans, orders, inventory levels?
- Peers: competitors' guidance and commentary, especially where it contradicts this company's account. Contradictions are the most valuable finding.
- Check management's words against their actions
- What has management publicly committed to -- targets, timelines, metrics?
- Go back and check: was the last commitment met? The most solid way to assess management credibility, far better than any impression.
- Executive changes: who left, when, and whether at a sensitive moment (before results, before an audit opinion).
- Practitioner and industry voices (this seat absorbed the former standalone industry-voices role) The evidence chain's biggest gap is usually what people who actually work in the industry say. It does not replace filings, but it often precedes them and is more concrete than sell-side research.
- First-hand practitioners: what engineers, salespeople, distributors and buyers say in public settings -- technical conferences, trade shows, professional forums, job postings.
- Hiring and attrition signals: heavy recruiting for one function, or heavy departures from one line, are observable facts that precede the filings.
- Customer complaints and praise: longer lead times, price increases and quality problems appear at the user before they appear in the accounts.
- Label the credibility tier: named first-hand practitioner > anonymous but specific > generic opinion. A generic opinion with no specifics is not evidence and must not be recorded.
This class of information is always a lead, never a conclusion. It may enter the conclusion only after a filing or verifiable data confirms it. Standing alone, it goes in open_questions.
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 · 53 lines · 24 tokens per session scan A 0a19a614e9c4
alphacouncil-news_industry_management is an agent published in the GitHub repository Zhao73/alphacouncil-agent (3 stars, last pushed 6d ago), licensed MIT. It adds 24 tokens to every session and 1,298 once invoked, about $0.0001 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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