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 agentmods add skills/yennanliu/investskill/industry-mapnpx skills add yennanliu/InvestSkill --skill industry-mapgit clone --depth 1 https://github.com/yennanliu/InvestSkillWrote 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/yennanliu/investskill/industry-map)<a href="https://agentmods.dev/skills/yennanliu/investskill/industry-map"><img src="https://agentmods.dev/badge/skills/yennanliu/investskill/industry-map.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 | $0.00036 | $0.04040 |
| Opus 5 | $0.00018 | $0.02020 |
| Sonnet 5 | $0.00007 | $0.00808 |
| Haiku 4.5 | $0.00004 | $0.00404 |
Grade A, and why
industry-map 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 — 320 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Industry Map — Supply & Value Chain
⚠️ Data Verification — Do This Before Any Analysis
Before running any analysis, always retrieve the latest market data for the ticker:
- Fetch current price — use web search or ask the user for the live price, 52-week range, and market cap. Never assume a price from training data.
- Confirm key figures — recent earnings, revenue, key ratios (P/E, P/S, etc.) as applicable to this skill.
- State your data source — note where the numbers came from (e.g., "Google Finance, June 19 2026") at the top of the output.
- Flag stale data explicitly — if live data is unavailable, display this warning before proceeding:
⚠️ Live data unavailable. The following analysis uses training-data estimates which may be significantly out of date. Verify all prices and metrics before making any decisions.
Never silently substitute training-data estimates for current prices. When in doubt, ask the user to paste the latest quote.
Draw an industry's supply and value chain as a directed graph — from raw inputs upstream all the way down to the end user — so you can take a bird's-eye view of a business, see where a company sits in the flow, understand where value and pricing power concentrate today, and reason about where they will migrate next.
Overview
Most analysis looks at one company in isolation. This skill zooms out and answers a different question: "How does this whole industry actually work, layer by layer, and who captures the profit at each stage?"
A value chain is a directed graph: nodes are the layers of production (raw materials → components → integrators → platforms → distribution → end users), and edges point in the direction goods and services flow — from supplier to customer. Once the chain is drawn, three things become visible that a single-company view hides:
- Position — is the target company upstream (inputs), midstream (integration/manufacturing), or downstream (distribution / end demand)? Position determines cyclicality, margin profile, and who has pricing power over whom.
- Chokepoints — the layer(s) with the fewest credible suppliers capture disproportionate value. Following the chain reveals bottleneck monopolies (e.g. EUV lithography, leading-edge foundry) that are the real toll-collectors of a theme.
- Value migration — the profit pool is not fixed. It shifts down (or up) the chain over time as scarcity moves. Mapping the chain lets you form a thesis about where the money goes next — the "picks-and-shovels" and second-order plays.
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 · 320 lines · 36 tokens per session scan A dc187519908c
industry-map is a skill published in the GitHub repository yennanliu/InvestSkill (199 stars, last pushed yesterday), licensed MIT. It adds 36 tokens to every session and 4,040 once invoked, about $0.0002 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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