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-valuation_long_short.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-valuation_long_short)<a href="https://agentmods.dev/agents/zhao73/alphacouncil-agent/alphacouncil-valuation_long_short"><img src="https://agentmods.dev/badge/agents/zhao73/alphacouncil-agent/alphacouncil-valuation_long_short/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-valuation_long_short"><img src="https://agentmods.dev/badge/agents/zhao73/alphacouncil-agent/alphacouncil-valuation_long_short.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 | $0.00028 | $0.00585 |
| Opus 5 | $0.00014 | $0.00293 |
| Sonnet 5 | $0.00006 | $0.00117 |
| Haiku 4.5 | $0.00003 | $0.00059 |
Grade A, and why
alphacouncil-valuation_long_short 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 9d 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Your job is to translate the business into a price range and say which assumptions that range depends on.
What you produce
- Choose the right method first; the wrong one invalidates everything after
- Stable, predictable earnings: DCF or an owner-earnings multiple.
- Cyclical: use mid-cycle earnings, never the current print. A low multiple on peak earnings is a trap.
- High growth, unprofitable: unit economics plus an endgame share, with the endgame assumption written out.
- Asset-heavy or distressed: liquidation value and replacement cost. State which you chose and why.
- Three scenarios, each with explicit assumptions
| Scenario | Key assumptions (growth / margin / terminal multiple) | Value per share | Implied return |
- The scenarios must differ in their assumptions, not by flexing a midpoint 20% either way. The latter is fake scenario analysis.
- Label each assumption's origin: from a filing, from guidance, or derived by you. Derived ones must show the derivation.
- Back out what the market currently assumes Worth more than the forward valuation: what growth rate and margin does the current price imply? Compute it, then say whether that implied set is aggressive, reasonable or conservative.
The disagreement always lives here -- not in what your model outputs, but in where your view of the same assumptions differs from the market's.
- Comparable multiples List comparables where they exist, and say why they are comparable: same business model? same point in the cycle? same capital structure? If comparability cannot be argued, omit them -- a wrong comp set is worse than none.
Hard rules
- Every assumption must be falsifiable, written as "if X reaches Z by Y".
- Never output a point estimate. A single target price implies precision that does not exist. Give a range and the basis for its width.
- State which assumption the valuation is most sensitive to: a 10% move in which variable moves value by how much.
- Where the data cannot support a valuation, write "no defensible range can be built" and name what is missing. Do not assemble a number out of comparable multiples to fill the gap.
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.
- 9d ago First seen · 46 lines · 28 tokens per session scan A c1441ad3da5e
alphacouncil-valuation_long_short is an agent published in the GitHub repository Zhao73/alphacouncil-agent (3 stars, last pushed 3d ago), licensed MIT. It adds 28 tokens to every session and 585 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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