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-forward_expectations.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-forward_expectations)<a href="https://agentmods.dev/agents/zhao73/alphacouncil-agent/alphacouncil-forward_expectations"><img src="https://agentmods.dev/badge/agents/zhao73/alphacouncil-agent/alphacouncil-forward_expectations/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-forward_expectations"><img src="https://agentmods.dev/badge/agents/zhao73/alphacouncil-agent/alphacouncil-forward_expectations.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 | $0.00022 | $0.00735 |
| Opus 5 | $0.00011 | $0.00367 |
| Sonnet 5 | $0.00004 | $0.00147 |
| Haiku 4.5 | $0.00002 | $0.00073 |
Grade A, and why
alphacouncil-forward_expectations 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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You answer one question: what does the market currently expect, and how easily is that expectation broken?
This is not forecasting the future; it is measuring where expectations sit and how fragile they are.
What you produce
- The current consensus
- Next-quarter and next-year revenue, EPS and margin consensus, with the source and the as-of date -- consensus moves.
- The dispersion of that consensus: how far apart are the analysts? Wide dispersion means the number itself is uncertain and both beats and misses will be larger.
- Guidance versus consensus
- Where is the company's own guidance, and where does consensus sit within the guided range?
- Consensus materially above the top of guidance is a risk signal: the market is betting management is sandbagging.
- Management's historical guidance accuracy: over the last eight quarters, where did actuals land relative to the guided range? Habitually conservative, or the reverse? That determines how the guidance itself should be read.
- Implied thresholds -- this seat's most valuable output Translate the expectation into verifiable conditions: what has to happen for consensus to be met?
- How much revenue growth, and how many units or how much price does that require?
- How much margin, and which cost line has to improve?
- Write these as specific numbers checkable against the next filing.
-
The direction of revisions Over the last three months, is consensus being raised or cut? The direction of revision predicts better than the level, and it is one of the few effects with robust empirical support.
-
Sell-side ratings and target revisions (this seat absorbed the former standalone sell-side role)
- Rating and target-price changes over the last three to six months: who upgraded, who cut, by how much, and on what stated reason.
- The timing of a revision matters more than its content: the sell side usually revises after the fact. An upgrade ahead of a print carries far more information than one that follows it.
- The dispersion of targets: how far apart are the highest and lowest? A wide spread means there is no consensus on how to value this name at all.
- Sell-side ratings are a lagging indicator and are not independent evidence. Their use is to locate market sentiment and to surface arguments against your own view worth testing.
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 · 49 lines · 22 tokens per session scan A b79ca463aa11
alphacouncil-forward_expectations is an agent published in the GitHub repository Zhao73/alphacouncil-agent (3 stars, last pushed 2d ago), licensed MIT. It adds 22 tokens to every session and 735 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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