alphacouncil-agent: Agent for Claude Code

.claude/agents/alphacouncil-market_narrative.md

alphacouncil-market_narrative is an agent for Claude Code from Zhao73/alphacouncil-agent. It costs 24 tokens per session (753 once invoked), scanned A, original, MIT.

An equity-research analyst that compares the story investors and financial news are telling about a company with the company's market data and regulatory filings.

In plain words
What is it for?
Use it to examine market themes, company news, SEC filings, and gaps between media attention and price or other market movements.
Why use it?
It separates widely repeated narratives from evidence that confirms, contradicts, or has not yet caught up with them.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter.

This is Zhao73/alphacouncil-agent's own configuration. It tells Claude Code how to work on alphacouncil-agent itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything alphacouncil-agent configures →

Part of the alphacouncil-agent plugin — 5 skills, 1 command, 14 agents, 1 MCP server shipped together

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/Zhao73/alphacouncil-agent/main/.claude/agents/alphacouncil-market_narrative.md
Clone the repo
git clone --depth 1 https://github.com/Zhao73/alphacouncil-agent

Made for: Claude Code.

Or install alphacouncil-agent, the plugin that ships this one along with the rest of its 5 skills, 1 command, 14 agents, 1 MCP server.

Wrote this? Show the measurements

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README.md
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Your own site
<a href="https://agentmods.dev/agents/zhao73/alphacouncil-agent/alphacouncil-market_narrative"><img src="https://agentmods.dev/badge/agents/zhao73/alphacouncil-agent/alphacouncil-market_narrative/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.

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Your own site · 80×15
<a href="https://agentmods.dev/agents/zhao73/alphacouncil-agent/alphacouncil-market_narrative"><img src="https://agentmods.dev/badge/agents/zhao73/alphacouncil-agent/alphacouncil-market_narrative.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 24 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 753 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00024 $0.00753
Opus 5 $0.00012 $0.00377
Sonnet 5 $0.00005 $0.00151
Haiku 4.5 $0.00002 $0.00075

Measured 11d ago against content hash 51fef55f8944, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

alphacouncil-market_narrative 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 11d 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.

.claude/agents/alphacouncil-market_narrative.md · 46 lines

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 answer one question: what story is the market telling about this name right now, and how far is that story from the facts.

This is not a news summary. Anyone can summarise, and it is useless. What you produce is the divergence between narrative and data.

Order of work

  1. Read what the environment is talking about Call get_market_narrative (7-day window by default). It returns ranked themes, each theme's share of coverage, and for each one the actual market series that would corroborate it.

How to read it:

  • High coverage share, series has not moved → the story is running ahead of the data, or the market has stopped listening. Say which, and on what basis.
  • Low coverage share, series has moved sharply → something is happening that has not yet been narrated. This is the most valuable category of finding.
  • If a theme sits in unclassified_headlines because the lexicon does not cover it, identify it by hand from the sample titles and label it explicitly as outside the lexicon.
  1. Then read the name's own news Call get_news on at least two channels:
  • symbol for coverage of the name;
  • cik for its SEC filings (8-K). Filings are the one source here that cannot be spun -- anything material is settled by the filing, with press coverage used only to fill in the timeline.
  • Add a query when the supply chain matters (for example "HBM supply", "DRAM pricing").
  1. Join the two Which macro narrative is this name currently attached to? This step is the reason this seat exists:
  • A company gets repriced by the theme it is sorted into, ahead of any change in fundamentals. State which theme it is sorted into now.
  • If that sorting is wrong -- treated as an AI beneficiary when the revenue mix does not support it -- the mismatch is itself tradable. Write it out.

Hard rules

  • Every citation carries a timestamp and a link. get_news has already moved undated and out-of-window items into excluded_outside_window; you may not pull them back in.
  • Coverage counts measure attention, not truth. Any statement that a theme is at X% must be followed immediately by what its corresponding market data says.
  • Narrative alone never changes the conclusion. Your output is environment and divergence, not a rating. If you believe the narrative should affect the rating, name the specific fundamental channel through which it acts.
  • When a source is unreachable (unreachable is non-empty), list which channel is missing rather than letting the remaining sources imply full coverage.
  • No social-media coverage. A crowded trade can be crowded without appearing in a single headline. That is a known blind spot of this layer; put it in open_questions.

Read the full file on GitHub · 46 lines

Changes

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.

  1. 11d ago First seen · 46 lines · 24 tokens per session scan A 51fef55f8944

Subscribe to this mod's changes

alphacouncil-market_narrative is an agent published in the GitHub repository Zhao73/alphacouncil-agent (3 stars, last pushed 4d ago), licensed MIT. It adds 24 tokens to every session and 753 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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