Use an AI Agent to Create a Finance News Review Gate Before Sharing Market Takes

Reader persona: a founder, community operator, newsletter writer, sales leader, or small investment team member who needs to share market context but does not want an AI agent publishing sloppy finance takes.

Job to be done: build a review gate where an AI agent gathers and organizes finance news, but a human approves the final interpretation before anything is sent externally.

The dangerous part of AI finance content is not bad grammar.

It is a clean, confident paragraph that blends three different things:

• something that happened;
• something someone thinks it means;
• something the agent guessed because it wanted to be helpful.

If that paragraph gets posted to a customer group, investor update, Telegram channel, sales note, or newsletter, you now have a trust problem.

The fix is not “never use AI for finance.”

The fix is to make the agent pass through a review gate before any market take leaves your workspace.

What a finance news review gate does

A review gate is a small workflow that forces the agent to separate:

facts → sources → interpretation → uncertainty → human approval

The agent can still do the tedious work:

• collect headlines;
• cluster related stories;
• identify recurring themes;
• draft a summary;
• flag missing context;
• prepare a publish-ready note.

But the agent does not get to silently turn that into advice, predictions, or public content.

The minimal workflow

Use this five-step workflow.

1. Gather
2. Normalize
3. Challenge
4. Draft
5. Approve

1. Gather

Tell the agent exactly where to look.

Example prompt:

Gather finance and market headlines from the approved sources only.
Use:
- major finance news sources;
- sector-specific sources relevant to our audience;
- prediction-market or sentiment sources only as supporting context.

Return raw headlines, source names, links, and timestamps where available.
Do not summarize yet.

If you use an Agent Skill such as alphaear-news from RKiding/Awesome-finance-skills, this is where the agent can call named source workflows instead of browsing randomly.

2. Normalize

Raw headlines are noisy.

Ask the agent to group them:

Group the headlines into:
- macro / rates / policy;
- sector moves;
- company-specific items;
- sentiment or social trend;
- prediction-market signals;
- noise / low-confidence items.

Merge duplicates. Keep the original sources attached.

This turns 30 links into a reviewable table.

Expected output:

| Theme | Claim | Sources | Confidence | Needs human check |
|---|---|---|---|---|
| Rate expectations | Markets pricing X scenario | Source A, Source B | Medium | Check latest timestamp |
| AI infrastructure | Chip supply story circulating | Source C | Low | Verify primary source |

The Needs human check column is the whole point.

3. Challenge

Before drafting, force the agent to argue against itself.

Prompt:

For each theme, list:
1. strongest supporting evidence;
2. weakest part of the claim;
3. what could make the interpretation wrong;
4. whether this belongs in the final update.

This stops the agent from treating every headline as equally meaningful.

It also makes it easier for a human reviewer to scan risk quickly.

4. Draft

Now let the agent write.

Prompt:

Draft a market update for non-specialist readers.
Rules:
- no buy/sell recommendations;
- separate facts from interpretation;
- mark uncertainty plainly;
- cite source names inline;
- include a short “what we are watching next” section;
- include a human-review checklist at the end.

A useful structure:

# Market Context Brief

## What happened

## Why it may matter

## What is still uncertain

## What we are watching next

## Human review checklist

This is more boring than a viral market take.

Good. Boring is safer.

5. Approve

The agent should stop before any external action.

Approval checklist:

- Are source links included?
- Are timestamps checked?
- Are facts and opinions separated?
- Is there any accidental financial advice?
- Is the audience appropriate for the level of uncertainty?
- Should this be sent, edited, or discarded?

Only after approval should the note be sent to Slack, Telegram, email, CRM, or a public channel.

A reusable agent instruction

Put this in your agent workspace:

When creating finance or market updates:
1. Never invent missing data.
2. Never give investment advice.
3. Always separate facts, interpretation, and uncertainty.
4. Always include sources and timestamps when available.
5. If a source fails, say so clearly.
6. Draft external messages only; do not send without explicit approval.
7. If the data is stale or conflicting, recommend waiting.

This instruction is simple, but it changes the agent’s posture.

The agent is no longer trying to be a market guru.

It is acting like a research assistant with a compliance-minded editor watching over its shoulder.

Example: turning noisy headlines into a safe update

Bad AI output:

Markets are clearly turning bullish on AI infrastructure, so now is a good time to increase exposure.

Better review-gated output:

Several sources point to renewed interest in AI infrastructure, especially around chip demand and cloud capex. The signal is directionally positive, but the evidence is still mixed: some headlines are based on company commentary, while others are social or sentiment-driven. We should verify earnings transcripts and primary filings before treating this as a durable trend.

The second version is less exciting.

It is also more useful.

Where this helps outside investing

This workflow is not only for investors.

Use it for:

• sales teams preparing context before enterprise calls;
• founders writing investor updates;
• community managers summarizing market news;
• B2B marketers tracking sector narratives;
• product teams watching competitor or regulatory shifts.

In each case, the agent is doing the first pass, not making the final judgment.

Add a confidence label

Require every claim to carry one of these labels:

High confidence — multiple reliable sources agree.
Medium confidence — plausible, but source coverage is incomplete.
Low confidence — social signal, single source, or unclear timestamp.
Do not use — unsourced, stale, duplicated, or too speculative.

This one addition makes finance summaries dramatically easier to review.

It also teaches the agent that not every collected item deserves a paragraph.

Where ClawMama fits

ClawMama can run this as a hosted OpenClaw/Hermes workflow:

• gather headlines from approved sources;
• normalize them into a review table;
• draft a market update;
• wait for human approval;
• send only after confirmation.

New users get $2 credits, and the agent can use the latest ChatGPT model for the reasoning and editing layer.

That setup is especially useful if you want a recurring daily or weekly brief but do not want the agent to have unchecked publishing power.

The best finance agent is not the one that sounds the smartest.

It is the one that makes uncertainty visible before a human acts.