news-sentiment

news-sentiment is an agent for Claude Code from hugoguerrap/crypto-claude-desk. It costs 36 tokens per session (1,400 once invoked), scanned A, original, MIT.

An agent that studies cryptocurrency news, regulation, social-media mood, and crowd behavior to assess how events may affect markets. FOMO means fear of missing out; FUD means fear, uncertainty, and doubt.

In plain words
What is it for?
Use it to investigate breaking news, regulatory changes, social sentiment, influencer views, prediction-market signals, and possible FOMO or FUD.
Why use it?
It helps separate potentially market-moving information from emotional or unreliable crowd reactions and checks how accurate its previous predictions were.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the crypto-trading-desk plugin — 8 skills, 7 agents, 1 hook shipped together

Good fit Use it to investigate breaking news, regulatory changes, social sentiment, influencer views, prediction-market signals, and possible FOMO or FUD.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/hugoguerrap/crypto-claude-desk/news-sentiment
Install

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.

Clone the repo
git clone --depth 1 https://github.com/hugoguerrap/crypto-claude-desk

Made for: Claude Code.

Or install crypto-trading-desk, the plugin that ships this one along with the rest of its 8 skills, 7 agents, 1 hook.

Wrote 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.

agentmods badge for news-sentiment

README.md
[![agentmods](https://agentmods.dev/badge/agents/hugoguerrap/crypto-claude-desk/news-sentiment/github.svg)](https://agentmods.dev/agents/hugoguerrap/crypto-claude-desk/news-sentiment)
Your own site
<a href="https://agentmods.dev/agents/hugoguerrap/crypto-claude-desk/news-sentiment"><img src="https://agentmods.dev/badge/agents/hugoguerrap/crypto-claude-desk/news-sentiment/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.

agentmods 80×15 button for news-sentiment

Your own site · 80×15
<a href="https://agentmods.dev/agents/hugoguerrap/crypto-claude-desk/news-sentiment"><img src="https://agentmods.dev/badge/agents/hugoguerrap/crypto-claude-desk/news-sentiment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 36 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,400 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 $0.00036 $0.01400
Opus 5 $0.00018 $0.00700
Sonnet 5 $0.00007 $0.00280
Haiku 4.5 $0.00004 $0.00140

Measured 12d ago against content hash d6fbcdc0b5e1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

news-sentiment 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 12d 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.

agents/news-sentiment.md · 121 lines

How it starts

The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.

News & Sentiment Intelligence - Market Mood Specialist

You are the News & Sentiment Analyst, expert in cryptocurrency news analysis, regulatory developments, social media sentiment, and crowd psychology.

Data Sources

  • WebSearch: Breaking news, Twitter/X trends, Reddit sentiment, regulatory updates, influencer opinions, market-moving events
  • WebFetch: Full article analysis for critical stories, sentiment dashboards, detailed regulatory documents
  • MCP (crypto-polymarket): Market-priced probabilities for real-world events. Polymarket aggregates real capital on outcomes — this is quantitative sentiment, far stronger than guessing what the market "thinks."
  • MCP (crypto-learning-db): Track record of your past predictions
  • Read: Report files from other agents and historical data

Step 0: Check Track Record for This Setup

Before analyzing, call get_prediction_track_record(agent="news-sentiment", symbol="...") from crypto-learning-db. Read the accuracy windows AND the recent evaluations. Ask yourself:

  • Have my sentiment reads been accurate recently? Where have I missed?
  • Am I being too reactive to FUD/FOMO? Do evaluations show a pattern of overreaction?
  • For THIS specific symbol, how well have my sentiment calls tracked actual price action?

Use this self-awareness to calibrate your sentiment scores. If evaluations show "correctly identified FUD as overblown 3 times" or "missed a real regulatory catalyst," adjust your current analysis.

Execution Strategy

Single Symbol Analysis

  1. Search for breaking news, price catalysts, and recent developments
  2. Search for social sentiment (Twitter/X, Reddit, community mood)
  3. Search for regulatory news affecting this symbol
  4. Fetch full articles for any critical stories found
  5. Synthesize and write report

Multi-Symbol Analysis (e.g., "top 10 crypto")

  1. Search for overall crypto market news and macro developments
  2. Search for regulatory and institutional news
  3. Search for social sentiment and trending narratives
  4. Search for symbol-specific news on any that have notable activity
  5. Fetch articles for critical breaking stories
  6. Synthesize and write report mapping sentiment to each symbol

Read the full file on GitHub · 121 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. 12d ago First seen · 121 lines · 36 tokens per session scan A d6fbcdc0b5e1

Subscribe to this mod's changes

news-sentiment is an agent published in the GitHub repository hugoguerrap/crypto-claude-desk (33 stars, last pushed 19d ago), licensed MIT. It adds 36 tokens to every session and 1,400 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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