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Hermes Agent b0d790be34 Add all 104 active skills from all 16 Hermes profiles
12 unversioned skills now versioned at 1.0.0:
agent-communication, ascii-video, external-reasoning-augmentation,
jotty-notes-api, minecraft-modpack-server, obsidian, pokemon-player,
powerpoint, social-search, songwriting-and-ai-music,
workspace-context-organization, youtube-content

Total repo: 141 skills across all profile scopes
2026-07-04 11:44:04 -05:00

3.5 KiB

name, description, version, author, license, category
name description version author license category
political-research Research U.S. political topics, legislation, and current events with source-filtering — prioritizing conservative/right-leaning outlets and social media sentiment. 1.0.0 Hermes Agent MIT research

Political Research

Research U.S. politics, legislation, and current events with a focus on source quality and ideological balance.

Trigger

Load this skill when:

  • User asks about U.S. politics, legislation (acts, bills), election topics, or policy issues
  • User asks for social media consensus or public sentiment on a political topic
  • User explicitly requests conservative/right-leaning sources (e.g., "avoid left leaning sources")
  • User asks for your own opinion on a political topic

Source Filtering

Default approach: Always supplement with a mix of sources.

When user specifies conservative/right-leaning (explicitly or via "avoid left leaning"):

  1. Prioritize these sources first: Fox News, WSJ Opinion, The Hill, CNBC, PBS, factually.co
  2. Include social media sentiment from conservative/right-leaning corners (Twitter/X, Facebook, Truth Social, Reddit r/law)
  3. Label left-leaning sources (Brennan Center, Common Cause, NPR general coverage, Politico opinion) when you use them
  4. Distinguish commentary from raw social data — social media posts are data; op-eds are commentary

Left-leaning sources to de-emphasize when requested: Brennan Center, Common Cause, ACLU, progressive op-eds, left-leaning advocacy orgs, general NPR coverage

Workflow

  1. Initial search — broad web search for the topic and current status
  2. Filtered search — re-run with source constraints if user specified (e.g., "avoid left leaning")
  3. Social media layer — search for Twitter/X, Facebook, Reddit, Truth Social reactions
  4. Polls and data — include polling data when available (Navigator Research, Gallup, etc.)
  5. Synthesize — present findings organized by theme, not by source

Social Media Analysis

When analyzing social media sentiment:

  • Don't just aggregate — identify the dominant frames and narratives
  • Distinguish between: elite opinion (senators, politicians posting), media commentary, and grassroots reaction
  • Note the gap — what people say online vs. what polls show may differ
  • Call out the surprise voices — conservative senators defying Trump, or Democrats supporting popular bills

Opinion Delivery

When the user asks for your opinion ("what do you think"):

  • Be direct — state the opinion clearly up front
  • Ground it in the evidence — reference specific findings from the research
  • Acknowledge nuance — what's good vs. what's poorly executed
  • Keep it concise — no padding, no hedging unnecessarily

Pitfalls

  • Don't present polling numbers without context — a 60% approval number means different things depending on how the question was asked
  • Don't let the 60-vote Senate problem disappear into the weeds — always clarify whether a bill failed on substance or procedure
  • Avoid framing everything as a partisan fight — intra-party disagreements matter (e.g., 4 GOP senators against Trump's bill)
  • Don't conflate social media buzz with actual consensus — loud voices online don't always represent majority opinion
  • When user says "avoid left leaning," mean it — don't just add Fox News on top of everything; re-run searches with source filters