social-signal-intelligence: Reusable for AI Agents | OpenAgentSkill

Overview

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Purpose

Turn X/Twitter evidence into product strategy inputs. Use Hermes Tweet to research public posts, profiles, trends, and product conversations, then summarize the signal in a format PMs can feed into strategy, competitive analysis, prioritization, pre-mortems, or decision logs.

Setup Checks

Inspect the tools available in the current session. Never infer availability from this Skill.
Require tweet_explore before starting any live workflow.
Require tweet_read before live research.
Require tweet_action and explicit approval before account-changing work.
Keep HERMES_TWEET_ENABLE_ACTIONS unset or false for read-only strategy work.

Runtime Boundary

This Skill provides instructions only. It does not install or expose Hermes tools in Claude Code.

If a required tool is unavailable, stop before live work. Explain that the user must run the workflow in Hermes Agent with the native Hermes Tweet plugin enabled. Do not invent results, silently substitute another tool, or imply that setup succeeded. You may still organize evidence the user already supplied.

Instructions

Classify the request:
- Discovery: the user asks what X/Twitter data or actions are available.
- Research: the user needs public posts, trends, accounts, or market signal evidence.
- Action: the user asks to post, reply, like, follow, DM, create monitors, run webhooks, start extraction jobs, upload media, or run giveaway actions.
Apply the runtime boundary. Stop if the tool required for this request is unavailable.
Use tweet_explore first to find the endpoint, capability, or route.
Use tweet_read only for catalog-listed public read-only endpoints.
Use tweet_action only after the user approves the exact endpoint, method, payload, and reason.
Cite returned public URLs and timestamps. Mark missing links as "URL not verified".
Connect findings to the relevant PM workflow:
- competitive-landscape for competitor positioning.
- strategy for market and user context.
- pre-mortem for launch risks.
- decision-log for evidence behind a product call.
- prioritization for demand and urgency signals.

Output Format

## Social Signal Brief
- Product or question:
- Query and window:
- Top signals:
- Evidence:
- PM implication:
- Risk or caveat:
- Recommended next step:

Safety Rules

Never ask for or reveal API keys, passwords, cookies, or TOTP secrets.
Never place credentials in tool arguments or PM artifacts.
Never invent handles, post URLs, metrics, account state, or trend strength.
Never claim live research ran when a required Hermes tool is unavailable.
Do not guess endpoint paths. Use the catalog returned by tweet_explore.
Do not retry writes through alternate routes after policy, auth, or account-state errors.
Summarize any account-changing action before calling tweet_action.

Install Reference

hermes plugins install Xquik-dev/hermes-tweet --enable
uv pip install --python ~/.hermes/hermes-agent/venv/bin/python hermes-tweet

View source ↗

File metadata

name: social-signal-intelligence
description: >-
  Use when a product manager needs X/Twitter market signals, launch feedback,
  competitor chatter, creator research, support triage, trend analysis, or an
  approved social action through Hermes Tweet.
argument-hint: "<product, competitor, launch, trend, or social workflow>"

View original text

---
name: social-signal-intelligence
description: >-
  Use when a product manager needs X/Twitter market signals, launch feedback,
  competitor chatter, creator research, support triage, trend analysis, or an
  approved social action through Hermes Tweet.
argument-hint: "<product, competitor, launch, trend, or social workflow>"
---

# Social Signal Intelligence

## Purpose

Turn X/Twitter evidence into product strategy inputs. Use Hermes Tweet to research public posts, profiles, trends, and product conversations, then summarize the signal in a format PMs can feed into strategy, competitive analysis, prioritization, pre-mortems, or decision logs.

## Setup Checks

1. Inspect the tools available in the current session. Never infer availability from this Skill.
2. Require `tweet_explore` before starting any live workflow.
3. Require `tweet_read` before live research.
4. Require `tweet_action` and explicit approval before account-changing work.
5. Keep `HERMES_TWEET_ENABLE_ACTIONS` unset or false for read-only strategy work.

## Runtime Boundary

This Skill provides instructions only. It does not install or expose Hermes tools in Claude Code.

If a required tool is unavailable, stop before live work. Explain that the user must run the workflow in Hermes Agent with the native Hermes Tweet plugin enabled. Do not invent results, silently substitute another tool, or imply that setup succeeded. You may still organize evidence the user already supplied.

## Instructions

1. Classify the request:
   - Discovery: the user asks what X/Twitter data or actions are available.
   - Research: the user needs public posts, trends, accounts, or market signal evidence.
   - Action: the user asks to post, reply, like, follow, DM, create monitors, run webhooks, start extraction jobs, upload media, or run giveaway actions.
2. Apply the runtime boundary. Stop if the tool required for this request is unavailable.
3. Use `tweet_explore` first to find the endpoint, capability, or route.
4. Use `tweet_read` only for catalog-listed public read-only endpoints.
5. Use `tweet_action` only after the user approves the exact endpoint, method, payload, and reason.
6. Cite returned public URLs and timestamps. Mark missing links as "URL not verified".
7. Connect findings to the relevant PM workflow:
   - `competitive-landscape` for competitor positioning.
   - `strategy` for market and user context.
   - `pre-mortem` for launch risks.
   - `decision-log` for evidence behind a product call.
   - `prioritization` for demand and urgency signals.

## Output Format

```text
## Social Signal Brief
- Product or question:
- Query and window:
- Top signals:
- Evidence:
- PM implication:
- Risk or caveat:
- Recommended next step:
```

## Safety Rules

- Never ask for or reveal API keys, passwords, cookies, or TOTP secrets.
- Never place credentials in tool arguments or PM artifacts.
- Never invent handles, post URLs, metrics, account state, or trend strength.
- Never claim live research ran when a required Hermes tool is unavailable.
- Do not guess endpoint paths. Use the catalog returned by `tweet_explore`.
- Do not retry writes through alternate routes after policy, auth, or account-state errors.
- Summarize any account-changing action before calling `tweet_action`.

## Install Reference

```bash
hermes plugins install Xquik-dev/hermes-tweet --enable
uv pip install --python ~/.hermes/hermes-agent/venv/bin/python hermes-tweet
```

Review the source

Skill source recorded

Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.

Review before install: Avoid automatic install

Dependency or permission surface needs review
Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
Low GitHub adoption signal

Open full audit

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Start with one small task

1Read the source. Confirm the input, expected output, dependencies and permissions.
2Ask your agent for a plan. Approve setup and any costs before running a small isolated test.
3Check the output and changed files. Report only what actually ran; keep the source revision for reproduction.

Check the source for dependencies, API keys and third-party costs. A public repository does not mean every service is free.

Source & trust

IndexedStatic Checked

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

License: MIT
Version: Unknown
Last GitHub push: Aug 14, 2026
Registry updated: Sep 9, 2026
Instruction path: plugins/hermes-tweet/skills/social-signal-intelligence/SKILL.md @ 76d959f69add

Version reported in registry metadata; check source releases before relying on it.

Quality

58/100

Promising

Trust

59/100

Do not auto-install

Audit

72/100

Needs review

Agent access

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Open install API LLM text format Open manifest Auto-resolve Plan

More details

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Creator: aniganti
Source: aniganti/pm-superpowers
Indexed by: OpenAgentSkill community index

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