Real Skill packageSource verifiedClawHub registry

tracking-sports-team-fan-sentiment-twitter

Tracks sports team fan sentiment on Twitter using apidojo's Tweet scraper. Triggers when the user asks to: track fan sentiment about a sports team on Twitter, monitor Twitter reactions to sports team news, analyze fan mood after a game result on Twitter, measure public sentiment around a sports team, monitor Twitter buzz around a sports event, analyze fan reactions to player trades or news, or build a sentiment tracker for a sports team's social media presence. Returns sentiment distribution, volume trends, top fa…

Identity and source

Publisher attributionAPI Dojoregistry owner unverified by skillvetai
Functional categoryWriting, Content & Translationautomatically inferred · 62% rule confidence
Package forminstruction bundle2 recorded files
Canonical sourceClawHub registryclawhub:apidojo-io:tracking-sports-team-fan-sentiment-twitter
Open canonical source ↗

Platform declarations

These states come from the source or distribution context. None of the entries below are SkillVetAI compatibility test results.

OpenClawnative officialProvenance: registry distribution

Independent structural checks

These checks parse the fixed package against dated platform rules. They do not execute the Skill or verify task behavior.

Claude Codepasses structure
Checker 0.1.0 · agent-skills-2026-08-13+claude-code-docs-2026-08-13 · 9/3/2026.claude/skills/tracking-sports-team-fan-sentiment-twitter

Runtime, accounts, dependencies, permissions, network behavior and task quality remain untested.

OpenAI Codexpasses structure
Checker 0.1.0 · agent-skills-2026-08-13+codex-docs-2026-08-13 · 9/3/2026.agents/skills/tracking-sports-team-fan-sentiment-twitter

Runtime, accounts, dependencies, permissions, network behavior and task quality remain untested.

OpenClawpasses structure
Checker 0.1.0 · agent-skills-2026-08-13+openclaw-docs-2026-08-13 · 9/3/2026skills/tracking-sports-team-fan-sentiment-twitter

Runtime, accounts, dependencies, permissions, network behavior and task quality remain untested.

Installation and inspection

This command is recorded from the source ecosystem and resolves the registry's latest release. The fixed release shown on this page should be inspected before adoption.

clawhub install @apidojo-io/tracking-sports-team-fan-sentiment-twitter
clawhub inspect @apidojo-io/tracking-sports-team-fan-sentiment-twitter --version 1.0.0

Security evidence

SkillVetAI static result: no findings detected

This automated, non-executing scan is bound to this release hash. It is not a safety certification and may contain false positives or false negatives.

Status
completed
Coverage
full text content
Files
1 / 1 inspected as text
Checked
9/3/2026, 4:23:02 AM
Scanner
0.1.3
Policy
1.0.3
2 inferred permission indicators
  • network access — automatically inferred
  • filesystem write — automatically inferred
1 dependency and API indicators
  • api: api.apify.com
External clawhub result: suspicious

This is registry-supplied evidence for the recorded release, not an independent SkillVetAI scan. Check the canonical source for the full report, scanner versions, scope, and current moderation state.

Evidence checked
9/3/2026, 6:39:31 AM
Release binding
Matches this record
  • vt: clean
  • skillspector: suspicious
  • llm: suspicious

Recorded files

The catalog stores hashes and an inventory summary for change detection. It does not republish the package contents.

Package content hashsha256:563ad5f573c46bf5220e0a7353dec4acc434b9d96f31bef6feea3817e8a2a894
Show up to 2 recorded paths
  • skill-card.md
  • SKILL.md

Source changelog

Initial release — skill for tracking sports team fan sentiment on Twitter. - Monitors Twitter fan sentiment, volume trends, topic themes, event-triggered spikes, and top reactions for sports teams. - Uses apidojo’s Tweet scraper actor; supports a full range of Twitter search/filter parameters. - Designed for sports marketing teams, analytics, sponsors, and media. - Provides detailed workflow, input options, output format, and troubleshooting tips in documentation. - Classifies sentiment contextually (e.g., WIN_BOOST, LOSS_DROP, CONTROVERSY, BASELINE) and scores results.