Use this skill when the user needs trace-based observability, not just testing: extract Session Tracing Data Model (STDM) records, work with Parquet datasets, reconstruct session timelines, analyze topic/action latency, or debug agent behavior from Data 360 telemetry.
Automate repetitive workflows and reduce manual effort
Example: Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example: Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example: Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add jaganpro/sf-skills --skill sf-ai-agentforce-observabilityCompatible with
Supported agents
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionsf-ai-agentforce-observabilityExecute the skills CLI command in your project's root directory to begin installation:
epx add jaganpro/sf-skills --skill sf-ai-agentforce-observabilityFetches sf-ai-agentforce-observability from jaganpro/sf-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/sf-ai-agentforce-observability
Restart Cursor to activate sf-ai-agentforce-observability. Access via /sf-ai-agentforce-observabilityin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
sf-ai-agentscript
jaganpro/sf-skills · AI/ML · same repo
observability-monitoring-monitor-setup
sickn33/antigravity-awesome-skills · Productivity · tag: observability
llm-council
am-will/codex-skills · AI/ML · same category
pretty-mermaid
imxv/pretty-mermaid-skills · AI/ML · same category
ml-engineer
sickn33/antigravity-awesome-skills · AI/ML · same category
claude-md-management
giuseppe-trisciuoglio/developer-kit · AI/ML · same category
sf-ai-agentforce-observability reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend sf-ai-agentforce-observability for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
sf-ai-agentforce-observability is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added sf-ai-agentforce-observability from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in sf-ai-agentforce-observability — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Useful defaults in sf-ai-agentforce-observability — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for sf-ai-agentforce-observability matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: sf-ai-agentforce-observability is the kind of skill you can hand to a new teammate without a long onboarding doc.
sf-ai-agentforce-observability has been reliable in day-to-day use. Documentation quality is above average for community skills.
sf-ai-agentforce-observability has been reliable in day-to-day use. Documentation quality is above average for community skills.
showing 1-10 of 75