sf-permissions▌
jaganpro/sf-skills · updated Apr 8, 2026
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Use this skill when the user needs permission analysis and access auditing: Permission Set / Permission Set Group hierarchy views, “who has access to X?” investigations, user-permission analysis, or permission-set metadata review.
sf-permissions
Use this skill when the user needs permission analysis and access auditing: Permission Set / Permission Set Group hierarchy views, “who has access to X?” investigations, user-permission analysis, or permission-set metadata review.
When This Skill Owns the Task
Use sf-permissions when the work involves:
- permission set / permission set group analysis
- user access investigation
- finding which permission grants object / field / Apex / flow / tab / custom-permission access
- auditing or exporting permission configuration
- reviewing permission metadata impacts
Delegate elsewhere when the user is:
- creating new metadata definitions → sf-metadata
- deploying permission sets → sf-deploy
- analyzing Apex-managed sharing logic → sf-apex
Required Context to Gather First
Ask for or infer:
- target org alias
- whether the question is about an object, field, Apex class, flow, tab, custom permission, or specific user
- whether the goal is hierarchy visualization, access detection, export, or metadata generation
- whether the output should be terminal-focused or documentation-friendly
Recommended Workflow
1. Classify the request
| Request shape | Default capability |
|---|---|
| “who has access to X?” | permission detector |
| “what does this user have?” | user analyzer |
| “show me the hierarchy” | hierarchy viewer |
| “export this permset” | exporter |
| “generate metadata from analysis” | generator or handoff |
2. Connect to the correct org
Verify sf auth before running permission analysis.
3. Use the narrowest useful query
Prefer focused analysis over broad org-wide scans unless the user explicitly wants a full audit.
When choosing identifiers, prefer stable metadata names first:
PermissionSet.NamePermissionSetGroup.DeveloperNameCustomPermission.DeveloperName- object and field API names such as
AccountorAccount.AnnualRevenue Assignee.Username/ email for user-centric checks
Use Salesforce record IDs only when:
- the underlying object model requires
ParentIdorSetupEntityId, or - you are drilling into records returned by a prior read-only query in the same investigation
4. Render findings clearly
Use:
- ASCII tree or table output for terminal work
- Mermaid only when documentation benefit is clear
- concise summaries of which permission source grants access
5. Hand off creation or deployment work
Use:
- sf-metadata for richer metadata generation
- sf-deploy for deployment
High-Signal Rules
- distinguish direct Permission Set grants from grants via Permission Set Groups
- prefer
Name/DeveloperName/ API names over org-specific record IDs for first-pass investigation queries - be explicit about whether access is object-level, field-level, class-level, flow-level, or custom-permission-based
- use Tooling API where required for setup entities and advanced visibility questions
- for agent access questions, verify exact agent-name matching in permission metadata
- when a follow-up child query requires
ParentIdorSetupEntityId, resolve the ID from a prior result instead of starting with copied IDs
Output Format
When finishing, report in this order:
- What was analyzed
- Org / subject scope
- Which permissions grant access
- Whether access is direct or inherited
- Recommended follow-up
Suggested shape:
Permission analysis: <hierarchy / detect / user / export>
Scope: <org, user, permission target>
Findings: <permsets / groups / access level>
Source: <direct assignment or via group>
Next step: <export, generate metadata, or deploy changes>
Cross-Skill Integration
| Need | Delegate to | Reason |
|---|---|---|
| generate or modify permission metadata | sf-metadata | metadata authoring |
| deploy permission changes | sf-deploy | rollout |
| identify Apex classes needing grants | sf-apex | implementation context |
| bulk user assignment analysis | sf-data | larger data operations |
Reference Map
Start here
Specialized analysis
Score Guide
| Score | Meaning |
|---|---|
| 90+ | strong permission analysis with clear access sourcing |
| 75–89 | useful audit with minor gaps |
| 60–74 | partial visibility only |
| < 60 | insufficient evidence; expand analysis |
How to use sf-permissions on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add sf-permissions
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches sf-permissions from GitHub repository jaganpro/sf-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate sf-permissions. Access the skill through slash commands (e.g., /sf-permissions) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★39 reviews- ★★★★★Mateo Gonzalez· Dec 28, 2024
I recommend sf-permissions for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Shikha Mishra· Dec 20, 2024
sf-permissions reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Arjun Chawla· Dec 20, 2024
Registry listing for sf-permissions matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Camila Khanna· Nov 27, 2024
sf-permissions is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Sakshi Patil· Nov 19, 2024
sf-permissions is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Noor Li· Nov 19, 2024
sf-permissions reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Yash Thakker· Nov 11, 2024
I recommend sf-permissions for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Ishan Choi· Nov 11, 2024
Useful defaults in sf-permissions — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Diego Jackson· Oct 18, 2024
Keeps context tight: sf-permissions is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Chaitanya Patil· Oct 10, 2024
Keeps context tight: sf-permissions is the kind of skill you can hand to a new teammate without a long onboarding doc.
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