create-evlog-enricher▌
hugorcd/evlog · updated Apr 8, 2026
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Scaffold a new built-in enricher for evlog with source, tests, and documentation across six mandatory touchpoints.
- ›Enrichers follow a strict architecture: info interface, factory function returning a context mutator, header lookup, field merging with overwrite control, and early returns for missing data
- ›Requires updates to enricher source code, test suite, built-in documentation, overview cards, public skill reference, and README enrichers table
- ›All six touchpoints are mandatory; the
Create evlog Enricher
Add a new built-in enricher to evlog. Every enricher follows the same architecture. This skill walks through all 6 touchpoints. Every single touchpoint is mandatory -- do not skip any.
PR Title
Recommended format for the pull request title:
feat: add {name} enricher
The exact wording may vary depending on the enricher (e.g., feat: add user agent enricher, feat: add geo enricher), but it should always follow the feat: conventional commit prefix.
Touchpoints Checklist
| # | File | Action |
|---|---|---|
| 1 | packages/evlog/src/enrichers/index.ts |
Add enricher source |
| 2 | packages/evlog/test/enrichers.test.ts |
Add tests |
| 3 | apps/docs/content/4.enrichers/2.built-in.md |
Add enricher to built-in docs |
| 4 | apps/docs/content/4.enrichers/1.overview.md |
Add enricher to overview cards |
| 5 | skills/review-logging-patterns/SKILL.md |
Add enricher to the Built-in line in the Enrichers section |
| 6 | README.md + packages/evlog/README.md |
Add enricher to README enrichers section |
Important: Do NOT consider the task complete until all 6 touchpoints have been addressed.
Naming Conventions
Use these placeholders consistently:
| Placeholder | Example (UserAgent) | Usage |
|---|---|---|
{name} |
userAgent |
camelCase for event field key |
{Name} |
UserAgent |
PascalCase in function/interface names |
{DISPLAY} |
User Agent |
Human-readable display name |
Step 1: Enricher Source
Add the enricher to packages/evlog/src/enrichers/index.ts.
Read references/enricher-template.md for the full annotated template.
Key architecture rules:
- Info interface -- define the shape of the enricher output (e.g.,
UserAgentInfo,GeoInfo) - Factory function --
create{Name}Enricher(options?: EnricherOptions)returns(ctx: EnrichContext) => void - Uses
EnricherOptions-- accepts{ overwrite?: boolean }to control merge behavior - Uses
mergeEventField()-- merge computed data with existing event fields, respectingoverwrite - Uses
getHeader()-- case-insensitive header lookup helper - Sets a single event field --
ctx.event.{name} = mergedValue - Early return -- skip enrichment if required headers are missing
- No side effects -- enrichers only mutate
ctx.event, never throw or log
Step 2: Tests
Add tests to packages/evlog/test/enrichers.test.ts.
Required test categories:
- Sets field from headers -- verify the enricher populates the event field correctly
- Skips when header missing -- verify no field is set when the required header is absent
- Preserves existing data -- verify
overwrite: false(default) doesn't replace user-provided fields - Overwrites when requested -- verify
overwrite: truereplaces existing fields - Handles edge cases -- empty strings, malformed values, case-insensitive header names
Follow the existing test structure in enrichers.test.ts -- each enricher has its own describe block.
Step 3: Update Built-in Docs
Edit apps/docs/content/4.enrichers/2.built-in.md to add a new section for the enricher.
Each enricher section follows this structure:
## {DISPLAY}
[One-sentence description of what the enricher does.]
**Sets:** `event.{name}`
\`\`\`typescript
const enrich = create{Name}Enricher()
\`\`\`
**Output shape:**
\`\`\`typescript
interface {Name}Info {
// fields
}
\`\`\`
**Example output:**
\`\`\`json
{
"{name}": {
// example values
}
}
\`\`\`
Add any relevant callouts for platform-specific notes or limitations.
Step 4: Update Overview Page
Edit apps/docs/content/4.enrichers/1.overview.md to add a card for the new enricher in the ::card-group section (before the Custom card):
:::card
---
icon: i-lucide-{icon}
title: {DISPLAY}
to: /enrichers/built-in#{anchor}
---
[Short description.]
:::
Step 5: Update skills/review-logging-patterns/SKILL.md
In skills/review-logging-patterns/SKILL.md (the public skill distributed to users), find the Enrichers section and add the new enricher to the Built-in: line:
Built-in: `createUserAgentEnricher()`, `createGeoEnricher()`, ..., `create{Name}Enricher()` — all from `evlog/enrichers`.
Step 6: Update README
Add the enricher to the enrichers section in packages/evlog/README.md (the root README.md is a symlink to it). Add the enricher to the enrichers table with its event field and output shape.
Verification
After completing all steps, run:
cd packages/evlog
bun run build # Verify build succeeds
bun run test # Verify tests pass
How to use create-evlog-enricher 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 create-evlog-enricher
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches create-evlog-enricher from GitHub repository hugorcd/evlog 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 create-evlog-enricher. Access the skill through slash commands (e.g., /create-evlog-enricher) 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
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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
4.4★★★★★28 reviews- ★★★★★Michael Sethi· Dec 16, 2024
create-evlog-enricher reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Ava Rao· Dec 12, 2024
create-evlog-enricher has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Shikha Mishra· Dec 8, 2024
I recommend create-evlog-enricher for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Yash Thakker· Nov 27, 2024
create-evlog-enricher fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Evelyn Kapoor· Nov 7, 2024
We added create-evlog-enricher from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Kaira Okafor· Nov 3, 2024
Solid pick for teams standardizing on skills: create-evlog-enricher is focused, and the summary matches what you get after install.
- ★★★★★Hassan Jackson· Oct 26, 2024
Keeps context tight: create-evlog-enricher is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Ava Gill· Oct 22, 2024
I recommend create-evlog-enricher for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Dhruvi Jain· Oct 18, 2024
create-evlog-enricher has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Oshnikdeep· Sep 25, 2024
Keeps context tight: create-evlog-enricher is the kind of skill you can hand to a new teammate without a long onboarding doc.
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