Domain-Specific Skills
SkillSearchLets your agent review SAP Commerce Go code, write SIEM detection rules, validate WordPress posts, and tune enterprise search.
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Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Domain-Specific Skills skill
About this skill
Domain-specific: SAP Commerce, OpenSearch detection, WordPress validation, enterprise search.
What this skill tells your AI
The instructions your AI receives, as published by notque/vexjoy-agent in skills/domain/domain/SKILL.md and read by ahel’s review.
Five domains: SAP Commerce Go review, SAP Commerce compliance audit, OpenSearch SIEM detection engineering, WordPress live validation, and enterprise search. Classify the request into one domain, then follow its section.
Mode Detection
| Domain | Signal | Agent |
|---|---|---|
| SAPCC Review | sapcc review, 10-specialist review, lead review | golang-general-engineer |
| SAPCC Audit | sapcc audit, sapcc compliance, full repo audit | golang-general-engineer |
| OpenSearch Detection | SIEM, SIGMA, MITRE, detection engineering, SOC | (this session) |
| WordPress Validation | validate wordpress post, check live post, post rendering | (this session) |
| Enterprise Search | search relevance, ranking, BM25, query understanding | opensearch-elasticsearch-engineer |
SAPCC Review
10-agent domain-specialist review. Each agent masters one rule domain and scans every package. Differs from SAPCC Audit: audit segments by package (generalist), review segments by rule domain (specialist, cross-package).
Phase 1: DISCOVER
Verify sapcc project and map the repo.
head -5 go.mod && grep -c "sapcc" go.mod
find . -name "*.go" -not -path "*/vendor/*" | wc -l
find . -name "*.go" -not -path "*/vendor/*" | sed 's|/[^/]*$||' | sort | uniq -c | sort -rn
Check key imports: go-bits, go-api-declarations, gophercloud, gorilla/mux, database/sql.
Gate: Repo mapped. If no sapcc imports, warn but continue.
Phase 2: DISPATCH
Load references/sapcc-review-agent-dispatch-prompts.md for the 10 agent specs.
Dispatch all 10 in ONE message via Agent tool. Each agent gets: path to sapcc-code-patterns.md, assigned sections, domain-specific reference, all .go files to scan, finding output format.
Gate: All 10 dispatched in single message.
Phase 3: AGGREGATE
Run git status --short to capture modified and untracked files. Collect all
findings. Deduplicate by file:line (keep higher severity). Apply severity
boosts:
| Pattern Strength | Boost |
|---|---|
| NON-NEGOTIABLE (4+ repos) | +1 level |
| Strong Signal (2-3 repos) | No change |
| Context-Specific (1 repo) | -1 level |
Mark quick wins (single-line, no behavioral change, low test risk). Write
sapcc-review-report.md with: verdict, scorecard (10 domains x severity),
quick wins, findings by severity, positives, systemic recommendations.
Phase 4: FIX (only with --fix)
Create worktree sapcc-review-fixes. Apply quick wins first. After each group:
go build ./... && go vet ./... && make check 2>/dev/null || go test ./....
If fix breaks tests, revert and note. Commit as
fix: apply sapcc-review findings (N fixes across M files).
SAPCC Audit
Full-repo compliance scan. Segments by package (generalist per package).
Phase 1: DISCOVER
Verify sapcc project (grep "sapcc" go.mod). Map packages:
find . -name "*.go" -not -path "./vendor/*" | sed 's|/[^/]*$||' | sort -u.
Count files per package. Plan 5-8 agents, 5-15 files each.
Gate: Packages mapped, agents planned.
Phase 2: DISPATCH
Load references/sapcc-audit-phase-2-dispatch-agents.md for the dispatch prompt
(11 review areas: over-engineering, dead code, error messages, constructors,
interface contracts, copy-paste, HTTP handlers, database patterns, type patterns,
logging, mixed approaches). Dispatch all in one message via Task tool with
subagent_type=golang-general-engineer.
Phase 3: COMPILE REPORT
Deduplicate by file:line. Write sapcc-audit-report.md with: verdict,
must-fix/should-fix/nit counts, per-package summary table. Display verdict,
must-fix count, and top 5 findings inline.
Finding format: [MUST-FIX/SHOULD-FIX/NIT]: summary with file:line, current
code, correct code, and rationale.
Audit only: reads and reports. Does not modify code unless --fix.
OpenSearch Detection Engineering
SIEM detection authoring and validation on OpenSearch Security Analytics: SIGMA rules, query DSL translation, MITRE ATT&CK mapping, anomaly detection, correlation, and SOC incident escalation.
Hardcoded Behaviors
- MITRE ATT&CK on every detection. Include technique ID (e.g., T1110.003)
- tactic name + kill chain phase. Tactic alone is insufficient.
- Field-existence check before rule creation. Run
GET {index}/_mapping; confirm every rule field exists. Absent fields cause silent failure. - Concrete API commands. Provide
PUT _mapping,POST _aliases, not abstract advice. - Escalation validation. Verify all 9 fields before escalation: ticket ID, alert link, MITRE mapping, timeline, investigation actions, impact analysis, evidence artifacts, containment recommendation, 5 Ws.
- Severity tier = binding SLA. Not advisory targets.
- Detection-owned index. When bootstrapping field aliases, recommend a dedicated index separate from the ingestion datastream.
Hard Gates
| Pattern | Fix |
|---|---|
| Rule field absent from index mapping | GET {index}/_mapping; confirm or add field |
| MITRE mapping missing technique ID or tactic | Specify both T####.### and tactic |
| Escalation missing any of 9 fields | Complete all fields per checklist |
| Chained findings monitor on high-frequency schedule | Use static query indices |
| Field alias bootstrap on shared datastream | Create detection-owned index |
Workflow
- Scope: Identify attack scenario, data source, severity tier. Map to MITRE ATT&CK. Confirm log source is ingested.
- Validate fields:
GET {index}/_mappingfor each rule field. Check cardinality fortermsaggregations. - Author: Write SIGMA rule (vendor-neutral), translate to OpenSearch DSL.
Load
references/opensearch-detection-engineering.mdfor translation patterns. Apply FP suppression (CIDR, service-account prefixes, time windows). - Safety check: Check for index flood, alias bootstrap risk. Load
references/opensearch-detection-safety-patterns.mdfor the full checklist. - Document: 6-section use case (General Info, Context, Outcomes, Detection
Logic, Continuous Improvement, Analyst Support). Load
references/opensearch-incident-escalation.mdfor template and KPIs. - Calibrate: Dry-run 5 business days, label TPs/FPs, adjust until FP rate <= 10%.
- Escalation (when alert fires): Build 9-field package, apply SLA, hand off per RACI.
Verification STOP Blocks
After authoring: "Have I verified every field via GET {index}/_mapping?"
After escalation: "Does the package include all 9 fields?"
After chained monitor: "Does this create a new query index per run?"
After MITRE mapping: "Did I include both technique ID and tactic?"
WordPress Live Validation
Loads a published WordPress post in a headless browser and verifies rendering matches what was uploaded. The browser is the source of truth.
Browser backend: Playwright MCP (default). Chrome DevTools MCP when the user says "check in my browser" or wants Lighthouse/performance profiling.
Constraints
- Read-only. Never click, type, or modify the WordPress site.
- Evidence-based. Every result references a DOM value, network response, or screenshot. No "looks fine."
- Non-blocking. Failed validation produces a report; does not revert uploads.
- Severity: BLOCKER (broken content), WARNING (degraded but functional), INFO (informational).
- Requires Playwright MCP or Chrome DevTools MCP. If neither available, skip.
Phase 1: NAVIGATE
Load references/wordpress-phase-checks.md for the 4-step procedure. Navigate
to URL, wait for content area (try selectors: article -> .entry-content ->
.post-content -> main), remove cookie banners.
Gate: HTTP 200, content selector found. If 4xx/5xx or no selector: screenshot, FAIL, STOP.
Phase 2: VALIDATE
Load references/wordpress-validation-checks.md for severity rationale and edge
cases. Load references/wordpress-playwright-tools.md for tool signatures.
Run all 7 checks:
| Check | Severity |
|---|---|
| Title match | BLOCKER |
| H2 structure | WARNING |
| Image loading | BLOCKER |
| JS console errors | WARNING |
| OG tags | WARNING |
| Meta description | WARNING |
| Placeholder/draft text | BLOCKER |
Execute each check via browser tools. Do not reason about outcomes -- run the command and report observed results.
Gate: All 7 checks executed with severity and evidence.
Phase 3: RESPONSIVE CHECK
Test three viewports: mobile (375x812), tablet (768x1024), desktop (1440x900).
Per viewport: resize, screenshot, check overflow, check container visibility.
See references/wordpress-phase-checks.md for JS snippets.
Phase 4: REPORT
Output structured report:
LIVE VALIDATION: {url}
CONTENT INTEGRITY: [PASS/FAIL/WARN] per check with evidence
SEO / SOCIAL: OG tags, meta description with values
RESPONSIVE: per viewport with overflow status and screenshot path
RESULT: {PASS | FAIL - N blockers, M warnings}
Error Handling
| Error | Response |
|---|---|
| Playwright MCP unavailable | Skip report, do not retry |
| 4xx/5xx | Screenshot, report HTTP status, STOP at Phase 1 |
| Content selector not found | Screenshot + DOM snapshot; attempt OG checks without selector |
| Image network timeout | Report; if all fail, note possible CDN issue |
| Cookie banner blocks content | Phase 1 attempts DOM removal; DOM checks still work |
Enterprise Search
Search infrastructure: relevance tuning, query understanding, index management, quality measurement, performance optimization. Always specify target platform and version.
Sub-mode Detection
| Mode | Signal | Load |
|---|---|---|
| RELEVANCE | BM25, boost, LTR, ranking | references/search-relevance-tuning.md |
| QUERY | intent, entity extraction, expansion, synonyms | references/search-query-understanding.md |
| INDEX | schema, mapping, analyzer, reindex, ILM | references/search-index-management.md |
| QUALITY | nDCG, MRR, judgments, A/B test | references/search-search-quality.md |
| PERFORMANCE | slow query, shard, cache, circuit breaker | references/search-performance-optimization.md |
| ARCHITECTURE | hybrid search, vector search, platform selection | Load per sub-topic |
Always load references/search-llm-search-failure-modes.md as a guardrail.
Shared Workflow Pattern
- Diagnose the problem class before acting.
- Baseline current metrics. No tuning without measurement.
- Change one variable at a time.
- Validate against baseline. Accept only statistically significant improvements.
Platform Conventions
| Platform | Query Language | Config |
|---|---|---|
| Elasticsearch 8.x | Query DSL (JSON) | elasticsearch.yml |
| OpenSearch 2.x | Query DSL (JSON) | opensearch.yml |
| Solr 9.x | SolrQL / JSON Request API | solrconfig.xml |
| Vespa | YQL | services.xml |
| Typesense | REST params | CLI / JSON |
Cross-platform traps: OpenSearch diverges from ES 7.10 on security/ML/alerting.
ES _field_caps changed between 7.x and 8.x. Solr edismax != ES multi_match.
Output Rules
- All query DSL in fenced blocks with platform + version annotation.
- Every recommendation: what to change, why, expected effect, how to measure.
- Configuration snippets must be copy-pasteable with comments.
Deep References
Load on demand when a phase needs detailed lookup data.
| Context | Reference |
|---|---|
| SAPCC Review Phase 2: 10 agent specs | references/sapcc-review-agent-dispatch-prompts.md |
| SAPCC Audit Phase 2: dispatch prompt | references/sapcc-audit-phase-2-dispatch-agents.md |
| SIGMA authoring, DSL translation, MITRE catalog | references/opensearch-detection-engineering.md |
| Detector failures, alias conflicts, index flood | references/opensearch-detection-safety-patterns.md |
| Escalation checklist, severity SLAs, KPIs | references/opensearch-incident-escalation.md |
| WordPress check specs, severities, edge cases | references/wordpress-validation-checks.md |
| WordPress Playwright tool signatures | references/wordpress-playwright-tools.md |
| WordPress phase procedures with JS snippets | references/wordpress-phase-checks.md |
| Search relevance tuning, BM25, LTR, boosts | references/search-relevance-tuning.md |
| Query understanding, intent, expansion | references/search-query-understanding.md |
| Index management, schema, analyzers, ILM | references/search-index-management.md |
| Search quality metrics, evaluation methodology | references/search-search-quality.md |
| Search performance, caching, sharding | references/search-performance-optimization.md |
| LLM failure modes in search engineering | references/search-llm-search-failure-modes.md |
Signals
- GitHub stars
- 425
- Forks
- 46
- Last commit
- Sep 2026
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