
dt-sec-semantic-mapping
Suggest and validate semantic dictionary (SD) mappings for new security integrations using vendor API samples or live events. Use when: mapping a new security vendor data to Dynatrace SD; checking required fields; validating namespaces; highlighting discrepancies vs the semantic dictionary; proposing mapping improvements; running runtime validation against live tenant data.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/dynatrace/dynatrace-for-ai --skill dt-sec-semantic-mapping- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads dt-sec-semantic-mapping automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
dt-sec-semantic-mapping
Build and validate semantic-dictionary-aligned mappings for new security integrations.
Purpose
Use this skill when a user wants to:
- Suggest a mapping from vendor API output to Dynatrace
security.eventsfields (Workflow A). - Validate an existing mapping for completeness and quality against:
- Local baseline samples and semantic dictionary (Workflow B1 — static, offline validation), or
- Live tenant data via live tenant access (Workflow B2 — runtime validation)
- Highlight discrepancies vs. the Semantic Dictionary and local references.
- Get actionable mapping improvements.
Semantic Dictionary
The Semantic Dictionary (SD) defines the canonical field set for security.events. See references/semantic-reference.md for the canonical reference: local-vs-live sources, queryable Grail tables, when-to-query decision matrix, and the authority rule (live SD wins on disagreement).
Required Inputs
Always run the intake checklist in references/intake-and-constraints.md before generating or validating a mapping. If inputs are incomplete, continue with a partial draft but explicitly list missing evidence and confidence limits.
Baseline Sources (self-contained)
All baseline material lives inside this skill:
samples/— real integration payloads covering all finding types and providers. Consulted as a fallback when primary references (SD, data-model-notes, known-discrepancies, validation-rules, object-type-expectations) leave a specific question unresolved — not as a routine step on every workflow run.references/semantic-reference.md— SD reference, field taxonomy, event types, provider taxonomy, and entity scopingreferences/validation-policy-and-reporting.md— validation rules, acceptable discrepancies, and report templatesreferences/intake-and-constraints.md— intake checklist, output contract,object.typeexpectations, and OpenPipeline constraints
Event-Type Coverage Requirements
The mapping MUST address the correct set of event.type values per finding class. Detection integrations are push-based and do not use scan cycles — never require scan events for detection.
See validation-policy-and-reporting.md § Event-Type Coverage for the full table, severity rules, and the alternative-classification path when a detection-class mapping incorrectly emits *_SCAN events.
Workflows
This skill operates in three modes. Detect the mode from context:
| Mode | Input | Procedural source |
|---|---|---|
| Workflow A — Suggest a new mapping | Raw vendor API payloads only | references/mapping-workflow.md § Workflow A (Phase 1 mapping table → user approval → Phase 2 sample JSON) |
| Workflow B1 — Static validation | Existing mapping + vendor API samples | references/mapping-workflow.md § Workflow B — classify input mode (final ingested / theoretical), apply rules, produce diff-highlighted table |
| Workflow B2 — Runtime validation | Existing mapping + live tenant access | references/runtime-validation.md — load the security (AppSec) events supporting skill first (REQUIRED Step 0), then run the query pack, produce a Validation Summary table |
All workflows follow the output contracts in references/intake-and-constraints.md and the report templates in references/validation-policy-and-reporting.md. Validation rules (event-type coverage, required fields, scan references, namespace requirements, value/type checks, vendor-namespace duplication) live in references/validation-policy-and-reporting.md.
Acceptable Discrepancy Policy
See references/validation-policy-and-reporting.md for the canonical list of acceptable SD deviations and vendor-namespace patterns. Do NOT raise critical/major issues for fields on that list. Genuinely unknown fields (not in local refs AND not in the live SD — see references/semantic-reference.md) must be questioned per references/validation-policy-and-reporting.md.
Scope
This skill covers:
- Mapping suggestion and refinement (Workflow A).
- Static validation against local baseline examples and semantic dictionary (Workflow B1).
- Runtime validation via live tenant access against live tenant data (Workflow B2).
- Semantic-dictionary conformance checks.
- Gap analysis and improvement recommendations.
This skill does not cover:
- Live ingestion pipeline deployment.
- Runtime DQL performance benchmarking.
- Tenant-side ingestion troubleshooting.
References
references/semantic-reference.md— SD reference plus data-model notes: local sources, live (queryable) sources, DQL patterns, when-to-query decision matrix, authority rule, field taxonomy- A skill covering full SD access patterns and Grail-table documentation — for DQL query patterns against
security.eventsand Grail tables - Semantic Dictionary (public docs)
references/intake-and-constraints.md— intake checklist, output contract, OpenPipeline constraints, andobject.typenamespace expectationsreferences/mapping-workflow.md— how to build and refine a mapping candidatereferences/validation-policy-and-reporting.md— full validation rule set, known discrepancies, and discrepancy report templatesreferences/runtime-validation.md— optional real-environment query validation pack
FAQ
What does the dt-sec-semantic-mapping skill do?
Suggest and validate semantic dictionary (SD) mappings for new security integrations using vendor API samples or live events. Use when: mapping a new security vendor data to Dynatrace SD; checking required fields; validating namespaces; highlighting discrepancies vs the semantic dictionary; proposing mapping improvements; running runtime validation against live tenant data.
How do I install dt-sec-semantic-mapping?
Run npx skills add https://github.com/dynatrace/dynatrace-for-ai --skill dt-sec-semantic-mapping in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/dt-sec-semantic-mapping/ (personal) or .claude/skills/dt-sec-semantic-mapping/ (project).
Which AI agents can use dt-sec-semantic-mapping?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is dt-sec-semantic-mapping safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains dt-sec-semantic-mapping?
It is published by dynatrace in dynatrace/dynatrace-for-ai. It has 1,338 recorded installs.
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