Kratos Development
aide-family/moon
Develops Go microservices with Kratos v2 following official design philosophy, DDD/Clean Architecture layout, Protobuf API, error/config/middleware patterns, and observability.
Distributed traces, spans, service dependencies, and request flow analysis.
$ npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-tracing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Dynatrace/dynatrace-for-ai dt-obs-tracing --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Dynatrace/dynatrace-for-ai.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/dt-obs-tracing .claude/skills/dt-obs-tracing && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "dt-obs-tracing" agent skill from https://github.com/Dynatrace/dynatrace-for-ai/tree/main/skills/dt-obs-tracing into .claude/skills/dt-obs-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dt-obs-tracing", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Dynatrace/dynatrace-for-ai/tree/main/skills/dt-obs-tracingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-tracing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Dynatrace/dynatrace-for-ai dt-obs-tracing --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Dynatrace/dynatrace-for-ai.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/dt-obs-tracing .agents/skills/dt-obs-tracing && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "dt-obs-tracing" agent skill from https://github.com/Dynatrace/dynatrace-for-ai/tree/main/skills/dt-obs-tracing into .agents/skills/dt-obs-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dt-obs-tracing", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-tracing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Dynatrace/dynatrace-for-ai dt-obs-tracing --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Dynatrace/dynatrace-for-ai.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/dt-obs-tracing .cursor/skills/dt-obs-tracing && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "dt-obs-tracing" agent skill from https://github.com/Dynatrace/dynatrace-for-ai/tree/main/skills/dt-obs-tracing into .cursor/skills/dt-obs-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dt-obs-tracing", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Dynatrace/dynatrace-for-ai.git --path skills/dt-obs-tracing--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-tracing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Dynatrace/dynatrace-for-ai dt-obs-tracing --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Dynatrace/dynatrace-for-ai.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/dt-obs-tracing .gemini/skills/dt-obs-tracing && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "dt-obs-tracing" agent skill from https://github.com/Dynatrace/dynatrace-for-ai/tree/main/skills/dt-obs-tracing into .gemini/skills/dt-obs-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dt-obs-tracing", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Dynatrace/dynatrace-for-ai dt-obs-tracingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-tracing -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Dynatrace/dynatrace-for-ai.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/dt-obs-tracing .github/skills/dt-obs-tracing && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "dt-obs-tracing" agent skill from https://github.com/Dynatrace/dynatrace-for-ai/tree/main/skills/dt-obs-tracing into .github/skills/dt-obs-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dt-obs-tracing", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-tracing -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Dynatrace/dynatrace-for-ai dt-obs-tracing --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Dynatrace/dynatrace-for-ai.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/dt-obs-tracing .opencode/skills/dt-obs-tracing && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "dt-obs-tracing" agent skill from https://github.com/Dynatrace/dynatrace-for-ai/tree/main/skills/dt-obs-tracing into .opencode/skills/dt-obs-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dt-obs-tracing", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
dt-obs-tracingDistributed traces, spans, service dependencies, and request flow analysis.
Dt Obs Tracing is an agent skill from Dynatrace/dynatrace-for-ai. Distributed traces, spans, service dependencies, and request flow analysis. Use when investigating span-level details, failures, performance bottlenecks, or trace correlation. Trigger: "trace analysis", "slow requests", "failed spans", "service dependencies", "distributed trace", "span details", "HTTP status codes in traces", "database query spans", "messaging spans", "gRPC calls", "Lambda cold starts", "trace ID lookup", "exception analysis", "correlate logs and traces", "request attributes". Do NOT use for…
Its SKILL.md is about 4.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including reference files (for example `references/database-spans.md`, `references/entity-lookups.md` and `references/failure-detection.md`).
It sits in Backend & APIs, covering gRPC and Protobuf, Technical writing and Observability. It works with gRPC. The repository describes itself as: Skills, prompts, and instructions for building AI agents on top of Dynatrace production context. The licence is Apache-2.0.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 4f9aa71. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are dql).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Dt Obs Tracing loads about 4.5k tokens when it runs, and up to ~17k if it reads all its reference files. Until then it costs about 183 tokens; SKILL.md has 1,197 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from Dynatrace/dynatrace-for-ai at commit 4f9aa71, republished under its Apache-2.0 licence (© Dynatrace). 1,197 words, ~4,479 tokens.
.claude/skills/dt-obs-tracing/SKILL.md (or your agent's skills folder). This skill also uses 12 other files; get the full folder from GitHub.Distributed traces in Dynatrace consist of spans - building blocks representing units of work. With Traces in Grail, every span is accessible via DQL with full-text searchability on all attributes. This skill covers trace fundamentals, common analysis patterns, and span-type specific queries.
Spans represent logical units of work in distributed traces:
Span kinds:
span.kind: server - Incoming call to a servicespan.kind: client - Outgoing call from a servicespan.kind: consumer - Incoming message consumption call to a servicespan.kind: producer - Outgoing message production call from a servicespan.kind: internal - Internal operation within a serviceRoot spans: A request root span (request.is_root_span == true) represents an incoming call to a service. Use this to analyze end-to-end request performance.
Essential attributes for trace analysis:
| Attribute | Description |
|---|---|
trace.id | Unique trace identifier |
span.id | Unique span identifier |
span.parent_id | Parent span ID (null for root spans) |
request.is_root_span | Boolean, true for request entry points |
request.is_failed | Boolean, true if request failed |
duration | Span duration in nanoseconds |
span.timing.cpu | Overall CPU time of the span (stable) |
span.timing.cpu_self | CPU time excluding child spans (stable) |
dt.smartscape.service | Service Smartscape node ID |
dt.service.name | Dynatrace service name derived from service detection rules. It is equal to the Smartscape service node name. |
endpoint.name | Endpoint/route name |
Spans reference services via Smartscape node IDs and the detected service name dt.service.name which is also present on every span.
fetch spans
| summarize spans=count(), by: { dt.smartscape.service, dt.service.name }Node functions:
getNodeName(dt.smartscape.service) - Adds dt.smartscape.service.name field with the human-readable service namegetNodeField(dt.smartscape.service, "attribute_name") - Access specific node attributes📖 Learn more: See Entity Lookups for advanced entity selectors, infrastructure correlation, and hardware analysis.
One span can represent multiple real operations due to:
aggregation.count)samplingRatio parameterWhen to extrapolate: Always extrapolate when counting actual operations (not just spans). Use the multiplicity factor:
fetch spans
| fieldsAdd sampling.probability = (power(2, 56) - coalesce(sampling.threshold, 0)) * power(2, -56)
| fieldsAdd sampling.multiplicity = 1 / sampling.probability
| fieldsAdd multiplicity = coalesce(sampling.multiplicity, 1)
* coalesce(aggregation.count, 1)
* dt.system.sampling_ratio
| summarize operation_count = sum(multiplicity)📖 Learn more: See Sampling and Extrapolation for detailed formulas and examples.
Fetch spans and explore by type:
fetch spans | limit 1Explore spans by function and type:
fetch spans
| summarize count(), by: { span.kind, code.namespace, code.function }List request root spans (incoming service calls):
fetch spans
| filter request.is_root_span == true
| fields trace.id, span.id, start_time, response_time = duration, endpoint.name
| limit 100Analyze service performance with error rates:
fetch spans
| filter request.is_root_span == true
| summarize
total_requests = count(),
failed_requests = countIf(request.is_failed == true),
avg_duration = avg(duration),
p95_duration = percentile(duration, 95),
by: {dt.service.name}
| fieldsAdd error_rate = (failed_requests * 100.0) / total_requests
| sort error_rate descFind all spans in a specific trace:
fetch spans
| filter trace.id == toUid("abc123def456")
| fields span.name, duration, dt.service.nameCalculate percentiles by endpoint:
fetch spans
| filter request.is_root_span == true
| summarize {
requests=count(),
avg_duration=avg(duration),
p95=percentile(duration, 95),
p99=percentile(duration, 99)
}, by: { endpoint.name }
| sort p99 desc💡 Best practice: Use percentiles (p95, p99) over averages for performance insights.
Find requests exceeding a threshold:
fetch spans, from:now() - 2h
| filter request.is_root_span == true
| filter duration > 5s
| fields trace.id, span.name, dt.service.name, duration
| sort duration desc
| limit 50fetch spans, from:now() - 24h
| filter http.route == "/api/v1/storage/findByISBN"
| summarize {
spans=count(),
trace=takeAny(record(start_time, trace.id))
}, by: { bin(duration, 10ms) }
| fields `bin(duration, 10ms)`, spans, trace.id=trace[trace.id], start_time=trace[start_time]Extract response time as timeseries:
fetch spans, from:now() - 24h
| filter request.is_root_span == true
| makeTimeseries {
requests=count(),
avg_duration=avg(duration),
p95=percentile(duration, 95),
p99=percentile(duration, 99)
}, by: { endpoint.name }📖 Learn more: See Performance Analysis for advanced patterns and timeseries techniques.
Summarize failures by service:
fetch spans
| filter request.is_root_span == true
| summarize
total = count(),
failed = countIf(request.is_failed == true),
by: { dt.service.name }
| fieldsAdd failure_rate = (failed * 100.0) / total
| sort failure_rate descBreakdown by failure detection reason:
fetch spans
| filter request.is_failed == true and isNotNull(dt.failure_detection.results)
| expand dt.failure_detection.results
| summarize count(), by: { dt.failure_detection.results[reason] }Failure reasons:
http_code - HTTP response code triggered failuregrpc_code - gRPC status code triggered failureexception - Exception caused failurespan_status - Span status indicated failurecustom_rule - Custom failure detection rule matchedFind failures by HTTP status code:
fetch spans
| filter request.is_failed == true
| filter iAny(dt.failure_detection.results[][reason] == "http_code")
| summarize count(), by: { http.response.status_code, endpoint.name }
| sort `count()` descList recent failures with details:
fetch spans
| filter request.is_root_span == true and request.is_failed == true
| fields
start_time,
trace.id,
endpoint.name,
http.response.status_code,
duration
| sort start_time desc
| limit 100📖 Learn more: See Failure Detection for exception analysis and custom rule investigation.
Analyze service communication patterns:
fetch spans, from:now() - 1h
| filter isNotNull(server.address)
| fieldsAdd
remote_side = server.address
| summarize
call_count = count(),
avg_duration = avg(duration),
by: {dt.service.name, remote_side}
| sort call_count descIdentify external API dependencies:
fetch spans
| filter span.kind == "client" and isNotNull(http.request.method)
| summarize
calls = count(),
avg_latency = avg(duration),
p99_latency = percentile(duration, 99),
by: { dt.service.name, server.address, server.port }
| sort calls descAggregate all spans in a trace to understand full request flow:
fetch spans, from:now() - 30m
| summarize {
spans = count(),
client_spans = countIf(span.kind == "client"),
// Endpoints involved in the trace
endpoints = toString(arrayRemoveNulls(collectDistinct(endpoint.name))),
// Extract the first request root in the trace
trace_root = takeMin(record(
root_detection_helper = coalesce(
if(request.is_root_span, 1),
if(isNull(span.parent_id), 2),
3),
start_time, endpoint.name, duration
))
}, by: { trace.id }
| fieldsFlatten trace_root
| fieldsRemove trace_root.root_detection_helper, trace_root
| fields
start_time = trace_root.start_time,
endpoint = trace_root.endpoint.name,
response_time = trace_root.duration,
spans,
client_spans,
endpoints,
trace.id
| sort start_time
| limit 100Root detection strategy: Use takeMin(record(...)) with a detection helper to reliably find the root request:
request.is_root_span == trueFind traces spanning multiple services:
fetch spans, from:now() - 1h
| summarize {
services = collectDistinct(dt.service.name),
trace_root = takeMin(record(root_detection_helper = coalesce(if(request.is_root_span, 1), 2), endpoint.name))
}, by: { trace.id }
| fieldsAdd service_count = arraySize(services)
| filter service_count > 1
| fields endpoint = trace_root[endpoint.name], service_count, services = toString(services), trace.id
| sort service_count desc
| limit 50Access custom request attributes captured by OneAgent on request root spans:
fetch spans
| filter request.is_root_span == true
| filter isNotNull(request_attribute.PaidAmount)
| makeTimeseries sum(request_attribute.PaidAmount)Field patterns: request_attribute.<name>, captured_attribute.<name> (always arrays)
→ Request Attributes — full patterns for request attributes, captured attributes, and request ID aggregation
| Span Type | Detection | Key Fields | Reference |
|---|---|---|---|
| HTTP server (incoming) | span.kind == "server" and isNotNull(http.request.method) | http.route, http.request.method, http.response.status_code | http-spans.md |
| HTTP client (outgoing) | span.kind == "client" and isNotNull(http.request.method) | server.address, server.port | http-spans.md |
| Database | span.kind == "client" and isNotNull(db.system) | db.system, db.namespace, db.statement | database-spans.md |
| Messaging | isNotNull(messaging.system) | messaging.system, messaging.destination.name, messaging.operation.type | messaging-spans.md |
| RPC / gRPC | isNotNull(rpc.system) | rpc.system, rpc.service, rpc.method, rpc.grpc.status_code | rpc-spans.md |
| Serverless / FaaS | isNotNull(faas.name) and span.kind == "server" | faas.name, faas.trigger.type, cloud.provider | serverless-spans.md |
⚠️ Database spans: Can be aggregated (one span = multiple calls). Always use aggregation.count extrapolation for accurate operation counts.
📖 Detailed patterns per span type: See the reference files above.
Exceptions are stored as span.events within spans:
fetch spans
| filter iAny(span.events[][span_event.name] == "exception")
| expand span.events
| fieldsFlatten span.events, fields: { exception.type }
| summarize {
count(),
trace=takeAny(record(start_time, trace.id))
}, by: { exception.type }
| fields exception.type, `count()`, trace.id=trace[trace.id], start_time=trace[start_time]💡 Tip: Use iAny() to check conditions within span event arrays.
→ Logs Correlation — joining logs and traces, filtering traces by log content → Network Analysis — client IPs, DNS resolution, subnet analysis
| Area | Rule |
|---|---|
| Filtering | Apply request.is_root_span == true and endpoint filters first |
| Sampling | Use samplingRatio (e.g., 100 = read 1%) for performance |
| Percentiles | Use p95/p99 over averages for performance analysis |
| Root spans | Use request.is_root_span == true for end-to-end analysis |
| Trace grouping | Group by trace.id for complete trace metrics |
| Request grouping | Group by request.id for OneAgent-only request metrics |
| Extrapolation | Always apply multiplicity for accurate operation counts |
| Exemplars | Use takeAny(record(start_time, trace.id)) to enable UI drilldown |
| Problem | Cause | Solution |
|---|---|---|
| Duration values seem wrong (too large) | duration is in nanoseconds, not milliseconds | Divide by 1000000 or compare with 5s (DQL duration literal) |
| Span counts don't match expected request volume | Sampling or aggregation not accounted for | Use multiplicity extrapolation — see Sampling and Extrapolation reference |
getNodeName(dt.smartscape.service) returns null | Service not yet resolved or OneAgent not monitoring | Verify OneAgent monitors the service; entity resolution may have a short delay |
request.is_root_span filter returns nothing | Querying OpenTelemetry-only traces without OneAgent | Use isNull(span.parent_id) as fallback for root span detection |
trace.id filter returns no results | Trace ID not converted to UID format | Use filter trace.id == toUid("abc123...") for string-based trace IDs |
| Database span counts are too low | Database spans are aggregated (one span = N calls) | Always use aggregation.count extrapolation for database operation counts |
Detailed documentation for specific topics:
© Dynatrace, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 12 other files (references) in skills/dt-obs-tracing of Dynatrace/dynatrace-for-ai.
Open the folder on GitHubat commit 4f9aa71
Dt Obs Tracing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Dt Obs Tracing this skillDynatrace/dynatrace-for-ai | 163 | — | ~4.5k | Automated safety check: Pass | Apache-2.0 | |
| Kratos Developmentaide-family/moon | 253 | — | ~1.5k | Automated safety check: Pass | None | |
| Use Yaakmountain-loop/yaak | 19k | — | ~1.9k | Automated safety check: Pass | MIT | |
| Backend Dev Guidelineslangfuse/langfuse | 36k | — | ~1.9k | Automated safety check: Pass | Custom licence | |
| Golang Proantoniopaya22/go-rest-template | 172 | 3 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Debug Grpc ConnectionGetBindu/Bindu | 10k | — | ~1.2k | Automated safety check: Pass | Custom licence |
aide-family/moon
Develops Go microservices with Kratos v2 following official design philosophy, DDD/Clean Architecture layout, Protobuf API, error/config/middleware patterns, and observability.
mountain-loop/yaak
A skill your agent uses when the user mentions Yaak, a Yaak workspace, or the yaak command, or asks to call, hit, or smoke test HTTP/REST endpoints, save or organize API requests for reuse or manual…
langfuse/langfuse
Build or review Langfuse backend code. An agent skill from langfuse/langfuse.
antoniopaya22/go-rest-template
Implements concurrent Go patterns using goroutines and channels, designs and builds microservices with gRPC or REST, optimizes Go application performance with pprof, and enforces idiomatic Go with…
GetBindu/Bindu
Diagnose gRPC connection issues between the Bindu core and a language SDK.
fanslead/ReverseProxy.Store
Build, review, refactor, or architect ASP.NET Core web applications using current official guidance for .NET web development.
Dynatrace/dynatrace-for-ai
Analyze dashboards and notebooks using Davis analyzers — anomaly detection, novelty scoring, and correlation.
Dynatrace/dynatrace-for-ai
Set up the Dynatrace iOS SDK (OneAgent) in an iOS project using Swift Package Manager.
Dynatrace/dynatrace-for-ai
End-to-end Dynatrace alerting lifecycle — anomaly detector setup and model selection (static threshold, adaptive baseline, seasonal baseline), alert event storage in Grail, problem grouping and…
Dynatrace/dynatrace-for-ai
AWS cloud resource monitoring including EC2, RDS, Lambda, ECS/EKS, VPC networking, load balancers, S3, DynamoDB, SQS/SNS, and cost optimization.
Dynatrace/dynatrace-for-ai
3rd-party test and monitor result ingestion into Dynatrace Grail via the platform events ingest API (platform/ingest/custom/events/).
Dynatrace/dynatrace-for-ai
DAVIS problem analysis including root cause identification, impact assessment, and correlation with other telemetry.
Works with
Categories
Distributed traces, spans, service dependencies, and request flow analysis. Dt Obs Tracing is an agent skill from Dynatrace/dynatrace-for-ai. Distributed traces, spans, service dependencies, and request flow analysis.
Dt Obs Tracing fits situations like: investigating span-level details; performance bottlenecks; trace correlation; explaining existing queries.
Run `npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-tracing -a claude-code`. Or copy the skill folder (skills/dt-obs-tracing in Dynatrace/dynatrace-for-ai) into .claude/skills/dt-obs-tracing in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-tracing -a codex`. Or copy the skill folder (skills/dt-obs-tracing in Dynatrace/dynatrace-for-ai) into .agents/skills/dt-obs-tracing in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-tracing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dt-obs-tracing, .gemini/skills/dt-obs-tracing, .github/skills/dt-obs-tracing and .opencode/skills/dt-obs-tracing in your project.
SKILL.md names no scripts, command-line tools or credentials: Dt Obs Tracing is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Dt Obs Tracing is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 4.5k tokens (SKILL.md is roughly 18k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 13k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Dt Obs Tracing: Kratos Development (aide-family/moon, 253 stars), Use Yaak (mountain-loop/yaak, 19k stars), Backend Dev Guidelines (langfuse/langfuse, 36k stars) and Golang Pro (antoniopaya22/go-rest-template, 172 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Dynatrace (a GitHub organization) maintains it in Dynatrace/dynatrace-for-ai, which has 163 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 1, 2026.
Source: Dynatrace/dynatrace-for-ai on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.