Conciseness

The body is lean: numbered mode steps, exact commands, env var names, and metric names with almost no explanation of concepts Claude already knows. The main trimmable redundancy is in the investigate mode, where each phase restates its bullet list as three near-duplicate example prompts — noticeable padding but not pervasive, matching the level-4 anchor rather than the fully lean level-5 anchor.

Actionability

Highly concrete guidance: exact commands ('helm upgrade --install datadog datadog/datadog -f values.yaml -n datadog', 'kubectl exec -n datadog ds/datadog -- agent status'), exact Terraform resource types ('datadog_monitor', 'datadog_service_level_objective'), exact env vars and API calls ('LLMObs.submit_evaluation()', 'span=LLMObs.export_span()'). Minor gaps keep it at 4: the generated artifacts are described but not shown — no values.yaml snippet, no Terraform resource example, no tracer-init code block.

Workflow Clarity

Clear mode dispatch with numbered steps, a 4-phase investigation workflow, verification commands in setup (step 4), and an explicit 'symptom → root cause hypothesis → evidence command → fix → validation' pattern in debug mode. Minor validation gaps — monitor/dashboard/slo modes lack a verify step (e.g., confirming the metric query returns data before creating the monitor, which is only hinted at in the debug bash comments) — placing it at 4 rather than the fully checkpointed level-5 anchor.

Progressive Disclosure

Good structure: mode sections are concise overviews, and detail is delegated one level deep with well-signaled, section-anchored pointers ('See `references/datadog.md` → MCP Server Setup', 'Reference: `references/llm-observability.md`'). However, neither referenced file exists in the bundle (references/ is absent), so the pointers cannot be verified as real navigation targets — a minor organization gap versus the level-5 anchor's easy, intact navigation.

Specificity

Lists multiple specific concrete capabilities — 'Agent deployment on Kubernetes, APM instrumentation, Log Management, Monitors, Dashboards, SLOs, Synthetic tests, and live incident investigation' — plus concrete tooling ('Datadog MCP server', 'Terraform-managed Datadog resources'). Comprehensive coverage of the Datadog domain matches the level-5 anchor; it is above level 4, which permits minor coverage gaps.

Completeness

The 'what' is explicit and clear, but there is no 'Use when...' clause or equivalent trigger guidance anywhere in the description — the 'when' is only weakly implied by the capability list. Per the rubric guideline, a missing explicit trigger clause caps completeness at 3; it is not a 4 because 'when' is entirely absent rather than merely imprecise.

Trigger Term Quality

Good natural-term coverage: 'set up', 'troubleshoot', 'APM', 'Monitors', 'Dashboards', 'SLOs', 'incident investigation', 'Kubernetes', 'Terraform'. A few common user phrasings are missing — 'logs/logging' (only the product name 'Log Management'), 'alerting', 'traces/tracing' — so it fits the level-4 anchor rather than the level-5 comprehensive-synonyms anchor.

Distinctiveness Conflict Risk

The description is anchored to the Datadog product name throughout with niche-specific triggers (MCP server, Terraform Datadog resources, SLOs), giving it a clear niche with minimal overlap risk against adjacent observability skills (Grafana, Prometheus). Matches the level-5 anchor.