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observability

Establish observability for research systems, experiments, and data pipelines with guardrails and confidence ceilings.

allowed_tools: Read, Write, Edit, Bash, Glob, Grep, Task, TodoWrite
model: sonnet

$ Installieren

git clone https://github.com/DNYoussef/context-cascade /tmp/context-cascade && cp -r /tmp/context-cascade/skills/research/observability ~/.claude/skills/context-cascade

// tip: Run this command in your terminal to install the skill


name: observability description: Establish observability for research systems, experiments, and data pipelines with guardrails and confidence ceilings. allowed-tools: Read, Write, Edit, Bash, Glob, Grep, Task, TodoWrite model: sonnet x-version: 3.2.0 x-category: research x-vcl-compliance: v3.1.1 x-cognitive-frames:

  • HON
  • MOR
  • COM
  • CLS
  • EVD
  • ASP
  • SPC

STANDARD OPERATING PROCEDURE

Purpose

  • Instrument research workflows (experiments, data pipelines, services) for visibility, debugging, and reproducibility.
  • Capture constraints and SLIs/SLOs explicitly; prevent silent failures.
  • Maintain structure-first artifacts and clear confidence ceilings for observations.

Trigger Conditions

  • Positive: need for telemetry on experiments, metrics tracking, drift detection, or reproducibility dashboards.
  • Negative: pure analysis without systems impact (use general-research-workflow), or production SRE (route to operations skills).

Guardrails

  • Constraint buckets include privacy/compliance, performance budgets, cardinality limits, and ownership.
  • Two-pass refinement: instrumentation plan → validation against constraints and data quality.
  • Evidence-first reporting: observations use observation ceiling (0.95); inferred impacts use inference ceiling (0.70).

Inputs

  • System or experiment topology; key questions to answer.
  • Metrics/SLIs, alert thresholds, and data retention policies.
  • Tooling constraints (OpenTelemetry, logging stack, dashboards).

Workflow

  1. Scope & Constraints: Define observability goals, HARD/SOFT/INFERRED constraints, and stakeholders.
  2. Instrumentation Plan: Select signals (logs, metrics, traces), sampling, and tagging strategy; align with budgets.
  3. Implement & Validate: Configure exporters/collectors, run smoke tests, and verify data quality.
  4. Dashboard & Alerts: Build views for key workflows; set alert thresholds and runbooks.
  5. Review & Iterate: Check coverage against goals, refine noisy signals, and document ownership/storage.

Validation & Quality Gates

  • Signals mapped to questions and SLIs; sampling and retention documented.
  • Privacy/compliance constraints respected.
  • Alert/runbook coverage verified; noise level acceptable.
  • Confidence ceilings stated for observations vs. inferences.

Response Template

**Scope & Constraints**
- HARD / SOFT / INFERRED.

**Signals & Plan**
- Metrics/logs/traces + tagging.

**Validation**
- Smoke tests, data quality, alert checks.

**Coverage & Gaps**
- ...

Confidence: 0.84 (ceiling: observation 0.95) - based on validated signals and dashboards.

Confidence: 0.84 (ceiling: observation 0.95) - reflects verified telemetry and quality gates.