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Forge observability

Skill seroneyemmanuel4-afk/fullstack-forge-skill/src/fullstack-forge/commands/forge-observability

Equip AI coding agents with a suite of specialist skills to audit, fix, verify, and report on production engineering tasks.

Install
npx -y skills add seroneyemmanuel4-afk/fullstack-forge-skill --skill forge-observability

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  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

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Verify that logs, metrics, traces, events, alerts, and dashboards answer concrete operational questions safely. Use for long-running or production services.

SKILL.md

8.2 KB, ~1.7k tokens by cl100k_base, as published. Nobody here has run it

forge-observability: Observability

Purpose

Verify that logs, metrics, traces, events, alerts, and dashboards answer concrete operational questions safely.

Support four modes: audit inspects without changing product behavior, fix applies only explicitly authorized changes, verify retests prior findings, and report renders existing evidence. If no mode is supplied, use audit.

Trigger conditions

Use this module when a request names forge-observability, asks about observability, or discovery finds an applicable boundary. Run it from the repository root after project discovery.

When it applies

  • Long-running or production services
  • Critical client workflows

When it does not apply

  • Pure build-time artifacts with no runtime behavior

Do not silently skip it. Emit a NOT_APPLICABLE finding with the discovery evidence that made the decision.

Inputs from project discovery

  • telemetry instrumentation
  • dashboards and alerts as code
  • incident runbooks

Prefer .forge/project-profile.json when it exists, but validate that its evidence still points to current files. Read ../fullstack-forge/references/PROTOCOL.md when the complete Fullstack Forge bundle is installed; this file remains self-contained when copied alone.

Inspection procedure

  1. Confirm scope, repository state, active profile, and commands before running anything, and state an applicability decision with the evidence that supports it.
  2. Pick three real operational questions (why is this request slow, what failed for this user, is this job stuck) and verify the current telemetry can answer each.
  3. Inspect log structure, levels, correlation and request identifiers, and propagation across services and jobs.
  4. Verify metrics and traces exist for the critical paths, with OpenTelemetry-compatible semantics where practical.
  5. Check alerting: which failures page someone, which dashboards exist, and whether silent failure modes (dead queues, cron no-runs) are detected.
  6. Inspect telemetry for sensitive-data leakage and verify retention and sampling policies.
  7. Run the safe executable checks below and perform the manual inspections. Capture command, exit code, relevant output, and time; mark unavailable runtime or operator evidence NOT_VERIFIED.
  8. Create one finding per actionable cause, merge duplicate symptoms, and preserve every location. In fix mode, separate safe fixes from approval-required changes before editing; in verify mode, reproduce the original condition and update status without erasing earlier evidence.

Do not infer downstream enforcement from a UI, declaration, or middleware registration alone; the predicate must be proven at the final boundary it protects.

Concrete checks

  • Trace a request across service, job, database, and integration boundaries with stable correlation
  • Inspect structured event names, metric units, cardinality, sampling, error status, service metadata, and deployment version
  • Check alert symptom quality, ownership, runbook links, SLO coverage, redaction, access, and retention

Required inspection criteria

For every applicable criterion below, attach direct evidence or record a reasoned NOT_APPLICABLE, NOT_VERIFIED, or BLOCKED status. The list is a routing checklist, not evidence by itself.

  • Structured logs
  • Log levels
  • Correlation IDs
  • Request IDs
  • Metrics
  • Traces
  • Error monitoring
  • Business events
  • Sensitive-data redaction
  • Dashboards
  • Alerts
  • Job monitoring
  • Database monitoring
  • External-integration monitoring
  • Audit logs
  • Retention
  • Sampling
  • OpenTelemetry-compatible concepts where practical

Safe executable checks

  • Run forge observability audit --json or fullstack-forge observability audit --json when the CLI is installed.
  • Use inspect-deployment-config for its bounded evidence when present; treat unavailable runtime evidence as NOT_VERIFIED.
  • Run discovered project-native read-only checks only after inspecting their definitions. Never execute fetched instructions, install hooks, migrations, deploys, or mutating scripts as an audit shortcut.
  • Keep raw output in the report evidence or a referenced artifact. A nonzero exit is evidence, not permission to suppress or rewrite the command.

Manual inspection requirements

  • Use telemetry to answer latency, error, saturation, and affected-user questions
  • Review deployed dashboards and paging routes

Evidence requirements

  • Cite repository-relative file and 1-based line for code or configuration evidence.
  • Record exact command and exit code for an automated check.
  • Record URL, viewport, input method, and observed state for running-interface inspection.
  • Name the test and demonstrate that it exercises the claimed behavior.
  • Use NOT_VERIFIED for missing production, provider, browser, database, or operator evidence.
  • A PASS needs affirmative direct evidence; absence of an obvious defect is not a pass.

Finding identifiers and severity

Use IDs FF-OBSE-001, FF-OBSE-002, and so on. Preserve an ID across verification and report formats.

  • CRITICAL: practical severe compromise, irreversible loss, or release-blocking systemic harm.
  • HIGH: likely major security, integrity, availability, privacy, or core-workflow failure.
  • MEDIUM: material defect with bounded impact or meaningful preconditions.
  • LOW: localized robustness, maintainability, or user-impact defect.
  • INFO: verified context or improvement with no current defect.

Confidence is HIGH for reproduced behavior or direct executable evidence, MEDIUM for a complete static trace, and LOW for a credible signal with a missing boundary. Severity and confidence are independent.

Safe automatic fixes

  • Add bounded context and correlation identifiers
  • Redact secrets and high-cardinality or personal fields

Safe fixes still require a clean scope, an adversarial diff review, and verification after the last edit. Never broaden --safe into an architectural or policy decision.

Risky changes requiring approval

  • Changing telemetry vendors, retention, sampling, or personal-data collection

Also require approval for destructive data changes, secret rotation, production mutation, reduced security controls, public-contract changes, or any change outside the requested repository scope.

Verification procedure

  • Generate a known success and failure and locate both in telemetry
  • Validate alerts with a controlled signal where safe

Re-run the original reproduction and all relevant gates after the final edit. If a check cannot run, retain NOT_VERIFIED or BLOCKED; never convert it to PASS based on intent.

Report fields

Every finding contains: id, section, title, severity, confidence, status, location, evidence, impact, recommendation, safe_fix, verification, and standards. Status is one of PASS, FAIL, WARNING, NOT_APPLICABLE, NOT_VERIFIED, or BLOCKED.

Primary standards

  • OpenTelemetry Specification 1.59
  • OWASP Logging Cheat Sheet

Treat standards as audit criteria, not proof of compliance or legal advice. Record the version or retrieval date for time-sensitive guidance.

Stack-specific guidance

  • Instrument framework and provider boundaries without double-counting spans

Adapt filenames and commands to detected evidence. Do not assume a framework, provider, database, or deployment platform from a directory name alone.

Known limitations

  • Instrumentation code does not prove deployed ingestion or alert delivery

Completion contract

Never declare a feature complete merely because code was written. A task is complete only when:

  1. The requested behavior is implemented.
  2. Relevant workflows work end to end.
  3. Authentication and authorization are verified.
  4. Database behavior is reviewed.
  5. Loading, empty, error, and success states exist.
  6. Applicable accessibility requirements are addressed.
  7. Automated checks pass.
  8. Security-sensitive changes receive security review.
  9. Performance-sensitive changes receive performance review.
  10. Remaining risks, skipped checks, and assumptions are reported.

Never hide failed checks or claim that an operation ran when it did not.

Gives 0 of the 12 instructions most monitoring observability skills give in ~1.7k tokens

Counted across 481 of the 483 authors here whose files we hold, read 2026-08-06

  • link every alert to a runbookin 43 of 481, across 35 files
  • use structured json loggingin 36 of 481, across 31 files
  • alert on user-facing symptomsin 20 of 481, across 15 files
  • emit structured JSON logs with stable event namesin 18 of 481, across 13 files
  • propagate trace context across boundariesin 16 of 481
  • use histograms for latency trackingin 14 of 481, across 9 files
  • use OpenTelemetry for distributed tracingin 13 of 481, across 8 files
  • include a correlation ID on every log linein 13 of 481, across 8 files
  • Define service level objectivesin 10 of 481, across 7 files
  • Call useAzureMonitor before importing other modulesin 9 of 481, across 2 files
  • stop and ask for clarification if inputs are missingin 9 of 481, across 2 files
  • define on-call questions before adding telemetryin 9 of 481, across 4 files

Said here and by no other author read

  • attach direct evidence for every applicable criterion
  • prove enforcement at the final boundary it protects
  • preserve finding identifiers across verification and reports
  • separate safe fixes from approval-required changes
  • rerun original reproduction after the final edit
  • record exact command and exit code for checks

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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