---

name: plan-error-handling description: > Plan-only audit of silent failures and observability gaps (Sentry, Langfuse). Use when "errors aren't showing in Sentry", "things fail silently", or "empty catch blocks". Apply patterns → backend-error-handling. license: MIT effort: high

Error-Handling & Observability Audit + Fix Plan

Degree of freedom: HIGH — map silent paths, score, plan. Stay plan-only. No code or SDK edits until each phase is approved.

This skill vs neighbors

Skill	Owns
plan-error-handling (this)	Silent-failure + Sentry/Langfuse plan
debug-sentry-monitor	Live Sentry triage
audit-langfuse-llm	LLM eval / trace quality

How to reason (every plan item)

1. Propose — report, init, redact, or wrap a silent path
2. Risk — what fails in prod with no signal (or PII leaving the env)
3. Keep-working — surfaces that already capture and sanitize
4. Phase — swallows → coverage → redaction → LLM traces (do not execute)

Worked example

Propose: report + rethrow the empty catch on api/pay.ts charge; init Sentry on the edge surface. Risk: payment failures produce no event — you only hear from the user. Keep-working: web client already captures unhandled exceptions. Phase: Phase 1 — stop silent failures.

Role: Senior reliability engineer + observability specialist.

Task: Map every silent-failure path across Sentry and Langfuse planes, score by blast radius × invisibility, phase remediations, emit plan-error-handling.md. Audit & plan only — no code or SDK edits until each phase is approved.

Find what fails in silence. Make it observable. Change nothing until approved.

AI coding agents optimize for making the error message go away, not for making failure visible. Error-handling gaps are nearly twice as common in AI-generated pull requests as in human ones — empty catch blocks, missing guards, unhandled promise rejections, and handlers that leak stack traces into capture systems. The dangerous part isn't the crash you see; it's the failure you don't.

This skill is the audit-and-plan half. Execution goes to backend-observability / audit-langfuse-llm after you approve each phase.

---

When this fires

Trigger phrases: "errors don't reach Sentry", "it fails silently", "empty catch blocks", "add error handling", "why can't I debug prod", "check my Langfuse traces", "my LLM costs are a mystery", "pre-launch observability".

Do not fire for: a specific firing incident (debug-error, debug-sentry-monitor), or security gaps (plan-rls-audit, plan-security-audit). This is the coverage audit, not incident response.

---

Why a dedicated skill

plan-stub-checker finds fake functionality (dead buttons). This finds real functionality that fails invisibly. Different failure mode: "if this breaks in production tonight, would you ever know?"

---

Plane 1 · Application errors (Sentry) [HIGH freedom]

Walk every error path:

• Swallowing catches — catch (e) {}, catch { return null }, catch (e) { console.log(e) } with no rethrow and no Sentry capture.
• Unreported catches — handlers that log but never call Sentry.captureException. Local console ≠ production visibility.
• Missing guards — absent null checks, array-bounds validation, optional chaining gaps that throw at runtime on the unhappy path.
• Async holes — unhandled promise rejections, await without try/catch on fallible calls, floating promises, missing .catch() on fire-and-forget.
• PII / secret leakage into events — raw request bodies, tokens, emails, stack traces with internal paths captured into Sentry. Recommend beforeSend scrubbing.
• Coverage holes — is Sentry initialized on every surface (web, edge functions, RN/Capacitor, server actions)? Source maps uploaded?
• User-facing vs internal split — sanitized user message vs raw stack in UI?

Plane 2 · LLM observability (Langfuse) [HIGH freedom]

For any AI/LLM feature:

• Untraced calls — model/tool/retrieval calls with no @observe / Langfuse generation wrapping them.
• Missing cost & token capture — generations logged without usage/model params.
• No eval scores — faithfulness/relevance aren't on by default; you wire your own judges. Flag features shipping with zero quality signal.
• Prompts not version-linked — prompts inline in code instead of managed/ versioned and linked to traces.
• Sessions/users not propagated — multi-turn flows without session/user attributes.
• PII in traces — confirm SDK-layer redaction before traces leave the env.
• Sampling blind spots — if sampling <100%, note which edge cases may be missed.

If the user self-hosts Langfuse, add a note to re-check hosting and licensing terms against current upstream ownership before launch — a note, not a code finding.

Cross-plane

• Error ↔ trace correlation — can a Sentry error tie back to its Langfuse trace (shared request/trace id)?
• Structured logging — JSON + correlation ids vs console.log soup?

---

Procedure [HIGH freedom]

1. Inventory surfaces. Which planes exist (Sentry? Langfuse? both?). Skip absent planes. State assumptions.
2. Sweep. Collect findings with path:line. For each: "If this fails in prod, what's the signal?" — None / Console-only / Sentry / Langfuse.
3. Score. Severity = blast radius × invisibility.
4. Phase into shippable groups mapped to execution skills.
5. Emit plan-error-handling.md, then end the turn with a standalone recap in chat: the two or three highest-impact findings and the first phase to approve. The file is the deliverable — write it before the recap. Do not edit code.

---

Guardrails [LOW freedom — run exactly]

• Plan only. No wrapping, no try/catch insertion, no SDK config edits.
• Don't add noise. Flag genuinely-silent real failures; don't recommend Sentry-spamming every validation miss.
• Swallowing ≠ handling. Intentional graceful degradation is fine if reported; blind swallowing is not.
• Redaction is not optional. PII/secret reaching Sentry or Langfuse = High minimum.
• Observability ≠ prevention. Pair with plan-test-coverage.
• Minimal quoting of source.

Self-critique before the burndown [LOW freedom — do not skip]

1. evidenced-not-assumed — every row has path:line and today's signal
2. plan-only — no try/catch, wrap, or SDK edit this pass
3. phase justified — silent swallows before LLM evals; PII leak is High minimum
4. right-owner — live incident → debug-sentry-monitor; LLM quality → audit-langfuse-llm
5. no-false-safety — console.log ≠ Sentry; do not spam validation misses

---

Report template — plan-error-handling.md

# Error-Handling & Observability Audit — <repo>

_Audit-only. Nothing changes until each phase is approved._

## Scope
- Planes: [ ] Sentry  [ ] Langfuse  | Surfaces: web / edge / RN / server actions
- Assumptions / not inspected: …

## Verdict
| Plane | Silent failures | PII leaks | Coverage holes |
|-------|-----------------|-----------|----------------|
| Sentry   | n | n | n |
| Langfuse | n | n | n |

## Findings — application errors (Sentry)
| # | path:line | Pattern | Signal today | Sev | Direction |
|---|-----------|---------|--------------|-----|-----------|
| E1 | api/pay.ts:88 | empty catch on charge | none | Crit | report + rethrow, surface to user |

## Findings — LLM observability (Langfuse)
| # | path:line | Gap | Sev | Direction |
|---|-----------|-----|-----|-----------|
| L1 | lib/ai.ts:40 | model call untraced | High | wrap with observe, capture usage |

## Phased burndown
- **Phase 1 — Stop silent failures** → `backend-observability` — E-tier swallows
- **Phase 2 — Close coverage holes** → `backend-observability` — init gaps, maps
- **Phase 3 — Redact PII** → `backend-observability` — beforeSend / SDK redaction
- **Phase 4 — LLM tracing & evals** → `audit-langfuse-llm` — L-tier items

## Execution handoff
Approve a phase to run it. Re-run after to confirm failures are now observable.

---

Chains with

• Security spine — observability layer (plan-error-handling); complements plan-test-coverage (tests prevent; observability reveals).
• Execution: backend-observability, audit-langfuse-llm, debug-sentry-monitor.
• Verify: trigger a controlled failure post-fix; confirm Sentry/Langfuse capture.

Plan at high effort. Execute after approval at the default effort under approved-plan-execution.mdc (no reward hacking, no feature deletion). The plan says what is invisible; the rule constrains how it's wired.