Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/developersglobal/ai-agent-skills/error-handlingnpx skills add DevelopersGlobal/ai-agent-skills --skill error-handlinggit clone --depth 1 https://github.com/DevelopersGlobal/ai-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/developersglobal/ai-agent-skills/error-handling)<a href="https://agentmods.dev/skills/developersglobal/ai-agent-skills/error-handling"><img src="https://agentmods.dev/badge/skills/developersglobal/ai-agent-skills/error-handling.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00032 | $0.00851 |
| Opus 5 | $0.00016 | $0.00426 |
| Sonnet 5 | $0.00006 | $0.00170 |
| Haiku 4.5 | $0.00003 | $0.00085 |
Grade A, and why
error-handling scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
Error handling is not defensive programming — it's a user experience. When things go wrong (and they will), the system should degrade gracefully, give users actionable information, and leave enough telemetry to diagnose and fix the problem.
When to Use
- When writing any code that can fail (I/O, network, parsing, user input)
- When reviewing error handling in existing code
- Before any service goes to production
Process
Step 1: Design Error Paths Explicitly
- For every operation, list: what can fail? What does failure look like?
- Classify failures:
- Transient: Retry likely to succeed (network blip, temporary unavailability)
- Client error: Bad input from the caller (4xx) — don't retry
- System error: Internal failure (5xx) — alert, investigate
- Design the failure path for each class before writing the happy path.
Verify: Error classes defined for every external operation.
Step 2: Meaningful Error Messages
- Every error message answers: what went wrong? How can the caller fix it?
- ✅ "Invalid email format. Expected: [email protected]"
- ❌ "Validation error"
- User-facing errors: friendly language, no stack traces.
- Developer-facing errors (logs): full context, request ID, stack trace.
- Never expose internal system details (DB schema, file paths) in user-facing errors.
Verify: Each error message would help a user or developer understand and fix the problem.
Step 3: Retry with Backoff
- Transient errors: retry with exponential backoff + jitter.
- Maximum retries: 3 (not infinite).
- After max retries: fail with a clear error, log the final failure.
- Non-transient errors (validation, auth): never retry.
Verify: Retry logic has a maximum. Non-transient errors don't retry.
Step 4: Graceful Degradation
- Identify non-critical dependencies. If they fail, degrade — don't crash.
- Example: recommendation engine fails → show default content, not 500.
- Circuit breaker pattern for failing dependencies: fail fast after threshold, recover automatically.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 95 lines · 32 tokens per session scan A 3f3042d3ed86
error-handling is a skill published in the GitHub repository DevelopersGlobal/ai-agent-skills (65 stars, last pushed 4mo ago), licensed MIT. It adds 32 tokens to every session and 851 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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