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 skills add khasky/awesome-agent-skills --skill awesome-error-standardsgit clone --depth 1 https://github.com/khasky/awesome-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/khasky/awesome-agent-skills/awesome-error-standards)<a href="https://agentmods.dev/skills/khasky/awesome-agent-skills/awesome-error-standards"><img src="https://agentmods.dev/badge/skills/khasky/awesome-agent-skills/awesome-error-standards/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/khasky/awesome-agent-skills/awesome-error-standards"><img src="https://agentmods.dev/badge/skills/khasky/awesome-agent-skills/awesome-error-standards.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00080 | $0.02272 |
| Opus 5 | $0.00040 | $0.01136 |
| Sonnet 5 | $0.00016 | $0.00454 |
| Haiku 4.5 | $0.00008 | $0.00227 |
Grade A, and why
awesome-error-standards 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 4d 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Error Handling Patterns
Apply consistent patterns for throwing, catching, logging, and surfacing errors so failures are predictable and debuggable without leaking internals.
When to Activate
- Implementing or refactoring error handling in an API or app
- User asks for "error handling", "how to handle errors", or "consistent errors"
- Reviewing code for proper failure handling
- Defining or documenting error contract for a service or API
Core Principles
- Operational vs programmer errors — Classify first. Operational failures (network timeout, invalid input, missing record) are expected: handle, retry, or surface them. Programmer errors (undefined access, broken invariant) are bugs: crash loudly or restart the process rather than limping on with corrupted state.
- Make the bug impossible, not just fixed — A single-point fix stops one path; defense in depth stops the class. Prefer prevention left of production, in order: (1) make invalid states unrepresentable in the type system (discriminated unions, branded/opaque types) so bad states won't compile; (2) validate at the boundary; (3) runtime guards; (4) error boundaries. For a high-value invariant, guard it at more than one layer and test that bypassing an outer layer still gets caught by an inner one (deliberately skip Layer 1, verify Layer 2 catches it; confirm mocks don't silently disable a validation).
- Fail at startup, not in production — Validate all required config, env vars, and connections at init and refuse to boot on failure, rather than discovering a missing value on the first request.
- Fail fast — Validate inputs and preconditions early; throw or return errors with clear messages. Do not continue with invalid state.
- Do not swallow — Avoid empty catch or broad catch that ignores; log and/or rethrow or return a result type. Propagate with context.
- Structured errors — Use a consistent shape (e.g. code, message, details) for API errors and for logs. Typed error classes or codes help callers handle by type.
- User vs developer — User-facing messages are safe and actionable; developer-facing detail (stack, internal message, request id) in logs or debug only. Never expose stack traces or SQL to end users.
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.
- 4d ago Changed · -17 tokens per session f8a8b14cb001
- 10d ago First seen · 131 lines · 97 tokens per session scan A 7ace95a0ed8b
awesome-error-standards is a skill published in the GitHub repository khasky/awesome-agent-skills (8 stars, last pushed 2d ago), licensed MIT. It adds 80 tokens to every session and 2,272 once invoked, about $0.0004 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 2026-08-31.
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