loud-errors

loud-errors is a skill for Claude Code, Codex from mikestangdevs/craft-skills. It costs 138 tokens per session (1,815 once invoked), scanned A, original, MIT.

A guide for handling errors so they stop the wrong work and include enough context to diagnose the cause. It targets swallowed exceptions, ignored logs, and vague messages such as “something went wrong.”

In plain words
What is it for?
Use it when reviewing empty catch blocks, ignored exceptions, generic error messages, or code that continues after an operation has failed.
Why use it?
It prevents failures from being hidden and later appearing as unrelated corruption. Specific errors make debugging and incident response easier.

Skill for Claude CodeCodex

Part of the craft-skills plugin — 17 skills shipped together

Install

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.

agentmods
npx agentmods add skills/mikestangdevs/craft-skills/loud-errors
Any agent
npx skills add mikestangdevs/craft-skills --skill loud-errors
Clone the repo
git clone --depth 1 https://github.com/mikestangdevs/craft-skills

Made for: Claude Code, Codex.

Or install craft-skills, the plugin that ships this one along with the rest of its 17 skills.

Wrote 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.

agentmods badge for loud-errors

README.md
[![agentmods](https://agentmods.dev/badge/skills/mikestangdevs/craft-skills/loud-errors.svg)](https://agentmods.dev/skills/mikestangdevs/craft-skills/loud-errors)
Your own site
<a href="https://agentmods.dev/skills/mikestangdevs/craft-skills/loud-errors"><img src="https://agentmods.dev/badge/skills/mikestangdevs/craft-skills/loud-errors.svg" alt="Measured on agentmods" height="20"></a>
Per session 138 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,815 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00138 $0.01815
Opus 5 $0.00069 $0.00907
Sonnet 5 $0.00028 $0.00363
Haiku 4.5 $0.00014 $0.00181

Measured 4d ago against content hash 8832e7d455e1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

loud-errors 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.

skills/craft/loud-errors/SKILL.md · 107 lines

How it starts

The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Loud Errors

The failure mode this fixes

The worst error is the one you can't see. Code that swallows failures — catch {}, except: pass, an error logged at debug and then execution continues as if nothing happened — turns a clean crash into a silent corruption that surfaces hours later, somewhere else, with no trace back to the cause. The second-worst is the error that is loud but says nothing: throw new Error("something went wrong") tells the on-call engineer at 3am exactly nothing.

Agents are especially prone to both. They're optimizing for "make the happy path run," so they wrap risky calls in a try that quietly eats the failure, or they emit a generic message to satisfy a linter. The result is code that looks defensive and is actually blind.

This skill does the opposite of defensive-by-swallowing: it makes failures loud (they stop the wrong thing from continuing) and specific (they carry enough context to diagnose without a debugger).

When to Use This Skill

  • You see an empty or near-empty catch: catch (e) {}, except: pass, catch { return null }, rescue nil
  • An error is logged and then execution continues as if it succeeded
  • A thrown/raised error is generic: "something went wrong", "error", "failed", a bare re-throw with no context
  • A caught exception is replaced by a new one that drops the original cause
  • You're reviewing AI-generated code and want to find where failures will be invisible
  • A real incident left no useful trace and you're hunting for where the signal got eaten

Don't use when: the swallow is deliberate and correct — a genuinely optional operation (best-effort cache warm, telemetry that must never break the request), a documented retry/fallback, or a control-flow exception in a language that uses them idiomatically. In those cases the rule is not "make it loud," it's "make the intent to swallow explicit" (see step 4). Don't turn an intentional fallback into a crash.

Instructions

1. Find where failures disappear

Read the full file on GitHub · 107 lines

Changes

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.

  1. 4d ago First seen · 107 lines · 138 tokens per session scan A 8832e7d455e1

Subscribe to this mod's changes

loud-errors is a skill published in the GitHub repository mikestangdevs/craft-skills (4 stars, last pushed 2mo ago), licensed MIT. It adds 138 tokens to every session and 1,815 once invoked, about $0.0007 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.

Related

Other skills, from other repositories

code-consolidation

This skill should be used when the user asks to "find duplicated code", "map responsibilities", "consolidate code", "find code sprawl", "analyze duplication", "create consolidation plan", or mentions "código duplicado", "responsabilidades espalhadas", "consolidar". Analyzes codebases to identify scattered…

parisgroup-ai/imersao-ia-setup · 79 tokens

new-skill

Scaffold a new brooks-lint analysis skill so it passes npm run validate and npm run evals on the first try — generates skills/{name}/SKILL.md (with the mandatory "Do NOT trigger for:" clause and a Process section citing guide step ranges) plus skills/{name}/{name}-guide.md (sequentially numbered steps), then appends…

hyhmrright/brooks-lint · 145 tokens

brooks-sweep

Full-sweep mode: runs a unified analysis across all quality dimensions — code decay, architecture, tech debt, and test quality — then applies fixes directly to the codebase. Safe changes are auto-applied; risky changes are confirmed before execution. Drawing on twelve classic engineering books. Triggers when: user…

hyhmrright/brooks-lint · 178 tokens

brooks-test

Test quality review drawing on twelve classic engineering books — with primary focus on xUnit Test Patterns, The Art of Unit Testing, How Google Tests Software, and Working Effectively with Legacy Code — that diagnoses structural problems in an existing test suite: brittleness, mock abuse, coverage illusions, slow…

hyhmrright/brooks-lint · 161 tokens

status

Where is the work right now. Regenerates the projections and the kanban board from the journal and answers with the progress line, the agents still running, the open gates and the resume steps. Read-only. Use for /tyran:status or when asked what is going on.

jjanczur/tyran · 58 tokens

prompt-tuning

Tune a prompt, or anything whose quality is measured by non-deterministic model output, without chasing noise - a noise baseline before the first edit, medians over repeated runs, enforcement AFTER generation rather than in the wording. Use when iterating on prompts or model-judged output.

jjanczur/tyran · 58 tokens