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/usefulsoftwareco/executor/wrdn-effect-typed-errorsnpx skills add UsefulSoftwareCo/executor --skill wrdn-effect-typed-errorsgit clone --depth 1 https://github.com/UsefulSoftwareCo/executorWhat 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 | $0.00062 | $0.02716 |
| Opus 5 | $0.00031 | $0.01358 |
| Sonnet 5 | $0.00012 | $0.00543 |
| Haiku 4.5 | $0.00006 | $0.00272 |
Grade A, and why
wrdn-effect-typed-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 yesterday.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- wrdn-effect-typed-errors — 100% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 360 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You fix one family of patterns: untyped JavaScript error handling in Effect code.
The preferred boundary is typed Schema.TaggedError / Data.TaggedError values in the Effect error channel. Construct the tagged error directly at the failure site unless a helper performs real classification or normalization.
Trace before changing
- Identify the boundary. Is this Effect domain code, React UI code, a third-party callback, or plain test/tooling code?
- Find the existing domain errors. Check nearby
errors.ts,Schema.TaggedError,Data.TaggedError, and API.addError(...)declarations before adding a new class. - Decide whether a new error is needed. Add a new tagged error only if callers have a distinct recovery path, HTTP status, UI affordance, retry policy, or telemetry classification.
- Preserve failure semantics. If the old code failed, the new code should fail in the Effect error channel. Do not replace thrown failures with fallback values like
false,null,undefined,[], or"unknown"unless the existing contract already treats that condition as non-fatal. - Preserve the typed channel. Do not convert typed failures into
Error, thrown exceptions,String(error), or.messagereads from unknown values. - Recognize real boundaries. Runtime workers, Vite/CLI tooling, callback APIs, and third-party interfaces may have to throw, catch, or reject at the boundary. Do not contort those files into fake Effect shapes. Keep the boundary idiom when it is contained and immediately wrapped into an Effect error channel, stable IPC envelope, or test/tooling result.
- Do not hide construction behind trivial helpers. Inline
new DomainError(...)unless the helper branches on input or maps an external error format into a domain error.
Preserve behavior first
The lint rule is about where the failure lives, not whether the operation should still fail.
Bad fix: this removes the lint finding by silently changing invalid input into a non-match.
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.
- yesterday First seen · 360 lines · 62 tokens per session scan A 16631077797c
wrdn-effect-typed-errors is a skill published in the GitHub repository UsefulSoftwareCo/executor (3,466 stars, last pushed yesterday), licensed MIT. It adds 62 tokens to every session and 2,716 once invoked, about $0.0003 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…