deliver-edge-cases

deliver-edge-cases is a skill for Claude Code, Codex from yuusakuri/agent-skills. It costs 98 tokens per session (903 once invoked), scanned A, a copy of deliver-edge-cases, MIT.

A catalogue of unusual situations, limits, errors, timing conflicts, and recovery paths that a feature must handle. It covers what can go wrong beyond the normal user flow.

In plain words
What is it for?
Use it during feature specification, quality assurance planning, production bug reviews, or pre-launch checks.
Why use it?
It helps teams find failure scenarios before users encounter them in production. It also gives engineers and testers a fuller view of what needs to be designed and checked.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it during feature specification, quality assurance planning, production bug reviews, or pre-launch checks.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yuusakuri/agent-skills/deliver-edge-cases
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.

Any agent
npx skills add yuusakuri/agent-skills --skill deliver-edge-cases
Clone the repo
git clone --depth 1 https://github.com/yuusakuri/agent-skills

Made for: Claude Code, Codex.

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 deliver-edge-cases

README.md
[![agentmods](https://agentmods.dev/badge/skills/yuusakuri/agent-skills/deliver-edge-cases/github.svg)](https://agentmods.dev/skills/yuusakuri/agent-skills/deliver-edge-cases)
Your own site
<a href="https://agentmods.dev/skills/yuusakuri/agent-skills/deliver-edge-cases"><img src="https://agentmods.dev/badge/skills/yuusakuri/agent-skills/deliver-edge-cases/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.

agentmods 80×15 button for deliver-edge-cases

Your own site · 80×15
<a href="https://agentmods.dev/skills/yuusakuri/agent-skills/deliver-edge-cases"><img src="https://agentmods.dev/badge/skills/yuusakuri/agent-skills/deliver-edge-cases.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 98 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 903 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 95% copy Near-identical to another mod 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 5.1 $0.00098 $0.00903
Opus 5 $0.00049 $0.00451
Sonnet 5 $0.00020 $0.00181
Haiku 4.5 $0.00010 $0.00090

Measured 11d ago against content hash 486c5e768a66, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

deliver-edge-cases 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 11d 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.

Origin

This is a copy

95% identical to deliver-edge-cases — 14 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/deliver-edge-cases/SKILL.md · 77 lines

How it starts

The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Edge Cases

An edge cases document systematically catalogs the unusual, boundary, and error scenarios for a feature. While happy-path flows are typically well-specified, edge cases often get discovered in production - causing bugs, poor user experience, and support burden. Documenting edge cases upfront ensures engineering handles them intentionally and QA knows what to test.

When to Use

  • When you need to enumerate failure modes, race conditions, timeouts, and boundary or limit scenarios - everything that can go wrong - and define a recovery path for each
  • During feature specification before engineering begins
  • When preparing QA test plans
  • After discovering production bugs to prevent similar issues
  • When reviewing PRDs or user stories for completeness
  • Before launch to ensure error states have been designed

When NOT to Use

  • You need story-scoped Given/When/Then checks for handoff -> use deliver-acceptance-criteria; this skill catalogs the whole feature's failure surface
  • The feature is not specified enough to enumerate inputs, states, and limits -> use deliver-prd first
  • A production incident already happened and you want the learning banked -> use retro, then update this catalog with the new case
  • You need readiness coordination for a launch, not failure analysis -> use shipping-and-launch

Instructions

When asked to document edge cases, follow these steps:

  1. Define the Feature Scope Clearly describe what feature or flow you're analyzing. Edge cases are specific to context - the same input might be valid in one feature and invalid in another.

  2. Walk Through Input Validation Consider every user input: What if it's empty? Too long? Wrong format? Contains special characters? What are the minimum and maximum valid values?

  3. Explore Boundary Conditions Find the edges of acceptable ranges. If a field accepts 1-100, test 0, 1, 100, and 101. Consider pagination boundaries, timeout thresholds, and rate limits.

Read the full file on GitHub · 77 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 11d ago First seen · 77 lines · 98 tokens per session scan A 486c5e768a66

Subscribe to this mod's changes

deliver-edge-cases is a skill published in the GitHub repository yuusakuri/agent-skills (2 stars, last pushed 4d ago), licensed MIT. It adds 98 tokens to every session and 903 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to deliver-edge-cases, differing in 14 lines, and is treated as a copy.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

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…

vercel/next.js · 95 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens

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…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens