design-system bugfixing.instructions.md

Bug-fixing instructions for the Iress Design System. They describe how to understand a support request, trace what happens in the code, confirm the diagnosis, and investigate the affected area before proposing a change.

In plain words
What is it for?
Use them to classify a report, identify affected interface elements or features, trace data from input to output, summarize the initial analysis, and prepare a visual reproduction.
Why use it?
They reduce the risk of fixing the wrong problem by separating the reported symptoms, expected behavior, technical flow, and scope of the issue.

Instructions file for GitHub Copilot

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 instructions/iress/design-system/bugfixing
Clone the repo
git clone --depth 1 https://github.com/iress/design-system

Made for: GitHub Copilot.

Per session 4,638 This file is loaded in full into every session.
When invoked 4,638 The same file — it is already loaded in full.
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 $0.04638 $0.04638
Opus 5 $0.02319 $0.02319
Sonnet 5 $0.00928 $0.00928
Haiku 4.5 $0.00464 $0.00464

Measured 2d ago against content hash d15750f53fca, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

design-system bugfixing.instructions.md 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 2d 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.

.github/instructions/bugfixing.instructions.md · 588 lines

How it starts

The opening of the file, as written. The whole thing — 588 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Bug Fixing Best Practices

1. Initial Analysis (Don't Jump to Solutions)

Parse the Support Request

  • Extract key symptoms: What exactly is broken? What's the expected vs actual behavior?
  • Identify affected components: Which UI elements, APIs, or features are involved?
  • Classify the issue: Bug, feature request, configuration issue, or user error?
  • Note reproduction context: Browser, environment, specific data, user actions

Understand the Technical Flow

  • Trace the data path: From input → processing → output where does it break?
  • Identify the domain: Styling, event handling, data transformation, rendering, etc.
  • Consider scope: Is this a single component issue or systemic problem?

Communicate Initial Analysis

Always summarize your initial understanding and ask for confirmation:

  • "Based on the bug report, I understand that [X problem] is happening when [Y scenario]. Is this correct?"
  • "I think this affects [components/areas]. Should I investigate these areas first?"
  • "This seems like a [bug type] issue. Does this match your expectations?"

Wait for confirmation before proceeding to investigation.

Create Story for Visual Inspection

After confirming the analysis, create a Storybook story to reproduce the bug:

  • Create the story in the main/root component's stories file (e.g., RichSelect.stories.tsx, not SelectMenu.stories.tsx)
  • This makes the bug reproduction more accessible and realistic for users
  • Include problem summary in the story description
  • Document expected vs actual behavior
  • Provide clear test steps
  • Make the bug visually apparent in the story
  • Use the actual component API that users would interact with
  • Create mock data that triggers the bug if needed

Template for bug reproduction story:

export const BugReproduction: Story = {
  name: 'Bug: [Brief Description]',
  args: {
    // Props that trigger the bug
  },
  parameters: {
    docs: {
      description: {
        story: `
**Problem Summary:** [What goes wrong]

**Expected Behavior:** [What should happen]

**Actual Behavior:** [What actually happens]

**How to Test:**
1. [Step by step instructions]
2. [To reproduce the issue]

        `,
      },
    },
  },
};

Read the full file on GitHub · 588 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. 2d ago First seen · 588 lines · 4,638 tokens per session scan A d15750f53fca

Subscribe to this mod's changes

design-system bugfixing.instructions.md is an instructions file published in the GitHub repository iress/design-system (1 stars, last pushed 6d ago), licensed Apache-2.0. It adds 4,638 tokens to every session, about $0.0232 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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