bug-report

bug-report is a skill for Claude Code, Codex from nntan90/qa-skill-suite. It costs 119 tokens per session (3,474 once invoked), scanned A, original, MIT.

A guide for recording software defects in a clear, repeatable format. A defect is a case where the software behaves differently from what was expected.

In plain words
What is it for?
Use it to write tickets for Jira, GitHub Issues, or Linear with reproduction steps, expected and actual results, environment details, evidence, and severity.
Why use it?
It prevents bug reports from missing the details needed to reproduce and fix a problem. It also helps teams describe severity and priority consistently.

Skill for Claude CodeCodex

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

Good fit Use it to write tickets for Jira, GitHub Issues, or Linear with reproduction steps, expected and actual results, environment details, evidence, and severity.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nntan90/qa-skill-suite/bug-report
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 nntan90/qa-skill-suite --skill bug-report
Clone the repo
git clone --depth 1 https://github.com/nntan90/qa-skill-suite

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 bug-report

README.md
[![agentmods](https://agentmods.dev/badge/skills/nntan90/qa-skill-suite/bug-report.svg)](https://agentmods.dev/skills/nntan90/qa-skill-suite/bug-report)
Your own site
<a href="https://agentmods.dev/skills/nntan90/qa-skill-suite/bug-report"><img src="https://agentmods.dev/badge/skills/nntan90/qa-skill-suite/bug-report.svg" alt="Measured on agentmods" height="20"></a>
Per session 119 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,474 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 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 5.1 $0.00119 $0.03474
Opus 5 $0.00060 $0.01737
Sonnet 5 $0.00024 $0.00695
Haiku 4.5 $0.00012 $0.00347

Measured 8d ago against content hash 92e57c698cc0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

bug-report 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 8d 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.

bug-report/SKILL.md · 444 lines

How it starts

The opening of the file, as written. The whole thing — 444 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Bug Report Skill

When to Use This Skill

  • User found unexpected behavior and needs to document it
  • User wants to create a bug ticket for Jira, GitHub Issues, or Linear
  • User wants a standardized template for their team
  • User needs to classify severity/priority of a defect

Agent Persona

Act like a senior QA engineer with 20 years of experience.

  • Use plain, clear English. Short sentences. No robot language.
  • Be direct. If something is wrong or missing, say it straight.
  • Share real experience. Say things like: "I've seen this miss bugs in production before" or "Most teams skip this, but it matters."
  • Always explain WHY a test matters, not just what to do.
  • Point out risks even when the user didn't ask.

Language standard: Write all output in B1-level English. Simple words. Active voice. One idea per sentence.


Output Review Loop

After producing any output, the agent MUST run this self-check and include the result at the bottom.

My Self-Check:
  [ ] Happy path — covered
  [ ] Error / failure cases — at least 2 covered
  [ ] Boundary values — covered (if numbers or ranges exist)
  [ ] Empty / null / zero inputs — covered
  [ ] Auth / permission — covered (if feature has login)
  [ ] Nothing obvious missing that a real user would try
  [ ] Output is complete — no "TODO" or "add more" placeholders

Verdict: COMPLETE / INCOMPLETE
If INCOMPLETE — what I still need to add: [list]

Input Schema

Trước khi viết bug report, agent PHẢI thu thập đủ thông tin sau. Nếu user mô tả tự do, hãy tự phân tích và điền vào template. Hỏi lại chỉ khi thiếu thông tin bắt buộc.

INPUT REQUIRED:
  # --- Mandatory ---
  observed_behavior:
    description: "Điều gì đã xảy ra (thực tế)"
    format: "Mô tả cụ thể, dùng đúng text từ UI/log nếu có"
    bad_example: "Button không hoạt động"
    good_example: "Submit button trên trang /checkout không phản hồi khi click, không có loading state, không có error message. Console log: TypeError: Cannot read property 'id' of undefined"

  expected_behavior:
    description: "Hành vi mong đợi (should happen)"
    note: "Mô tả đúng đắn theo spec/requirement, không chỉ nói 'should work'"
    example: "Click Submit nên gửi POST /api/orders, hiện loading spinner, và redirect sang /orders/success"

  steps_to_reproduce:
    description: "Các bước tái tạo lỗi"
    format: "Numbered steps, mỗi step là 1 action, bắt đầu từ clean state"
    example: |
      1. Open incognito browser
      2. Go to https://app.com/login
      3. Login with [email protected] / password123
      4. Navigate to /cart, add 2 items
      5. Click 'Proceed to Checkout'
      6. Fill card: 4111111111111111, 12/27, CVV 123
      7. Click 'Submit Order'
      8. Observe: button becomes unresponsive

  # --- Strongly Recommended ---
  environment:
    description: "Môi trường xảy ra lỗi"
    fields:
      app_version: "v2.3.1 hoặc commit SHA abc1234"
      environment: "Production / Staging / Dev"
      os: "macOS 14.3 / Windows 11 / Ubuntu 22.04"
      browser: "Chrome 123 / Firefox 124 / Safari 17"
      device: "Desktop / iPhone 15 Pro / Samsung Galaxy S24"
      user_role: "Admin / Free user / Guest / [specific role]"

  severity_hint:
    description: "Gợi ý mức độ nghiệm trọng (agent sẽ xác nhận lại)"
    options: ["Critical — system down", "High — major feature broken", "Medium — partial impact", "Low — cosmetic"]
    note: "Nếu không biết, agent sẽ tự phân loại dựa trên impact"

  # --- Optional ---
  frequency:
    description: "Tần suất xảy ra"
    options: ["Always (100%)", "Often (>50%)", "Sometimes (~25%)", "Rarely (<10%)", "Once"]

  evidence:
    description: "Bằng chứng kèm theo"
    types: ["screenshot", "video/loom", "console errors", "network request/response", "server logs"]
    note: "Paste text evidence trực tiếp nếu có; mô tả những gì cần attach"

  target_platform:
    description: "Platform để format bug report"
    options: ["standard (default)", "jira", "github", "linear"]
    default: "standard"

Read the full file on GitHub · 444 lines

Files

What ships with it

1 file 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. 8d ago First seen · 444 lines · 119 tokens per session scan A 92e57c698cc0

Subscribe to this mod's changes

bug-report is a skill published in the GitHub repository nntan90/qa-skill-suite (5 stars, last pushed 4mo ago), licensed MIT. It adds 119 tokens to every session and 3,474 once invoked, about $0.0006 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

debug-optimize-lcp

Guides debugging and optimizing Largest Contentful Paint (LCP) using Chrome DevTools MCP tools. Use this skill whenever the user asks about LCP performance, slow page loads, Core Web Vitals optimization, or wants to understand why their page's main content takes too long to appear. Also use when the user mentions…

ChromeDevTools/chrome-devtools-mcp · 99 tokens

systematic-debugging

Use when debugging a failing test, build error, or runtime issue that isn't immediately obvious. Guides a 4-phase root cause analysis instead of random fix attempts.

open-metadata/OpenMetadata · 37 tokens

diagnose

Trace from a reproduced symptom to the source code that causes it. Pin the specific file and approximate line, rate confidence in the cause and clarity of the fix independently, and always propose a concrete fix.

emdash-cms/emdash · 43 tokens

repro-admin

Reproduce an EmDash admin UI bug. Attach a container, start the demo dev server, drive the admin with agent-browser using the dev-bypass session, and capture the reproduction as screenshots plus a replayable transcript.

emdash-cms/emdash · 48 tokens

log-error-digest

Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or…

zebbern/claude-code-guide · 71 tokens

byted-util-volcengine-detect-retry

An orchestration workflow for Volcengine Cloud Detect, a service that checks websites or network endpoints from test locations.

bytedance/agentkit-samples · 101 tokens