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 skills add jaktestowac/awesome-copilot-for-testers --skill reporting-bugsgit clone --depth 1 https://github.com/jaktestowac/awesome-copilot-for-testersWrote 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.
[](https://agentmods.dev/skills/jaktestowac/awesome-copilot-for-testers/reporting-bugs)<a href="https://agentmods.dev/skills/jaktestowac/awesome-copilot-for-testers/reporting-bugs"><img src="https://agentmods.dev/badge/skills/jaktestowac/awesome-copilot-for-testers/reporting-bugs.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00053 | $0.00944 |
| Opus 5 | $0.00026 | $0.00472 |
| Sonnet 5 | $0.00011 | $0.00189 |
| Haiku 4.5 | $0.00005 | $0.00094 |
Grade A, and why
reporting-bugs 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.
How it starts
The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reporting Bugs
Use this skill to turn messy observations into bug reports that developers can actually act on. It is optimized for reproducibility, evidence quality, and clean communication rather than speculative root-cause analysis.
When to Use
- write a bug report from rough notes or screenshots
- normalize findings from exploratory testing
- triage an intermittent or hard-to-reproduce issue
- rewrite a vague defect description into a developer-ready report
- capture product, accessibility, or automation defects in a consistent format
Reporting Rules
- Observation first - describe what happened before discussing why it may have happened.
- Reproduction beats opinion - a calm, reproducible report is worth more than a dramatic summary.
- Evidence should travel with the bug - attach logs, screenshots, recordings, payloads, or selectors when available.
- Severity follows impact - grade the issue by user or business impact, not by frustration level.
- Unknowns stay visible - if confidence is low, say so clearly instead of bluffing.
Workflow
Phase 0: Gather the raw material
Collect what exists today:
- short summary of the problem
- environment and build details
- preconditions or setup state
- reproduction steps or triggering actions
- actual result
- expected result
- evidence such as screenshots, traces, logs, payloads, or timestamps
If critical pieces are missing, ask only for what is needed to make the report actionable.
Phase 1: Normalize the reproduction story
Reduce the issue to a clean sequence:
- starting state
- user action or system trigger
- observable result
- expected result
If the issue is intermittent, capture the pattern explicitly:
alwayssometimesseen oncenot reproduced yet
Phase 2: Classify the issue
Give the bug enough metadata to route it correctly.
Suggested dimensions:
- Category - functional, data, auth, performance, accessibility, automation, or integration
- Severity - use
./resources/severity-matrix.md - Confidence - confirmed, likely, or suspected
- Reproducibility - always, intermittent, once, or unknown
What ships with it
2 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.
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.
- 8d ago First seen · 127 lines · 53 tokens per session scan A 12b47c108e70
reporting-bugs is a skill published in the GitHub repository jaktestowac/awesome-copilot-for-testers (113 stars, last pushed 13d ago), licensed MIT. It adds 53 tokens to every session and 944 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
Issue Triage
Turn messy bug reports into actionable tasks and reproduction steps.
debug-behavior
Investigate inconsistent or incorrect behavior with a structured workflow.
skill-debug
Debug a reproducible symptom with a bounded feedback loop and original-scenario verification.
systemic-issue-triage
Trigger: new issue, bug report, triage, backlog, issue flood, community report, root cause, dead-end, blocked user. Attack issues by root class, never one-by-one; fixes must shrink the system, not grow it.
issue-root-resolution
Trigger: root audit, atacar la raíz, issue roots, backlog roots, mechanism map, deletion-driven fix, resolver issues de raíz, close outdated issues. Audit and resolve issue clusters by verified root cause.
agents-sdk-dotnet-debugging
Use when troubleshooting an agent built with the Microsoft Agents SDK (Microsoft.Agents.Hosting.AspNetCore and related packages) in C# / .NET. Trigger on any of these symptoms: build or C# compile errors, crashes on startup, 401 or auth errors on incoming requests, the bot not responding to messages, appsettings.json…