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 ArabelaTso/Skills-4-SE --skill issue-report-generatorgit clone --depth 1 https://github.com/ArabelaTso/Skills-4-SEWrote 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/arabelatso/skills-4-se/issue-report-generator)<a href="https://agentmods.dev/skills/arabelatso/skills-4-se/issue-report-generator"><img src="https://agentmods.dev/badge/skills/arabelatso/skills-4-se/issue-report-generator/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.
<a href="https://agentmods.dev/skills/arabelatso/skills-4-se/issue-report-generator"><img src="https://agentmods.dev/badge/skills/arabelatso/skills-4-se/issue-report-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 230 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00082 | $0.03285 |
| Opus 5 | $0.00041 | $0.01643 |
| Sonnet 5 | $0.00016 | $0.00657 |
| Haiku 4.5 | $0.00008 | $0.00329 |
Grade A, and why
issue-report-generator 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 7d 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 — 493 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Issue Report Generator
Overview
Generate comprehensive, developer-friendly issue reports from failing tests. Analyze test failures, identify affected code, infer root causes when possible, and produce structured Markdown reports ready for issue tracking systems.
Report Generation Workflow
Step 1: Analyze the Failing Test
Understand what the test is checking and why it fails:
-
Identify the test:
- Test file path
- Test class/function name
- Test method name
-
Understand test intent:
- What functionality is being tested?
- What is the expected behavior?
- What assertions are being made?
-
Analyze the failure:
- Exception type (if any)
- Assertion failure details
- Expected vs. actual values
- Error messages
- Stack trace
-
Extract key information:
- Failure type (exception, assertion, timeout, etc.)
- Failure location (file, line number)
- Failure context (method calls, parameters)
Step 2: Identify Affected Code Components
Locate the code related to the failure:
-
From stack trace:
- Extract file paths
- Extract class/method names
- Extract line numbers
- Identify the failure point
-
From test code:
- Find the method/class being tested
- Identify dependencies
- Locate related components
-
Code analysis:
- Read the failing code section
- Understand the logic
- Identify potential issues
-
Record locations:
- Primary affected file(s)
- Specific methods/functions
- Line numbers or ranges
Step 3: Infer Root Cause
Determine why the failure occurs (when possible):
-
For exceptions:
- Which variable/object caused it?
- Why is it null/invalid?
- Where should it be initialized?
- What condition triggers the exception?
-
For assertion failures:
- Why does actual differ from expected?
- What code produces the wrong value?
- What condition causes the mismatch?
- Is there a logic error?
-
For timeouts:
- What operation is slow?
- Is there an infinite loop?
- Is there inefficient algorithm?
- Are there blocking operations?
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.
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.
- 7d ago First seen · 493 lines · 82 tokens per session scan A 17cb7ac9a5d4
issue-report-generator is a skill published in the GitHub repository ArabelaTso/Skills-4-SE (252 stars, last pushed 20d ago), licensed Apache-2.0. It adds 82 tokens to every session and 3,285 once invoked, about $0.0004 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 2026-09-03.
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