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 arozumenko/sdlc-skills --skill reproducing-issuesgit clone --depth 1 https://github.com/arozumenko/sdlc-skillsWrote 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/arozumenko/sdlc-skills/reproducing-issues)<a href="https://agentmods.dev/skills/arozumenko/sdlc-skills/reproducing-issues"><img src="https://agentmods.dev/badge/skills/arozumenko/sdlc-skills/reproducing-issues/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/arozumenko/sdlc-skills/reproducing-issues"><img src="https://agentmods.dev/badge/skills/arozumenko/sdlc-skills/reproducing-issues.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00066 | $0.00892 |
| Opus 5 | $0.00033 | $0.00446 |
| Sonnet 5 | $0.00013 | $0.00178 |
| Haiku 4.5 | $0.00007 | $0.00089 |
Grade A, and why
reproducing-issues scanned grade A with 1 finding 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 10d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **API** → reproduce the failing request with `curl` or a small script; How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reproducing Issues
Turn a vague bug report into precise, repeatable reproduction steps backed by evidence, ending in a clear verdict. Reproduction and documentation only — you do NOT fix code.
Platform & systems
Findings go on the tracker ticket — the source of truth — using the
tracker scout recorded in .agents/profile.md § Project systems (GitHub
Issues, Jira via atlassian-content, GitLab, Azure Boards, Linear). The
gh issue … commands below are the GitHub reference; translate per
.agents/workflow.md § Git host. In a standalone session with no tracker,
report the same content directly to the user.
Methodology — 5 phases
1. Intake
Read the report in full (gh issue view <N> or the tracker equivalent).
Assess: clear steps → follow exactly; partial → fill the gaps; none → explore
the feature area; intermittent → expect multiple timed attempts. Note that
reproduction has started on the ticket.
2. Environment setup
Identify the target URL/endpoint/page, auth (user role, credentials), prerequisite data/state, and client requirements. Reproduction must be repeatable — document the environment.
3. Reproduction attempts
- UI → drive the browser with the
playwright-testingorbrowser-verifyskill: navigate, snapshot for refs, follow the reported steps, screenshot the failure, capture console errors and network requests. - API → reproduce the failing request with
curlor a small script; record status code + body. - Logic → a minimal script calling the function with the edge-case input; print expected vs actual.
- Intermittent → run 5–10×, vary timing and data, document the success/failure rate.
4. Root-cause hints (handoff to RCA)
Gather clues for root-cause-analysis: exact console errors + stack traces;
failing requests / unexpected status codes; works-vs-fails patterns;
triggering vs safe inputs; timing sensitivity. Post these technical
observations on the ticket.
5. Confirmation gate (required)
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.
- 10d ago First seen · 90 lines · 66 tokens per session scan A 72b26b05e33c
reproducing-issues is a skill published in the GitHub repository arozumenko/sdlc-skills (20 stars, last pushed 5d ago), licensed MIT. It adds 66 tokens to every session and 892 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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