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 reatlat/fullstory-claude-plugin --skill jira-bug-reportergit clone --depth 1 https://github.com/reatlat/fullstory-claude-pluginWrote 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/reatlat/fullstory-claude-plugin/jira-bug-reporter)<a href="https://agentmods.dev/skills/reatlat/fullstory-claude-plugin/jira-bug-reporter"><img src="https://agentmods.dev/badge/skills/reatlat/fullstory-claude-plugin/jira-bug-reporter/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/reatlat/fullstory-claude-plugin/jira-bug-reporter"><img src="https://agentmods.dev/badge/skills/reatlat/fullstory-claude-plugin/jira-bug-reporter.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 110 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 | $0.00048 | $0.01143 |
| Opus 5 | $0.00024 | $0.00571 |
| Sonnet 5 | $0.00010 | $0.00229 |
| Haiku 4.5 | $0.00005 | $0.00114 |
Grade A, and why
jira-bug-reporter 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 12d 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Jira Bug Reporter
Turn session evidence into detailed bug reports — auto-populated with session URLs, error messages, device info, stack traces, and reproduction steps.
When to Use
- "File a bug for the checkout error we just found"
- "Create a Jira ticket from this rage-click session"
- "Write up the TypeError on /dashboard as a bug report"
- "Report the mobile Safari checkout issue to the engineering team"
Mental Model
You have raw data from Fullstory — session URLs, error messages, timestamps, device info — and you need to turn it into a structured bug report an engineer can act on. The skill formats everything, then the user pastes it into Jira (or you output it as a markdown block ready to copy).
If the user has Jira MCP or a Jira API integration, you can create the ticket directly. Otherwise, you produce a formatted report they can copy-paste.
Workflow
Step 1: Gather evidence
Before writing the report, collect everything:
From error-forensics or frustration-hunter:
- Error message and stack trace
- Page URL where it occurred
- Device and browser (with versions if available)
From session-review:
- Session URL (most important — engineer can watch the replay)
- Timestamp of the error/frustration event
- Screenshots from
session_viewshowing the UI at failure - What the user did before the error (reproduction steps)
- What happened after (did they retry? abandon? work around it?)
From user context:
- How many users are affected? (from
get_opportunity_statsorcompute_metric) - Is this a new regression or an existing issue?
- Severity: cosmetic, functional, or data-loss?
Step 2: Classify severity
| Severity | Definition | Example |
|---|---|---|
| P0 – Critical | Data loss, security, complete outage | Checkout broken for all users |
| P1 – High | Core functionality broken for many users | Rage-click on primary CTA, 400+ users |
| P2 – Medium | Feature broken for some users | Error on settings page, Safari-only, 50 users |
| P3 – Low | Cosmetic issue, edge case | Dead click on rarely-used icon, 5 users |
| P4 – Trivial | Visual polish, nice-to-have | Alignment issue on mobile, no functional impact |
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.
- 12d ago First seen · 111 lines · 48 tokens per session scan A cf3a68a7ba21
jira-bug-reporter is a skill published in the GitHub repository reatlat/fullstory-claude-plugin (62 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 1,143 once invoked, about $0.0002 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.
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