Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add artem-from-ua/claude-plugins/plugin install ai-fortuneWrote 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/artem-from-ua/claude-plugins/ai-fortune)<a href="https://agentmods.dev/skills/artem-from-ua/claude-plugins/ai-fortune"><img src="https://agentmods.dev/badge/skills/artem-from-ua/claude-plugins/ai-fortune/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/artem-from-ua/claude-plugins/ai-fortune"><img src="https://agentmods.dev/badge/skills/artem-from-ua/claude-plugins/ai-fortune.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 | $0.00073 | $0.04974 |
| Opus 5 | $0.00036 | $0.02487 |
| Sonnet 5 | $0.00015 | $0.00995 |
| Haiku 4.5 | $0.00007 | $0.00497 |
Grade B, and why
ai-fortune scanned grade B 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
1. `Read` `~/.claude/settings.json` → extract `enabledPlugins` array How it starts
The opening of the file, as written. The whole thing — 336 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/ai-fortune — Career Direction Analysis
Run all phases in order. Each step specifies the exact tools to use.
Phase 0: Load Persistent State
Step 0: Load State
- Read
~/.claude/ai-fortune.json- If exists → load
reportLanguage(language preference),dataSources(saved file paths),answers(interview answers with timestamps),reportsDir(saved report directory) - If not found → start with empty state:
reportLanguage = null,dataSources = {},answers = {},reportsDir = null
- If exists → load
- Set
sources_used = 0counter to track how many of the 9 data sources produce data
Phase 1: Data Collection (Steps 1-6)
Collect data from up to 8 sources. Each source is optional — if unavailable, note it and continue.
Step 1: Memory Chat File
Purpose: Extract industry, tech stack, interests, domain context from the user's Claude web memory export.
- Check if
dataSources.memoryFilePathexists in loaded state - If saved path exists →
AskUserQuestion: "Memory chat file path: use saved path{path}?"- Options: "Use saved path", "Enter different path", "Skip this source"
- If no saved path →
AskUserQuestion: "Where is your Claude memory chat export file? (Markdown file exported from claude.ai)"- Options: "Skip this source"
- Free text for custom path
- If not skipped →
Readthe file - Extract: industry, tech stack, interests, projects, domain expertise, personal context
- Save chosen path to
dataSources.memoryFilePath - Increment
sources_used
Step 1.5: PDF Resume
Purpose: Extract complete career history, tenure patterns, skill timeline, and education.
- Check
dataSources.resumePathin loaded state - If saved path exists and file readable →
AskUserQuestion: "PDF resume: use saved{path}?"- Options: "Use saved path", "Enter different path", "Skip"
- If no saved path →
AskUserQuestion: "Do you have a PDF resume (LinkedIn export or any format)? Adds career history, tenure patterns, and skill verification to the analysis."- Options: "Skip this source"
- Free text for path
- If not skipped →
Readthe PDF (Claude reads PDFs natively) - Extract structured data per
${SKILL_DIR}/references/resume-extraction.md - Save path to
dataSources.resumePath - Increment
sources_used
What ships with it
4 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.
- 10d ago First seen · 336 lines · 73 tokens per session scan B c7c9b081e168
ai-fortune is a skill published in the GitHub repository artem-from-ua/claude-plugins (11 stars, last pushed yesterday), licensed MIT. It adds 73 tokens to every session and 4,974 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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