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 agentmods add skills/ishandutta2007/awesome-ai-job-hunting/job-scrapernpx skills add ishandutta2007/Awesome-AI-Job-Hunting --skill job-scrapergit clone --depth 1 https://github.com/ishandutta2007/Awesome-AI-Job-HuntingWhat 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 | $0.00067 | $0.04637 |
| Opus 5 | $0.00034 | $0.02318 |
| Sonnet 5 | $0.00013 | $0.00927 |
| Haiku 4.5 | $0.00007 | $0.00464 |
Grade A, and why
scrape 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 yesterday.
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.
fields manually. If it returns HTTP 403, retry with browser headers via curl per This is a copy
95% identical to scrape — 13 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Job Scraper
How It Works
This skill searches job portals using the installed portal-search CLIs in
.agents/skills/ (plus WebSearch as a fallback), using queries from your profile.
It deduplicates against previously seen jobs and the application tracker, and
presents new matches with a quick fit assessment.
Invocation
The user triggers this skill by saying things like:
- "Find new jobs"
- "Scrape for jobs"
- "Any new positions?"
- "/scrape"
Optional arguments:
- A focus area, e.g. "/scrape data science" or "/scrape geophysics"
- "broad" to run all search categories, e.g. "/scrape broad"
- "health" to run the portal health check only (Step 4.75), without searching, deduplicating, or presenting jobs - e.g. "/scrape health", or "/scrape health jobnet" to probe one portal even if disabled
Execution Steps
Step 0: Load State
- Read
job_scraper/seen_jobs.json(create if missing - start with{"seen": {}}) - Read
job_search_tracker.csvto extract already-applied companies+roles - Read
search-queries.md(this directory) for the search strategy
Step 1: Search
Read search-queries.md (this directory) for the search strategy. By default, run the top 3 priority query categories. If the user said "broad", run all categories. If the user specified a focus area (e.g. "data science"), prioritize queries from that category.
Use the installed CLI tools as the primary search mechanism. Fall back to WebSearch only for portals that do not have a CLI skill, or if bun is unavailable on the system.
1a. Check bun availability
bun --version
If this fails (bun not installed), skip to 1c (WebSearch fallback) for all portals and note the fallback in the Step 5 output.
1b. Run CLI tools (primary — run these in parallel where possible)
Discover all installed portal CLI skills by reading every SKILL.md found under .agents/skills/*/SKILL.md. Each file documents that portal's exact CLI flags and usage examples. Use each portal's own documented interface — do not guess flags. This approach automatically includes any new portals added via /add-portal without requiring changes to this file.
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.
- yesterday First seen · 270 lines · 67 tokens per session scan A 2c77c3556b61
scrape is a skill published in the GitHub repository ishandutta2007/Awesome-AI-Job-Hunting (3 stars, last pushed 6d ago), licensed MIT. It adds 67 tokens to every session and 4,637 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 95% identical to scrape, differing in 13 lines, and is treated as a copy.
Other skills, from other repositories
General-purpose LinkedIn automation – fetch profiles, search people and companies, send messages, manage connections, create posts, and more. Use when the user wants to interact with LinkedIn.
using-awesome-ai-skills
Discovers and invokes Awesome AI Skills. Use when starting a session or when you need to discover which skill applies to the current task. This is the meta-skill that governs how all other skills are discovered and invoked.
separateweb-capture
Capture a URL into a full-page screenshot, cropped UI item PNGs, and a JSON manifest. Use when the user says separateweb capture , asks to capture a website, or wants UI extraction assets without running the SeparateWeb web app.
demo-6-article-kg
Demo skill that web-fetches two Decoding AI knowledge-graph articles, has the agent itself distill them into a typed entity/relation graph, and renders an interactive dark-themed force-directed KG into one self-contained kg.html — no graph library, no CDN.
apify-ecommerce
Scrape e-commerce data for pricing, reviews, bestsellers, and seller discovery across 30+ platforms including Amazon, Walmart, eBay, Shopify, WooCommerce, and more. Use when user asks about product prices, competitor analysis, store scraping, tech stack detection, food delivery, real estate, or marketplace…
apify-lead-scoring-enrichment
Score and enrich a CSV of B2B leads using Apify Actors. Takes a CSV with company URLs, free-text scoring rules, and an enrichment preference; runs BuiltWith (tech stack), Website Content Crawler (content classification), and Contact Info Scraper (company metadata) for scoring; enriches with either department-specific…