job-search-and-apply

job-search-and-apply is a skill for Claude Code, Codex from XyrusCode/ai-sync. It costs 93 tokens per session (1,765 once invoked), scanned A, original, MIT.

A job-search workflow that finds suitable openings on chosen job boards and prepares tailored application emails for review. Job boards are websites where employers list vacancies.

In plain words
What is it for?
Use it to search for developer or other jobs, collect direct links, and prepare application emails based on the user's experience and preferences.
Why use it?
It reduces the manual work of checking multiple job sites and rewriting an application for every role. Drafts stay for the user to review and send.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/xyruscode/ai-sync/job-search-and-apply
Any agent
npx skills add XyrusCode/ai-sync --skill job-search-and-apply
Clone the repo
git clone --depth 1 https://github.com/XyrusCode/ai-sync

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for job-search-and-apply

README.md
[![agentmods](https://agentmods.dev/badge/skills/xyruscode/ai-sync/job-search-and-apply.svg)](https://agentmods.dev/skills/xyruscode/ai-sync/job-search-and-apply)
Your own site
<a href="https://agentmods.dev/skills/xyruscode/ai-sync/job-search-and-apply"><img src="https://agentmods.dev/badge/skills/xyruscode/ai-sync/job-search-and-apply.svg" alt="Measured on agentmods" height="20"></a>
Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,765 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00093 $0.01765
Opus 5 $0.00046 $0.00882
Sonnet 5 $0.00019 $0.00353
Haiku 4.5 $0.00009 $0.00177

Measured 5d ago against content hash 2324c6c2c697, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

job-search-and-apply 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 5d 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.

skills/job-search-and-apply/SKILL.md · 142 lines

How it starts

The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Job Search & Application Drafting

A repeatable workflow for finding job openings across a prioritized list of sources and turning each one into either a direct link or a ready-to-send application draft — never neither.

Before first use: gather the user's profile

This skill needs a few things from the user (once — reuse across runs, e.g. from memory, a config file, or by asking):

  • Role/stack focus: what kind of roles to search for (title, core tech stack).
  • Location & remote preference: home location, and whether to search local, remote, or both.
  • Sources, in priority order: which job boards to check and in what order. Ask if not given; don't assume a default list — job boards are highly region- and industry-specific.
  • Contact sign-off: email, phone, portfolio/site — used to sign drafted applications.
  • Real, quantified experience to draw on for cover letters (achievements, metrics, skills) — pull from a resume, memory, or ask the user to point to a source. Never invent stats.
  • Whether to name past employers in application content, or keep experience generic ("in a previous role," "I've built...") — ask once, remember the preference.

Step 1: Search, in the user's priority order

For each source in priority order:

  • Prefer a direct connector/API if one is available and connected for that source.
  • Otherwise, web_search for the role + location/remote qualifier on that specific site, then web_fetch the listing page(s) for full details (title, company, pay, remote status, post date).
  • Capture the actual URL for each listing when the source provides one directly (many job boards do). Do not fabricate or guess at a URL — only pass along links returned by a real search or fetch.
  • Some sources (large aggregators in particular) only surface listings via search snippets with no individually fetchable page. Note this explicitly rather than presenting a broken or fabricated link.
  • If the user asks for remote-only, filter on the actual listing content, not just the title — watch for "remote" labels that mean remote-from-a-specific-country or fixed-timezone-hours rather than genuinely open. Flag anything like this explicitly instead of silently including it.
  • If a source turns up nothing new, say so rather than skipping it silently — the user should know it was checked.
  • Only expand beyond the user's given source list if they ask, or if the given sources return nothing relevant — confirm before broadening scope.

Read the full file on GitHub · 142 lines

Changes

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.

  1. 5d ago First seen · 142 lines · 93 tokens per session scan A 2324c6c2c697

Subscribe to this mod's changes

job-search-and-apply is a skill published in the GitHub repository XyrusCode/ai-sync (2 stars, last pushed 2d ago), licensed MIT. It adds 93 tokens to every session and 1,765 once invoked, about $0.0005 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 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens