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 ishandutta2007/Awesome-AI-Job-Hunting --skill job-application-assistantgit clone --depth 1 https://github.com/ishandutta2007/Awesome-AI-Job-HuntingWrote 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/ishandutta2007/awesome-ai-job-hunting/job-application-assistant)<a href="https://agentmods.dev/skills/ishandutta2007/awesome-ai-job-hunting/job-application-assistant"><img src="https://agentmods.dev/badge/skills/ishandutta2007/awesome-ai-job-hunting/job-application-assistant/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/ishandutta2007/awesome-ai-job-hunting/job-application-assistant"><img src="https://agentmods.dev/badge/skills/ishandutta2007/awesome-ai-job-hunting/job-application-assistant.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 | $0.00067 | $0.01123 |
| Opus 5 | $0.00034 | $0.00562 |
| Sonnet 5 | $0.00013 | $0.00225 |
| Haiku 4.5 | $0.00007 | $0.00112 |
Grade A, and why
job-application-assistant 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.
This is a copy
100% identical to job-application-assistant — 0 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Job Application Assistant
Workflow
When the user provides a job posting (URL or text), follow this workflow:
Step 1: Research & Evaluate Fit
- Fetch the job posting content (use WebFetch for URLs). A 403 is not a dead end - follow the escalation order in
09-web-research.mdbefore concluding a page is unavailable, and prefer the employer's own careers posting over an aggregator listing - Keep the full posting text verbatim for Step 3b to archive - never a summary
- Analyze the posting for required competencies, keywords, and priorities
- Research the company (website, LinkedIn, mission, recent news), per
09-web-research.md - Score the posting against the candidate's profile using the framework in
04-job-evaluation.md - Present the evaluation table and verdict
- Suggest whether the candidate should call the employer before applying (see
04-job-evaluation.mdfor guidance) - Ask the user if they want to proceed with an application
Step 2: Tailor CV
- Before writing either document, derive
<company>_<role>once by the Subfolder naming rule indocuments/README.md; reuse that exact value for the CV, cover letter, and Step 3b archive path. If the rule says to stop because the derived name is empty, stop before creating any file. - Read the most relevant existing CV variant from
cv/as a starting point - Follow the guidelines in
05-cv-templates.md - Create
cv/main_<company>_<role>.texwith tailored content - Adjust: profile statement, skills section, experience bullet emphasis, section order
Step 3: Write Cover Letter
- Follow the writing style rules in
03-writing-style.md(critical: no em-dashes, no cliches) - Follow the template structure in
06-cover-letter-templates.md - Create
cover_letters/cover_<company>_<role>.tex - Ensure the letter connects specific experience to the role requirements
Step 3b: Record the Application
- Run this once both documents exist. A CV or cover letter drafted alone is not yet an application.
- Follow
/applyStep 6b (.claude/commands/apply.md) exactly: same header, same match-then-update rule, samedraftedrow, same posting archive, same prohibition on touchingjob_scraper/seen_jobs.json. It is stated there once so the two paths cannot drift. Four of its values are named in/apply's own terms:cv_file/cover_letter_fileare the paths written in Steps 2 and 3 here,sourceis the posting URL from Step 1,deadlineis the application deadline from the posting text Step 1 keeps verbatim (empty when the posting states none - never guess one), and the posting text item 7 archives is the one Step 1 read. - This step exists here because
/scrapeStep 5 routes straight into this skill. Without it, that path writes two documents and records nothing.
What ships with it
9 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.
- 12d ago First seen · 79 lines · 67 tokens per session scan A c8b624e90a77
job-application-assistant is a skill published in the GitHub repository ishandutta2007/Awesome-AI-Job-Hunting (3 stars, last pushed 17d ago), licensed MIT. It adds 67 tokens to every session and 1,123 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to job-application-assistant, differing in 0 lines, and is treated as a copy.
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