A job-fit checker that compares a job posting with your resume using Gemini, an AI model. It returns a fit level, strengths, gaps, and a recommendation.

Use it with a supported job URL to assess suitability, identify missing qualifications, and decide whether an application is worth pursuing.

It gives a consistent first assessment before you spend time applying. If the full job description cannot be fetched, it can still score the role from its title and reports that limitation.

fit-check — Skill for Claude Code by Mahashwetha

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.

Any agent

npx skills add Mahashwetha/Job-search-email-system-claude --skill fit-check

Clone the repo

git clone --depth 1 https://github.com/Mahashwetha/Job-search-email-system-claude

Made for: Claude Code.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/mahashwetha/job-search-email-system-claude/fit-check/github.svg)](https://agentmods.dev/skills/mahashwetha/job-search-email-system-claude/fit-check)

Your own site

<a href="https://agentmods.dev/skills/mahashwetha/job-search-email-system-claude/fit-check"><img src="https://agentmods.dev/badge/skills/mahashwetha/job-search-email-system-claude/fit-check/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/mahashwetha/job-search-email-system-claude/fit-check"><img src="https://agentmods.dev/badge/skills/mahashwetha/job-search-email-system-claude/fit-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 318 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00067	$0.00318
Opus 5.5	$0.00027	$0.00127
Sonnet 5.5	$0.00013	$0.00064
Haiku 4.5	$0.00007	$0.00032

Measured 20d ago against content hash bd50840cf7c2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

fit-check 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 20d 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.

.claude/skills/fit-check/SKILL.md · 34 lines

What it actually says

Fit Check

Run a job fit analysis against the user's resume using fit_check.py.

Trigger

User says fit-check <url> or pastes a job URL asking "is this a good fit" / "check fit".

Steps

Extract the URL from the user's message.
Optionally extract --title and --company if the user mentioned them.
Run from the project root:

cd claude-job-agent
python fit_check.py "<url>" [--title "..."] [--company "..."]

Show the output to the user.
If the score is Weak or Moderate, offer a brief 1-line note on whether it's still worth applying (e.g. if it's a stretch role they want to aim for).

Notes

fit_scorer.py must be in the same directory (it is).
FIT_SCORE_ENABLED = True must be set in config.py (default is True).
WTTJ and BuiltIn URLs are supported. LinkedIn guest API is also supported.
If description fetch fails, the score is title-only — the output will say so.

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.

20d ago Changed bd50840cf7c2
1mo ago First seen · 34 lines · 67 tokens per session scan A f46c0ba4a6b0

Subscribe to this mod's changes

fit-check is a skill published in the GitHub repository Mahashwetha/Job-search-email-system-claude (10 stars, last pushed today), licensed MIT. It adds 67 tokens to every session and 318 once invoked, about $0.0003 per session on Opus 5.5. 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.

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