fit-check

fit-check is a skill for Claude Code from Mahashwetha/Job-search-email-system-claude. It costs 67 tokens per session (328 once invoked), scanned A, original, MIT.

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.

In plain words
What is it for?
Use it with a supported job URL to assess suitability, identify missing qualifications, and decide whether an application is worth pursuing.
Why use it?
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.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

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

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mahashwetha/job-search-email-system-claude/fit-check
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.

agentmods badge for fit-check

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.

agentmods 80×15 button for fit-check

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 328 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00067 $0.00328
Opus 5 $0.00034 $0.00164
Sonnet 5 $0.00013 $0.00066
Haiku 4.5 $0.00007 $0.00033

Measured 12d ago against content hash f46c0ba4a6b0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, 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 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.

.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

  1. Extract the URL from the user's message.
  2. Optionally extract --title and --company if the user mentioned them.
  3. Run from the project root:
cd C:\Users\mahas\Learnings\claude-job-agent
python fit_check.py "<url>" [--title "..."] [--company "..."]
  1. Show the output to the user.
  2. 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.

  1. 12d 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 (9 stars, last pushed 12d ago), licensed MIT. It adds 67 tokens to every session and 328 once invoked, about $0.0003 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.

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