mcp-overleaf-server: Skill for Claude Code

.agents/skills/jobs/SKILL.md

jobs is a skill for Claude Code from abhi-ramtel/mcp-overleaf-server. It costs 65 tokens per session (2,382 once invoked), scanned A, original, MIT.

A guided batch workflow for collecting several job postings and preparing a tailored résumé and cover letter for each one.

In plain words
What is it for?
Use it to enter a group of jobs, choose résumé or CV and cover-letter options, and produce application materials for each posting.
Why use it?
It avoids entering and adapting every application separately when you are applying to multiple jobs.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool; installed under .agents/ (shared by several agents).

This is abhi-ramtel/mcp-overleaf-server's own configuration. It tells Claude Code how to work on mcp-overleaf-server itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything mcp-overleaf-server configures →

Reuse

Borrowing it

Nothing to install: this file belongs to abhi-ramtel/mcp-overleaf-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/abhi-ramtel/mcp-overleaf-server/main/.agents/skills/jobs/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/abhi-ramtel/mcp-overleaf-server

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 jobs

README.md
[![agentmods](https://agentmods.dev/badge/skills/abhi-ramtel/mcp-overleaf-server/jobs/github.svg)](https://agentmods.dev/skills/abhi-ramtel/mcp-overleaf-server/jobs)
Your own site
<a href="https://agentmods.dev/skills/abhi-ramtel/mcp-overleaf-server/jobs"><img src="https://agentmods.dev/badge/skills/abhi-ramtel/mcp-overleaf-server/jobs/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 jobs

Your own site · 80×15
<a href="https://agentmods.dev/skills/abhi-ramtel/mcp-overleaf-server/jobs"><img src="https://agentmods.dev/badge/skills/abhi-ramtel/mcp-overleaf-server/jobs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,382 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 $0.00065 $0.02382
Opus 5.5 $0.00026 $0.00953
Sonnet 5.5 $0.00013 $0.00476
Haiku 4.5 $0.00006 $0.00238

Measured 14d ago against content hash 888d2345ec2c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

jobs 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 14d 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.

.agents/skills/jobs/SKILL.md · 170 lines

How it starts

The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Multi-job entry

Replaces hand-writing a jobs JSON. Ask how many jobs, render that many entry cards as a form in the chat, then run the existing batch pipeline on what comes back.

$ARGUMENTS may already contain the job count (e.g. /jobs 4).

Step 0 — infer before asking

Skip any question you can already answer:

  • A number in $ARGUMENTS or in the user's message ("I have 3 jobs") → that's the count, skip step 1.
  • Job postings already pasted in this conversation, attached as files, or referenced by a readable local path/URL → skip straight to step 3. Read the source first; do not make the user paste it again.
  • job.json in the repo root filled in with real values → offer to use it instead of the form.

Never ask for something the conversation already told you.

Step 1 — how many jobs

Call mcp__visualize__read_me with modules: ["elicitation"] first — it carries the canonical form chrome and the current design rules. Then render form 1 from forms.md with mcp__visualize__show_widget.

It asks three things at once: job count (1–30), résumé vs CV, and cover letters. Stop and wait for the reply — it arrives as the user's next message.

Step 2 — the job cards

Render form 2 from forms.md, repeating the job block exactly N times with the index incremented. Only include the per-job cover-letter pills when step 1 answered "let me pick per job".

Cap at 30 (MAX_PLAN_JOBS in src/core/batch.ts). If more are wanted, run the first 30 and say so. Above ~8 jobs the form gets long — render it anyway rather than splitting it; the batch itself is chunked later.

Step 3 — parse the reply

The submitted answers arrive as one line of Label: value pairs, with any value over 200 characters replaced by (N chars — see below) and repeated verbatim under a --- Full content --- fold. Read the fold — that's where the job descriptions are.

Build a list of { company, position, jobDescription, jobUrl, questions }:

  • Job N posting → jobDescription. Required. Drop any job whose posting is blank and say which.
  • Job N company / Job N role → if blank, read them out of the posting text. They are almost always in the first lines. Say what you inferred so it can be corrected.
  • Job N link → jobUrl, omit if blank.
  • Job N questions → split on newlines into questions, omit if blank.

Read the full file on GitHub · 170 lines

Files

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.

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. 14d ago Changed · +43 lines 888d2345ec2c
  2. 2mo ago First seen · 127 lines · 65 tokens per session scan A 3de4e4c83eb4

Subscribe to this mod's changes

jobs is a skill published in the GitHub repository abhi-ramtel/mcp-overleaf-server (1 stars, last pushed 15d ago), licensed MIT. It adds 65 tokens to every session and 2,382 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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