resume-tailoring

resume-tailoring is a skill for Claude Code, Codex from sayantan94/AppliedIn. It costs 67 tokens per session (771 once invoked), scanned A, original, MIT.

A résumé editor that adapts a LaTeX résumé—a résumé written in a document-formatting language—to one job description. It changes wording, ordering, and the summary while keeping the résumé truthful, then compiles the result.

In plain words
What is it for?
Use it to tailor a résumé for a specific opening, reorder skills and experience, sharpen the summary, and produce a compiled résumé file.
Why use it?
It helps present genuine experience using the job posting’s terminology and put the most relevant evidence first. It avoids adding facts that are not in the original résumé.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to tailor a résumé for a specific opening, reorder skills and experience, sharpen the summary, and produce a compiled résumé file.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/sayantan94/appliedin/resume-tailoring
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 sayantan94/AppliedIn --skill resume-tailoring
Clone the repo
git clone --depth 1 https://github.com/sayantan94/AppliedIn

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 resume-tailoring

README.md
[![agentmods](https://agentmods.dev/badge/skills/sayantan94/appliedin/resume-tailoring/github.svg)](https://agentmods.dev/skills/sayantan94/appliedin/resume-tailoring)
Your own site
<a href="https://agentmods.dev/skills/sayantan94/appliedin/resume-tailoring"><img src="https://agentmods.dev/badge/skills/sayantan94/appliedin/resume-tailoring/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 resume-tailoring

Your own site · 80×15
<a href="https://agentmods.dev/skills/sayantan94/appliedin/resume-tailoring"><img src="https://agentmods.dev/badge/skills/sayantan94/appliedin/resume-tailoring.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 771 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 $0.00771
Opus 5 $0.00034 $0.00385
Sonnet 5 $0.00013 $0.00154
Haiku 4.5 $0.00007 $0.00077

Measured 10d ago against content hash 523efac12948, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

resume-tailoring 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 10d 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.

src/agent/skills/resume-tailoring/SKILL.md · 61 lines

How it starts

The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Résumé tailoring

Tailor the candidate's seed résumé — the LaTeX in state base_latex — to the job description (state jd_text). Output the full tailored .tex via save_tailored_resume. The result must stay 100% truthful and still compile.

Instructions

Step 1: Read the JD for signal

Extract must-have skills, seniority, domain, and the exact vocabulary it uses ("agentic", "MCP", "multi-agent", "platform", "LLM evaluation").

Step 2: Edit the LaTeX — reword, rephrase, then reorder

Tailoring is primarily rewording and rephrasing, not restructuring. Change only these:

  • \resumeItem{...} bullets — rephrase each bullet in the JD's own vocabulary and framing: keep the true accomplishment, but say it the way the JD says it (its verbs, its nouns, its emphasis). Only where it's genuinely true. Then reorder so the most JD-relevant come first.
  • The Summary line — rephrase it to target this exact role.
  • The order of skills within the Skills line.

Example — JD stresses "multi-agent orchestration": \resumeItem{Built workflows where agents talk to each other}\resumeItem{Built multi-agent orchestration for agent-to-agent workflows} (same fact, JD's words). Never claim orchestration if the seed doesn't show it.

Leave untouched, byte-for-byte:

  • Every \resumeSubheading{...} / \resumeSubheadingSingle{...} line (employer, title, dates, project name, patent) — these are the immutable facts.
  • The preamble, \section headers, and document structure.

For detailed techniques (truthful vocabulary mirroring, quantification, hard cases), consult references/emphasis-techniques.md.

Step 3: Save

Call save_tailored_resume(tailored_latex=<the full .tex>). It validates the facts survived, compiles the PDF with Tectonic, and uploads it. If it returns missing_facts, you altered a \resumeSubheading line — restore it verbatim and re-save.

Hard rules

  • NEVER change or drop an employer, title, employment date, degree, institution, certification, or patent number. Copy those lines verbatim.
  • NEVER add a skill or achievement the seed doesn't contain.
  • Keep the LaTeX valid — balanced braces, defined macros only. Every claim must survive an interview.
  • NEVER write internal engineering minutiae. A bullet states what was built and what it achieved, never the private history of how the code got there. Banned: line/file counts and deltas ("cut 3.1K lines across 5 files to 636 across 2"), refactor and rewrite narratives, bug-hunt stories, commit or PR counts, names of internal modules or subprocesses, and framing that describes fixing your own earlier mistake. A reader outside the repo cannot verify any of it, and reducing code is not an accomplishment on its own — it reads as churn. Rewrite to the outcome: what the system now does, at what scale, for whom.

Read the full file on GitHub · 61 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. 10d ago First seen · 61 lines · 67 tokens per session scan A 523efac12948

Subscribe to this mod's changes

resume-tailoring is a skill published in the GitHub repository sayantan94/AppliedIn (7 stars, last pushed yesterday), licensed MIT. It adds 67 tokens to every session and 771 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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