prep

An interview-preparation workflow that creates a company overview and examples connected to your experience. It uses information about the role, company, résumé, portfolio, and application.

In plain words
What is it for?
Use it to prepare for a phone screen or interview, review a company and job description, and organize matching case studies from your experience.
Why use it?
It gathers relevant preparation material in one place and connects your past work to likely interview discussions.

Skill for Claude CodeCodex

Part of the jfm plugin — 11 skills, 11 commands shipped together

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.

agentmods
npx agentmods add skills/alwaysmap/jobs4me/prep
Any agent
npx skills add alwaysmap/jobs4me --skill prep
Clone the repo
git clone --depth 1 https://github.com/alwaysmap/jobs4me

Made for: Claude Code, Codex.

Or install jfm, the plugin that ships this one along with the rest of its 11 skills, 11 commands.

Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,899 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00080 $0.01899
Opus 5 $0.00040 $0.00949
Sonnet 5 $0.00016 $0.00380
Haiku 4.5 $0.00008 $0.00190

Measured 2d ago against content hash c2f2a557e42f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

prep 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 2d 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.

skills/prep/SKILL.md · 176 lines

How it starts

The opening of the file, as written. The whole thing — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Interview Prep Generator

Create research documents that help the user walk into an interview with company context and pre-mapped case studies.

When to Trigger

  • User explicitly asks for interview prep
  • User moves a role to interviewing stage
  • User says they have a phone screen or interview coming up

Workflow

  1. Read profile.yaml and tracker.yaml

  2. Find the application matching the company name:

    node ${CLAUDE_PLUGIN_ROOT}/scripts/tracker.js find --company "Company Name"
    

    If multiple roles are returned for the same company, list them with role titles and stages and ask which one:

    I found two roles at Google:

    1. Staff Engineer (maybe)
    2. Engineering Manager (interviewing)

    Which one are you prepping for?

  3. Get file paths for the chosen application:

    node ${CLAUDE_PLUGIN_ROOT}/scripts/tracker.js paths --id <id>
    

    This returns company_dir, role_dir, and current file locations.

  4. If a JD exists (check has_jd from paths output), read it. If not, ask the user for the job posting URL and fetch it.

  5. Read the user's evidence: fetch resume URL if provided, read portfolio URLs, read additional context.

  6. Generate the two documents below.

  7. Save files to the company structure:

    • Company Overview → {company_dir}/overview.md (shared across roles at this company)
    • Interview Prep → {role_dir}/prep.md (role-specific) Create directories with mkdir -p if they don't exist.
  8. Update the application's stage to interviewing in tracker.yaml if it isn't already.

  9. Show the user what was created. After saving, present the documents inline:

    Company Overview{company_dir}/overview.md {Show a 3-4 line summary of what the overview covers}

    Interview Prep{role_dir}/prep.md {Show a 3-4 line summary: number of topics covered, key areas, questions to ask}

    Read the full docs in {company_dir}/ or click the links on your board.

Read the full file on GitHub · 176 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. 2d ago First seen · 176 lines · 80 tokens per session scan A c2f2a557e42f

Subscribe to this mod's changes

prep is a skill published in the GitHub repository alwaysmap/jobs4me (2 stars, last pushed 1mo ago), licensed MIT. It adds 80 tokens to every session and 1,899 once invoked, about $0.0004 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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