interviewprep

A tool that creates interview questions from a job description and a resume tailored to that role.

In plain words
What is it for?
Use it to prepare customized interview questions for a specific company, role, and candidate background.
Why use it?
It reduces the work of preparing relevant questions for a particular application.

Skill for Claude CodeCodex

Part of the jobops plugin — 26 skills, 17 agents 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/reggiechan74/jobops/interviewprep
Any agent
npx skills add reggiechan74/JobOps --skill interviewprep
Clone the repo
git clone --depth 1 https://github.com/reggiechan74/JobOps

Made for: Claude Code, Codex.

Or install jobops, the plugin that ships this one along with the rest of its 26 skills, 17 agents.

Per session 15 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,590 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 $0.00015 $0.03590
Opus 5 $0.00008 $0.01795
Sonnet 5 $0.00003 $0.00718
Haiku 4.5 $0.00002 $0.00359

Measured 3d ago against content hash 9445f2e5a3a1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

interviewprep 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 3d 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.

plugins/jobops/skills/interviewprep/SKILL.md · 374 lines

How it starts

The opening of the file, as written. The whole thing — 374 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Configuration

Read .jobops/config.json. If missing, stop with:

JOBOPS NOT CONFIGURED Run /jobops:setup to initialize your workspace.

Use config.directories.<key> for all file paths in this skill. Use config.preferences.cultural_profile if this skill generates resume-style content. Use config.preferences.default_jurisdiction if this skill has jurisdiction-sensitive logic (crisis/legal skills accept --jurisdiction=<ISO-3166-2> to override).

Templates

For each template used by this skill, resolve the full path as:

{config.templates.base_dir}/{config.templates.active.<template_name>}/

Templates referenced by this skill: assessment_report_structure

Application Path Resolution

This skill writes to a per-application folder. Before writing any output:

  1. Parse {Company}_{Role}_{YYYYMMDD} from the job-posting filename, or honor --app=<slug> if supplied. The slug MUST be canonical: a leading PascalCase {Company} token (matching the Company_Intelligence/{Company}/ folder so OSINT links), a PascalCase {Role} (underscores between words allowed), and a trailing compact 8-digit date (20260519 — no hyphens, no time). Reject leading date/time prefixes such as 2026-04-15_214414_...; if the source filename carries one, recompose it into canonical form ({Company}_{Role}_{YYYYMMDD}) before composing the folder path.
  2. Compose the app folder: {config.directories.applications_root}/{app_slug}/.
  3. Resolve this skill's sub-folder by category:
    • resume-development (buildresume, provenance-check) → resume/
    • cover-letter (coverletter) → cover-letter/
    • rubric / assessment (createrubric, assessjob, assesscandidate, auditjobposting) → assessment/
    • briefing / interview prep (briefing, interviewprep) → interview/
  4. If the app folder does not exist, mkdir -p it, then copy {config.directories.job_postings}/{filename}{app_slug}/job_posting.md so the pinned JD cannot silently change under completed work. Ensure the pinned copy begins with YAML front matter carrying output_type: job_posting: if the source JD already has a front-matter block, add the key to it; otherwise wrap a new block (--- / output_type: job_posting / source_jd: {filename} / ---) above the JD body.
  5. Exact-slug collisions (same Company+Role+Date) are not auto-suffixed. If the folder already contains the same output type, require the user to pass --app=<distinct-slug>.
  6. Output filename (fixed; only the sub-folder above is resolved dynamically): write the question set to interview/interview_prep.md; a split set uses interview/interview_prep_part1.md, interview/interview_prep_part2.md, ….

Read the full file on GitHub · 374 lines

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. 3d ago First seen · 374 lines · 15 tokens per session scan A 9445f2e5a3a1

Subscribe to this mod's changes

interviewprep is a skill published in the GitHub repository reggiechan74/JobOps (25 stars, last pushed 3mo ago), licensed MIT. It adds 15 tokens to every session and 3,590 once invoked, about $0.0001 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 2026-08-30.

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