interview

interview is a skill for Claude Code, Codex from Sma1lboy/coforce-apply. It costs 85 tokens per session (1,440 once invoked), scanned A, original, MIT.

An interview-preparation workflow for a specific job application that has been tracked. It builds preparation material from the saved job description, submitted résumé, earlier feedback, and cached company research, and can optionally run a practice interview.

In plain words
What is it for?
Use it to prepare for an upcoming interview or practise against a tracked application, including applications identified by company and role.
Why use it?
It keeps preparation consistent with what the employer has already read and adapts the discussion to the current interview stage.

Skill for Claude CodeCodex

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/sma1lboy/coforce-apply/interview
Any agent
npx skills add Sma1lboy/coforce-apply --skill interview
Clone the repo
git clone --depth 1 https://github.com/Sma1lboy/coforce-apply

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 interview

README.md
[![agentmods](https://agentmods.dev/badge/skills/sma1lboy/coforce-apply/interview.svg)](https://agentmods.dev/skills/sma1lboy/coforce-apply/interview)
Your own site
<a href="https://agentmods.dev/skills/sma1lboy/coforce-apply/interview"><img src="https://agentmods.dev/badge/skills/sma1lboy/coforce-apply/interview.svg" alt="Measured on agentmods" height="20"></a>
Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,440 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 $0.00085 $0.01440
Opus 5 $0.00043 $0.00720
Sonnet 5 $0.00017 $0.00288
Haiku 4.5 $0.00009 $0.00144

Measured 3d ago against content hash fbbaa19ab35c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

interview 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.

.agents/skills/interview/SKILL.md · 123 lines

How it starts

The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Interview — prep for a tracked application

The apply/campaign skills optimize what the company reads; this skill optimizes what the company hears. The bridge is consistency: the interviewer has read the submitted resume, so every talking point prepared here must match what that document claims.

Read ~/.coforce/instructions.md first if present — it overrides everything below. Data home resolves as $COFORCE_HOME<checkout>/.coforce/~/.coforce.

Step 0: Identify the application

$ARGUMENTS may name a company (optionally a role). Match against ~/.coforce/applications.json (tracker skill's schema), case-insensitive on company, then position/title. One match → proceed. Several → list and ask. None → not tracked; accept the posting and role directly if the user wants to prep anyway (suggest tracking it after).

Without an argument: list entries whose status suggests a live process (interviewing, offer, or applied updated in the last 21 days) and ask which one. Prep targets a specific application — for generic practice, prep against a real tracked entry instead.

Step 1: Load the application context

  1. The tracker entry: description (the JD as applied to), notes, historyfeedback recorded from an earlier stage is the highest-value input for the next stage's prep.
  2. The archive ~/.coforce/applications/<id>/: the resume PDF that was actually submitted (campaign copy or out/ copy). This is what the interviewer read — Read it; every story told in the interview must be consistent with its claims. Also any existing interview-prep.md (you are updating for a new stage, not starting over) and the global interview-cheatsheet.md sibling if present.
  3. ~/.coforce/profile.json — the verified pool. STAR stories may only draw on bullets and facts that live there; an interview answer is held to the same never-fabricate law as the resume.
  4. Ask the user what this interview is (skip anything already recorded): stage (phone screen / technical / system design / behavioral / final), date, format, and who is interviewing (names/titles if known).

Read the full file on GitHub · 123 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 · 123 lines · 85 tokens per session scan A fbbaa19ab35c

Subscribe to this mod's changes

interview is a skill published in the GitHub repository Sma1lboy/coforce-apply (5 stars, last pushed 4d ago), licensed MIT. It adds 85 tokens to every session and 1,440 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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