agentic-resume-builder: Skill for Claude Code

.claude/skills/content-interview/SKILL.md

content-interview is a skill for Claude Code from WtotdeD/agentic-resume-builder. It costs 50 tokens per session (3,839 once invoked), scanned A, original, MIT.

An interview workflow that asks about a job, project, achievement, or community contribution and turns the answers into resume content in Markdown. Markdown is plain text with simple formatting marks.

In plain words
What is it for?
Use it to add or extend work experience, showcase a repository or side project, or record a notable project or community contribution in a resume content vault.
Why use it?
It gives structure to experiences that are difficult to describe and checks whether similar content already exists before adding more.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter.

This is WtotdeD/agentic-resume-builder's own configuration. It tells Claude Code how to work on agentic-resume-builder 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 agentic-resume-builder configures →

Reuse

Borrowing it

Nothing to install: this file belongs to WtotdeD/agentic-resume-builder. 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/WtotdeD/agentic-resume-builder/main/.claude/skills/content-interview/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/WtotdeD/agentic-resume-builder

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 content-interview

README.md
[![agentmods](https://agentmods.dev/badge/skills/wtotded/agentic-resume-builder/content-interview/github.svg)](https://agentmods.dev/skills/wtotded/agentic-resume-builder/content-interview)
Your own site
<a href="https://agentmods.dev/skills/wtotded/agentic-resume-builder/content-interview"><img src="https://agentmods.dev/badge/skills/wtotded/agentic-resume-builder/content-interview/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 content-interview

Your own site · 80×15
<a href="https://agentmods.dev/skills/wtotded/agentic-resume-builder/content-interview"><img src="https://agentmods.dev/badge/skills/wtotded/agentic-resume-builder/content-interview.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,839 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 $0.00050 $0.03839
Opus 5.5 $0.00020 $0.01536
Sonnet 5.5 $0.00010 $0.00768
Haiku 4.5 $0.00005 $0.00384

Measured 2mo ago against content hash aeac783ecee1, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

content-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 2mo 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.

.claude/skills/content-interview/SKILL.md · 356 lines

How it starts

The opening of the file, as written. The whole thing — 356 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Content Interview

Interview the user to produce content for the resume vault. The argument $ARGUMENTS may specify the content type and a brief description (e.g., "experience my role at Hyperion" or "showcase my workflow-api repo").

Phase 0: Determine content type

If $ARGUMENTS specifies the type, use it. Otherwise ask:

What are we capturing?

  1. Experience — a job role (produces content/experience/{id}.md)
  2. Showcase — a repo or side project you want to demo (appends to content/showcases.md)
  3. Project — a notable project or community contribution (appends to content/projects.md)

Do not proceed until the type is clear.

Phase 0b: Detect existing content (extend mode)

After determining the content type, check whether an entry already exists:

  • Experience: Search content/experience/*.md for a file matching the company name or description from $ARGUMENTS. Read the file.
  • Showcase: Search content/showcases.md for a matching ## {Name} or id: entry. Read the relevant section.
  • Project: Search content/projects.md for a matching ## {Name} entry.

If existing content is found:

  1. Present a summary to the user:

    I found an existing entry for {name} in {file path}:

    • Narrative: {sentence count} sentences, {paragraph count} paragraphs
    • Sections: {list of ## headings with bullet counts, e.g., "Achievements (6), Leadership & Mentoring (3)"}
    • Technologies: {count} listed

    Do you want to extend this entry (add sections, fill gaps, add bullets) or start a new entry (e.g., a different role at the same company)?

  2. If the user chooses extend, proceed to Phase 1 in extend mode (gap-filling questions).

  3. If the user chooses start new, proceed to Phase 1 as normal (full interview).

If no existing content is found: proceed to Phase 1 as normal.

Phase 0c: Read the lenses before you interview

Do this for every experience interview, new or extend. It is what turns one job into several resumes.

Read the full file on GitHub · 356 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. 2mo ago First seen · 356 lines · 0 tokens per session scan A aeac783ecee1

Subscribe to this mod's changes

content-interview is a skill published in the GitHub repository WtotdeD/agentic-resume-builder (2 stars, last pushed 2mo ago), licensed MIT. It adds 50 tokens to every session and 3,839 once invoked, about $0.0002 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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