resume-importing
Converts plain-text resumes into organized YAML data while maintaining original phrasing.
Install
mkdir -p .claude/skills/resume-importing && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/13356" && unzip -o skill.zip -d .claude/skills/resume-importing && rm skill.zipInstalls to .claude/skills/resume-importing
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Extract a draft data/master.yaml from plain-text resume content while preserving the user's resume wording.Key capabilities
- →Extract structured YAML from free-form resume text.
- →Preserve the user's bullet wording verbatim.
- →Generate stable, slug-style IDs for entries.
- →Assign priorities in 10-point bands within each role or project.
- →Choose tags from a predefined vocabulary.
- →Preserve dates verbatim from the resume.
How it works
This skill parses free-form resume text, extracts relevant information, and structures it into a YAML format conforming to master.schema.yaml, while preserving original wording and generating unique IDs.
Inputs & outputs
When to use resume-importing
- →Standardizing candidate resume data
- →Importing profile info for portfolio sites
- →Organizing work history for automated exports
About this skill
Resume importing
Role
Extract structured YAML conforming to master.schema.yaml from free-form
resume text. You are not a resume writer in this task. Preserve the user's
bullet wording verbatim, with only light whitespace trimming, and restructure
the content into the schema.
Do not improve, embellish, or restyle thin bullets. Thin input still passes through; the user will edit the draft after import.
Schema
Use the provided master.schema.yaml as the source of truth. Emit a single
YAML mapping with these sections when present in the resume:
profile.{name,email,headline?,location?,phone?,links?}experience[].{id,company,role,start,end,bullets[].{id,text,priority,tags,impact?,categories?}}projects[]using the project schema:id,name, optionalsubtitle,url,start,end,tech, andbullets[]with the same bullet shapeskills[].{category,items}education[].{id,institution,location?,degree,start,end,details?}
Required values must be populated when the resume states them. Optional values must be omitted when the resume does not mention them.
ID generation
Generate stable, slug-style IDs:
- Lowercase letters, digits, and underscores only.
- For an experience entry, use a company token such as
acmelabs. - For an experience bullet, use
<experience-id>_<short-topic-token>, such asacmelabs_workflow_engine. - For a project bullet, use
<project-id>_<short-topic-token>. - For education, use a stable institution token such as
state_u.
IDs must be unique across the document and reference-stable. If two IDs would collide, add a short distinguishing token rather than a random suffix.
Priorities
Assign priorities in 10-point bands within each role or project:
100for the most impactful bullet in that role or project.- Decrement by 10 for the next bullets.
- Preserve the resume's apparent order and emphasis. Do not sort arbitrarily.
Tags
Choose only from this vocabulary:
platform, backend, frontend, infra, ml, data-pipeline,
distributed, performance, observability, security, leadership,
product, mobile, open-source
Multiple tags per bullet are fine. Do not invent new tags. If no tag is a perfect fit, choose the closest one or omit tags rather than creating a new label.
Dates
Preserve dates verbatim from the resume:
- Keep
March 2022asMarch 2022. - Keep
PresentasPresent. - Keep
2019-06as2019-06.
Do not normalize or reinterpret date formats.
Quote every start and end date value in YAML so it remains a string after
parsing. This includes year-only dates such as "2018" and ISO-like dates
such as "2019-06".
What not to do
- Do not fabricate metrics.
- Do not rewrite bullets in a different voice.
- Do not invent links, locations, degrees, employers, dates, or titles the resume does not mention.
- Do not gate-keep thin bullets or sparse resumes.
- Do not include schema fields whose values are unknown.
Output contract
Emit only the YAML, wrapped in these exact markers:
---MASTER YAML---
profile:
name: ...
---END MASTER YAML---
No prose before the opening marker, after the closing marker, or between YAML sections. No Markdown code fences. No commentary.
When not to use it
- →When the task involves rewriting bullets in a different voice.
- →When the task requires fabricating metrics.
- →When the task involves inventing links, locations, degrees, employers, dates, or titles not mentioned in the resume.
Limitations
- →It does not improve, embellish, or restyle thin bullets.
- →It only uses tags from a predefined vocabulary.
- →It does not normalize or reinterpret date formats.
How it compares
This skill converts unstructured resume text into a specific, structured YAML format with predefined fields and ID generation rules, unlike manual data entry which lacks standardization and automation.
Compared to similar skills
resume-importing side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| resume-importing (this skill) | 0 | 2mo | No flags | Intermediate |
| quant-analyst | 103 | 2mo | No flags | Advanced |
| stock-analyzer | 71 | 2mo | Review | Beginner |
| xlsx | 87 | 6mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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