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.
npx skills add iterationlayer/skills --skill extract-resume-and-generate-profilegit clone --depth 1 https://github.com/iterationlayer/skillsWrote 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.
[](https://agentmods.dev/skills/iterationlayer/skills/extract-resume-and-generate-profile)<a href="https://agentmods.dev/skills/iterationlayer/skills/extract-resume-and-generate-profile"><img src="https://agentmods.dev/badge/skills/iterationlayer/skills/extract-resume-and-generate-profile/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.
<a href="https://agentmods.dev/skills/iterationlayer/skills/extract-resume-and-generate-profile"><img src="https://agentmods.dev/badge/skills/iterationlayer/skills/extract-resume-and-generate-profile.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00027 | $0.05232 |
| Opus 5 | $0.00014 | $0.02616 |
| Sonnet 5 | $0.00005 | $0.01046 |
| Haiku 4.5 | $0.00003 | $0.00523 |
Grade A, and why
extract-resume-and-generate-profile scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
EXTRACTION=$(curl -s -X POST https://api.iterationlayer.com/document-extraction/v1/extract \ This is a copy
88% identical to extract-product-data-and-generate-listing-image — 712 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 631 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Extract Resume Data and Generate an Employee Profile
Staffing agencies and HR departments use this pipeline to accelerate onboarding — extracting key details from a candidate's resume and generating a standardized employee profile document ready for internal systems.
APIs Used
Document Extraction (1 credit per page), Document Generation (1 credits/request)
Prerequisites
You need an Iteration Layer API key. Get one at platform.iterationlayer.com during the 7-day trial.
For full integration guidance (SDKs, auth, MCP, error handling), see the Iteration Layer Integration Guide.
Implementation
# Step 1: Extract resume data
EXTRACTION=$(curl -s -X POST https://api.iterationlayer.com/document-extraction/v1/extract \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"files": [
{
"type": "url",
"name": "resume-elena-vasquez.pdf",
"url": "https://example.com/resumes/elena-vasquez-2026.pdf"
}
],
"schema": {
"fields": [
{
"name": "full_name",
"type": "TEXT",
"description": "Candidate full name"
},
{
"name": "email",
"type": "EMAIL",
"description": "Email address"
},
{
"name": "phone",
"type": "TEXT",
"description": "Phone number"
},
{
"name": "address",
"type": "ADDRESS",
"description": "Home address"
},
{
"name": "job_title",
"type": "TEXT",
"description": "Most recent job title"
},
{
"name": "employer",
"type": "TEXT",
"description": "Most recent employer"
},
{
"name": "years_of_experience",
"type": "INTEGER",
"description": "Total years of professional experience"
},
{
"name": "education",
"type": "TEXT",
"description": "Highest degree and institution"
},
{
"name": "skills",
"type": "TEXTAREA",
"description": "Key skills listed on the resume"
}
]
}
}')
# Step 2: Generate an employee profile document
curl -X POST https://api.iterationlayer.com/document-generation/v1/generate \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"format": "pdf",
"document": {
"metadata": {
"title": "Employee Profile — Elena Vasquez",
"author": "Apex Staffing Solutions"
},
"page": {
"size": {
"preset": "A4"
},
"margins": {
"top_in_pt": 54,
"right_in_pt": 54,
"bottom_in_pt": 54,
"left_in_pt": 54
}
},
"content": [
{
"type": "headline",
"level": "h1",
"text": "Employee Profile"
},
{
"type": "headline",
"level": "h2",
"text": "Elena Vasquez"
},
{
"type": "separator"
},
{
"type": "table",
"header": {
"cells": [
{
"text": "Field"
},
{
"text": "Details"
}
]
},
"rows": [
{
"cells": [
{
"text": "Email"
},
{
"text": "[email protected]"
}
]
},
{
"cells": [
{
"text": "Phone"
},
{
"text": "+1 (512) 555-0198"
}
]
},
{
"cells": [
{
"text": "Address"
},
{
"text": "814 Congress Ave, Austin, TX 78701"
}
]
},
{
"cells": [
{
"text": "Current Title"
},
{
"text": "Senior Product Manager"
}
]
},
{
"cells": [
{
"text": "Current Employer"
},
{
"text": "NovaTech Solutions"
}
]
},
{
"cells": [
{
"text": "Experience"
},
{
"text": "8 years"
}
]
},
{
"cells": [
{
"text": "Education"
},
{
"text": "MBA, University of Texas at Austin"
}
]
}
]
},
{
"type": "separator"
},
{
"type": "headline",
"level": "h3",
"text": "Key Skills"
},
{
"type": "paragraph",
"runs": [
{
"text": "Product roadmap planning, Agile/Scrum methodology, cross-functional team leadership, data-driven decision making, user research, A/B testing, SQL, stakeholder management"
}
]
},
{
"type": "separator"
},
{
"type": "paragraph",
"runs": [
{
"text": "Prepared by Apex Staffing Solutions — Confidential"
}
]
}
]
}
}'
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.
- 7d ago First seen · 631 lines · 27 tokens per session scan A dbf70c071a33
extract-resume-and-generate-profile is a skill published in the GitHub repository iterationlayer/skills (3 stars, last pushed 3mo ago), licensed MIT. It adds 27 tokens to every session and 5,232 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 88% identical to extract-product-data-and-generate-listing-image, differing in 712 lines, and is treated as a copy.
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