# Niw Case Builder

> NIW Case Builder

- Skill: `kateaiuser/niw-case-builder` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add kateaiuser/niw-case-builder`
- Raw SKILL.md: https://api.skillmd.com/api/skills/kateaiuser/niw-case-builder/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: kateaiuser (https://skillmd.com/u/kateaiuser)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/kateaiuser/niw-case-builder

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# NIW Case Builder

Use this skill after `niw-officer-review` or whenever the user wants to turn a weak or messy case into a tighter one.
This is an educational drafting workflow, not legal advice.

## Goal

Build a case that is:

- narrower;
- easier to prove;
- less emotionally noisy;
- more legible under `Dhanasar`;
- less dependent on unsupported claims.

## Build sequence

### 1. Choose one anchor endeavor

Do not let the case split into multiple companies, missions, or populations unless the user already has unusually strong evidence across all of them.

Prefer one anchor endeavor that best satisfies all three:

- strongest national-importance framing;
- strongest execution proof;
- strongest reason to waive the job offer and labor certification.

### 2. Write the endeavor statement

Use this format:

`The petitioner seeks to advance a U.S.-based endeavor focused on [specific intervention], addressing [specific national problem or system-level gap] by [method], with expected impact on [defined public, industry, or regional outcome].`

Avoid:

- visionary language;
- self-brand language;
- broad platform language;
- claims that sound like a mission statement.

### 3. Build the evidence chain

Map every claim to proof.

Use four buckets:

- `problem evidence`: data, reports, burden, shortage, cost, access gap;
- `execution evidence`: history, product, clients, pilots, grants, publications, patents, partnerships;
- `outside validation`: expert letters, customer letters, media, awards, accelerators, agencies, adoption;
- `waiver logic`: why this work should not be trapped inside one employer relationship.

If a claim has no proof, either weaken it or remove it.

### 4. Reframe founder stories

Founder stories should sound like public-benefit execution stories, not personal journeys.

Translate:

- from `I care deeply about this issue`
- to `I have built a specific mechanism to address a documented U.S. gap.`

Translate:

- from `my company will succeed`
- to `the proposed endeavor is already being advanced through identifiable steps with outside validation.`

### 5. Draft support letters correctly

Support letters should do at least one of these:

- validate the national problem;
- validate the petitioner’s role and capability;
- validate demand, adoption, or implementation value;
- explain why the work has broader implications beyond one employer.

Letters that only praise intelligence or work ethic are low value.

## Output format

Default to:

### Reframed case thesis

One paragraph.

### Proposed endeavor

One polished paragraph.

### Evidence map

- `Prong 1`:
- `Prong 2`:
- `Prong 3`:

### Claims to cut

List claims that should be removed or softened.

### Evidence to obtain next

Prioritize the highest-value missing pieces.

### Drafting notes

State what tone and logic the full petition should follow.

## Sector lenses

### Women’s health / hormonal health

Prefer frames tied to:

- access to care;
- diagnostic delay;
- patient navigation;
- underserved populations;
- reproductive, endocrine, menopausal, or chronic-condition burden;
- measurable public-health or healthcare-delivery impact.

Be careful with:

- wellness-only positioning;
- consumer-brand language;
- generalized empowerment messaging without clinical or system-level evidence.

### Conservation / environmental work

Prefer frames tied to:

- measurable ecological or resilience outcomes;
- public infrastructure, land, water, agriculture, compliance, monitoring, or risk reduction;
- scalable implementation rather than local volunteering.

Be careful with:

- passion-project framing;
- local-only restoration narratives;
- impact claims without policy, data, or deployment pathway.

### AI / deep tech

Prefer frames tied to:

- a specific deployed capability with named users, pilots, or integrations;
- national priorities such as critical technology, security, infrastructure, or competitiveness;
- measurable adoption, performance, or cost outcomes.

Be careful with:

- "AI" as a buzzword without a working system behind it;
- hype language borrowed from fundraising decks;
- national-importance claims that rest on the industry’s importance alone.

## References

Read these only when needed:

- [USCIS and AAO criteria](references/uscis_and_aao.md)
- [Drafting red flags](references/drafting_red_flags.md)