claims-search▌
aivaclaims.com/claims-search-39p4hf · updated May 21, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Search AIVA Claims Assistant's public 22-entry FAQ knowledge base for VA-disability-claim service info (eligibility, pricing, process, AI-model vendor, accreditation). Returns matching Q&A pairs by category. Read-only; no sign-in.
| name | claims-search |
| title | AIVA Claims Knowledge Base Search |
| description | >- Search AIVA Claims Assistant's public 22-entry FAQ knowledge base for VA-disability-claim service info (eligibility, pricing, process, AI-model vendor, accreditation). Returns matching Q&A pairs by category. Read-only; no sign-in. |
| website | aivaclaims.com |
| category | veterans-services |
| tags | - veterans - va-claims - faq-search - knowledge-base - disability - aiva |
| source | 'browserbase: agent-runtime 2026-05-18' |
| updated | '2026-05-18' |
| recommended_method | browser |
| alternative_methods | - method: api rationale: >- No public REST/JSON API for FAQ content. The only `/api/*` route discovered (POST /api/benefits/search, the Benefits Finder backend) is auth-walled and returns 401 'Unauthorized: No token provided' to anonymous requests. Do not attempt — confirmed blocked. - method: url-param rationale: >- No deep-link query parameter on /faq pre-filters or scrolls to a Q&A. Navigation is entirely client-side React state. - method: hybrid rationale: >- The optimal browser flow is itself a hybrid: drive a session, wait for React to mount, then extract the FAQPage JSON-LD blob in one eval rather than driving the on-page searchbox. Listed as 'browser' since a real session is required to render the JSON-LD, but the actual extraction is structured-data parsing, not DOM walking. |
| verified | true |
| proxies | true |
AIVA Claims Knowledge Base Search
Purpose
Search the public AIVA Claims Assistant knowledge base for information about U.S. VA disability claim preparation, the AIVA service process, pricing, eligibility, and operational details. Returns matching question/answer pairs from a curated 22-entry FAQ knowledge base organized into four categories: Getting Started, Claims Process, Pricing & Payment, Technical Support. Read-only, no sign-in required, no claim is filed.
This skill does not cover personalized federal/state/local benefit eligibility lookups — that surface exists (/benefits-finder) but its backend (POST /api/benefits/search) requires a Clerk session and returns 401 Unauthorized: No token provided to anonymous clients. Don't waste cycles on it. See gotchas.
When to Use
- A veteran or caregiver asks "what does AIVA do?", "how much does it cost?", "is AIVA a law firm?", "what about appeals?" — any general-policy / how-the-service-works question.
- The user wants pre-purchase due-diligence facts: pricing model, payment timing, security practices, AI-model vendor, accreditation status.
- The user wants quick procedural pointers ("how do I get my VA medical records?", "what is an Intent to File?") and is willing to be routed to AIVA's plain-English summaries rather than VA.gov primary sources.
- The user is comparison-shopping between AIVA, VSOs, and law firms and wants AIVA's stated positioning on backpay percentages and flat fees.
Do NOT use this skill for:
- Personalized benefit eligibility lookup by ZIP + disability rating — requires a Clerk-authenticated session this skill does not provide.
- Authoritative VA regulation / rate-table data — those live at
va.gov. AIVA's FAQ summarizes; it is not the source of truth. - Anything that involves uploading medical records, generating draft documents, signing forms, or submitting claims — all gated behind sign-in at
clerk.aivaclaims.comand out of scope.
Workflow
The FAQ knowledge base is delivered as a React SPA — a raw HTTP fetch of /faq returns only the SSR shell with two unrelated JSON-LD blocks (Organization, WebApplication) and no FAQ content. The full Q&A catalog is injected into the DOM after React mounts as a <script type="application/ld+json"> block of @type: FAQPage. So a browser session is required, but once it is running you have two equivalent paths — the JSON-LD extract is strictly faster and more reliable than driving the searchbox.
-
Open the FAQ page in a browser session (Cloudflare-fronted but bare-friendly for read-only — stealth/proxies are optional, not required).
sid=$(browse cloud sessions create --keep-alive | jq -r .id) export BROWSE_SESSION="$sid" browse open "https://aivaclaims.com/faq" --remote -
Wait ~2-3 seconds for React to mount and inject the
FAQPageJSON-LD block. Confirm with a snapshot or by checking thatscript[type="application/ld+json"]count is 4 (Organization, WebApplication, BreadcrumbList, FAQPage). -
Optimal — extract the full knowledge base in one call via JSON-LD and match locally against the user's query. This avoids any DOM-state mutation and gives you the complete catalog:
browse eval "JSON.parse(Array.from(document.querySelectorAll('script[type=\"application/ld+json\"]')).find(s => s.textContent.includes('FAQPage')).textContent)" --remoteThe result is a
FAQPageobject withmainEntity: [{ '@type': 'Question', name, acceptedAnswer: { '@type': 'Answer', text } }, ...]— 22 entries. Note: the JSON-LD does not contain category labels. If you need the category for each entry (Getting Started / Claims Process / Pricing & Payment / Technical Support), read it from the DOM (each<section>element has the category as its<h2>), or use Workflow step 4b which shows category inline. -
Match the user's query against the 22 entries locally (substring or fuzzy match against
name+acceptedAnswer.text). Return up to N best matches with question, answer, and source URLhttps://aivaclaims.com/faq.
Alternative — drive the on-page searchbox (no API call)
Useful when you want the site's own ranking signal or you want a screenshot of the filter UI for evidence. Note: the filter is client-side only — no network request is made. Output is just a re-rendered DOM subset.
# After step 1+2 above:
browse snapshot --remote # find the searchbox ref (look for "searchbox: Search frequently asked questions")
browse fill "@<ref>" "intent to file" --remote
sleep 1
# Re-snapshot — visible rows are now "{Question text} ({Category})" with the answer in an adjacent region.
The filter matches across both question and answer text, and the question label is augmented with the category in parentheses, e.g. "How do I get started with AIVA? (Getting Started)" — which is the easiest way to recover category data without re-walking sections.
Site-Specific Gotchas
-
/benefits-finderAPI is auth-walled — confirmed blocked. The form onhttps://aivaclaims.com/benefits-finderacceptslocationanddisabilityRatinginputs unauthenticated, fetches a CSRF token fromGET /api/csrf-token(200 OK, even anonymously), then submitsPOST /api/benefits/searchwith body{"location":"...","disabilityRating":N}andX-CSRF-Tokenheader. The response is401 {"error":"Unauthorized: No token provided"}because a Clerk session bearer is also required. The user sees a red "We couldn't complete your search / Unauthorized: No token provided" banner. Do not attempt to bypass. If a user asks for personalized benefits lookup, return a clear "requires sign-in at aivaclaims.com" message; don't pretend to deliver results. -
Rate-limit on
/api/*:x-ratelimit-limit: 100per window (the reset header indicates ~60s rolling). Even failed 401 requests count against the budget. Don't loop on the benefits endpoint. -
FAQPageJSON-LD is client-rendered, not in the SSR shell. Acurl/browse cloud fetchof/faqwill return ~14.9 KB of HTML with onlyOrganizationandWebApplicationJSON-LD — no Q&A. You must drive a real browser and wait for React to mount before extracting. -
JSON-LD lacks category labels. The
FAQPage.mainEntity[]entries only carrynameandacceptedAnswer.text. To attach a category (one of Getting Started, Claims Process, Pricing & Payment, Technical Support), either (a) read the rendered DOM where each<section>groups questions under an<h2>, or (b) use the on-page searchbox — its filtered output formats questions as"<question> (<category>)". -
Knowledge base is small and curated (22 entries) — not a full claim-condition catalog. This skill cannot answer "is my hypertension service-connected?" or "what conditions are presumptive under PACT?" — those are VA regulatory questions that AIVA's marketing FAQ does not cover. Route those to VA.gov or to a VA-accredited representative.
-
Cookie consent overlay (
region: Privacy preferenceswith "Accept optional / Reject optional / Customize") appears on first visit per session and overlays the form on/benefits-finder. On/faqit does not obstruct the searchbox, so for the recommended FAQ workflow it can be ignored. If you do need to dismiss it (e.g. for a clean screenshot), the "Reject optional" button is the privacy-respecting choice — chat widget still loads regardless. -
Brevo live-chat iframe loads unconditionally on every page (treated as strictly necessary). It appears as a green chat bubble in the bottom-right of screenshots and occupies its own iframe in the snapshot tree. It does not interfere with the FAQ extraction but will show in marketplace card images.
-
Site supports Spanish via an English/Spanish toggle in the header (button
English Toggle language menu). TheFAQPageJSON-LD reflects whichever locale is active, so if you switch languages mid-session, your extracted Q&A text will swap. The default is English. -
/adminand/dashboard/sign*are disallowed byrobots.txtand are the authenticated app surface. Stay out — they require Clerk session and represent a private-user-data boundary. -
Cloudflare-fronted with no observed bot challenges for read-only navigation during testing. Stealth (
--verified --proxies) is overkill for this skill; a plainbrowse cloud sessions create --keep-aliveis sufficient. Verified + proxies were tested and also work; choose based on cost/budget. -
The site is a marketing-and-onboarding surface for a paid SaaS service, not a government tool. AIVA is not affiliated with the U.S. Department of Veterans Affairs and not a VA-accredited claims agent or law firm (their own legal disclaimer states this prominently on
/services/disability-claims). Any claim-result data returned from this skill should be framed as "AIVA's stated process / pricing," not as authoritative VA policy.
Expected Output
A successful query returns an array of matched FAQ entries, plus a small envelope describing the query and source. The 22-entry catalog is the universe; results are a subset.
{
"query": "intent to file",
"match_count": 2,
"matches": [
{
"question": "How do I get started with AIVA?",
"category": "Getting Started",
"answer": "First, file your Intent to File on VA.gov to protect your effective date. Then, download your VA medical records from My HealtheVet and upload them to AIVA. AIVA's AI will analyze your records and generate draft claim documents within 24 hours for YOUR review, editing, and submission."
},
{
"question": "What is an Intent to File and why do I need it?",
"category": "Claims Process",
"answer": "An Intent to File (VA Form 21-0966) protects your potential effective date for up to one year. This means if you file your intent today and submit your complete claim later, your benefits will be backdated to your intent filing date - potentially worth thousands of dollars in backpay."
}
],
"source_url": "https://aivaclaims.com/faq",
"knowledge_base_size": 22,
"categories": ["Getting Started", "Claims Process", "Pricing & Payment", "Technical Support"],
"method": "json-ld-extract"
}
For a query that does not match any FAQ entry:
{
"query": "agent orange presumptive conditions",
"match_count": 0,
"matches": [],
"source_url": "https://aivaclaims.com/faq",
"knowledge_base_size": 22,
"note": "No matches in AIVA's 22-entry FAQ. AIVA's knowledge base covers service-process and pricing topics, not VA regulatory content. Route this query to va.gov or a VA-accredited representative."
}
For a query that the user clearly meant as a personalized eligibility lookup (mentions a ZIP code, location, or rating percentage in a way that maps to the Benefits Finder surface), return the auth-wall outcome instead of attempting to drive /benefits-finder:
{
"query_type": "personalized_benefits_lookup",
"status": "auth_required",
"form_url": "https://aivaclaims.com/benefits-finder",
"error": "The Benefits Finder backend (POST /api/benefits/search) requires a Clerk session token and returns 401 'Unauthorized: No token provided' to anonymous requests. Personalized federal/state/local benefit recommendations are gated behind sign-in.",
"user_action_required": "Sign in at https://aivaclaims.com (Clerk auth) and submit the form interactively.",
"fallback": "For general information about AIVA's claim-preparation service, this skill's FAQ search remains available."
}
How to use claims-search on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add claims-search
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches claims-search from GitHub repository aivaclaims.com/claims-search-39p4hf and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate claims-search. Access the skill through slash commands (e.g., /claims-search) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★56 reviews- ★★★★★Sofia Srinivasan· Dec 28, 2024
claims-search has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Aditi Bansal· Dec 20, 2024
Registry listing for claims-search matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Aarav Menon· Dec 12, 2024
We added claims-search from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Noah Martinez· Dec 12, 2024
claims-search fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Fatima Wang· Nov 27, 2024
Solid pick for teams standardizing on skills: claims-search is focused, and the summary matches what you get after install.
- ★★★★★Mateo Dixit· Nov 19, 2024
claims-search fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Mateo Ghosh· Nov 3, 2024
claims-search has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Sofia Singh· Oct 22, 2024
Solid pick for teams standardizing on skills: claims-search is focused, and the summary matches what you get after install.
- ★★★★★Aditi Jain· Oct 18, 2024
claims-search has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Noah Robinson· Oct 10, 2024
We added claims-search from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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