docs: add OSS launch demo assets

README.md

@@ -39,10 +39,21 @@ AdLint currently has three demo-friendly entry points:
 2. **Local Web UI** — paste copy, configure platform/industry/model settings, review findings, and export reports.
 3. **FastAPI** — embed `/analyze` into internal tools or CI workflows.
 
-Suggested screenshot/GIF flow for the public repo:
+![AdLint Web UI review](docs/assets/adlint-ui-review.png)
+
+The demo intentionally uses risky health/weight-loss copy so the review surface
+shows matched evidence, recommended actions, and safer rewrite suggestions.
+Risk scores are heuristic decision-support signals, not compliance guarantees.
+
+Example generated reports:
+
+- [`docs/assets/demo/adlint-report.md`](docs/assets/demo/adlint-report.md)
+- [`docs/assets/demo/adlint-report.json`](docs/assets/demo/adlint-report.json)
+
+Reproduce the CLI demo:
 
 ```bash
-adlint scan examples/high_risk_tiktok_health.json --format markdown
+adlint scan examples/meta_high_risk_health.json --format markdown --output-dir docs/assets/demo
 make api  # then open http://127.0.0.1:8000/ui/
 ```
 
@@ -106,7 +117,7 @@ make dev   # install and run the high-risk example, writing reports/
 make scan  # install and run the wellness example
 make api   # start uvicorn with adlint.api:app
 make eval  # run the seed evals and write evals/results/latest.json
-make benchmark    # run the 209-row synthetic policy regression benchmark
+make benchmark    # run the 213-row synthetic policy regression benchmark
 make policy-coverage           # refresh docs/policy_coverage_matrix.md
 make policy-coverage-validate  # check the committed coverage matrix
 make rewrite-quality # run the deterministic rewrite-quality rubric eval
@@ -473,6 +484,8 @@ High-value contribution areas:
 ## Related docs
 
 - `docs/open_source_goal.md`
+- `docs/release_v0.1.0.md`
+- `docs/announcement_draft.md`
 - `docs/policy_design.md`
 - `docs/meta_ads_scope.md`
 - `docs/legal_disclaimer.md`

adlint/static/index.html

@@ -52,6 +52,7 @@ <h2>Draft ad</h2>
                 <option value="google">Google</option>
                 <option value="tiktok">TikTok</option>
                 <option value="linkedin">LinkedIn</option>
+                <option value="meta">Meta</option>
               </select>
             </label>
 

docs/announcement_draft.md

@@ -0,0 +1,71 @@
+# Announcement draft
+
+## Short post
+
+I open-sourced **AdLint** — a local-first linting tool for ads, landing pages,
+and growth campaigns before they hit platform review.
+
+Think ESLint, but for risky ad claims:
+
+- Flags unsupported health/finance claims, disclosure gaps, platform-policy review triggers, landing-page mismatch, privacy-sensitive tracking, and brand-safety concerns.
+- Runs locally through a CLI, FastAPI service, or small Web UI.
+- Uses transparent YAML policy rules and eval gates instead of black-box compliance theater.
+- Keeps raw ad copy out of storage by default.
+- Includes initial Google, TikTok, LinkedIn, and Meta Ads heuristic modules.
+
+It is not legal advice and it does not guarantee platform approval. The goal is
+simple: give growth teams earlier, explainable feedback before campaign review
+becomes expensive.
+
+Repo: https://github.com/ftchvs/AdLint
+
+## Longer post
+
+Growth teams usually find ad risk late — during platform review, legal review,
+or after a landing page is already collecting traffic.
+
+I wanted a lightweight preflight step that works like developer tooling:
+transparent, local, scriptable, and easy to extend.
+
+So I open-sourced **AdLint**.
+
+AdLint scans draft ad copy and optional landing-page context, then returns:
+
+- `approved`, `needs_review`, or `high_risk`
+- exact matched evidence
+- policy categories and severity
+- recommended actions
+- safer rewrite options
+- JSON/Markdown reports
+
+The project is intentionally local-first. The rule engine is deterministic and
+policy-as-code-first. There is also an optional Ollama-compatible local model
+reviewer, but the baseline does not depend on hosted models.
+
+What is in the first OSS release:
+
+- CLI, API, and Web UI
+- policy YAML files
+- initial platform modules for Google, TikTok, LinkedIn, and Meta Ads
+- privacy/disclosure/landing-page/brand-safety checks
+- seed evals, benchmark evals, real-case fixtures, and policy coverage gates
+
+What it does *not* claim:
+
+- legal advice
+- definitive compliance decisions
+- guaranteed platform approval
+- complete Meta/Google/TikTok/LinkedIn policy parity
+
+If you work on growth, regulated campaigns, creator ads, landing pages, or local
+AI/product tooling, I’d love feedback and contributions.
+
+Repo: https://github.com/ftchvs/AdLint
+
+## Product Hunt / Hacker News style blurb
+
+AdLint is a local-first ad preflight tool for growth teams. It scans draft ad
+copy and landing-page context for risky claims, disclosure gaps, platform-policy
+review triggers, privacy-sensitive tracking, and brand-safety concerns. It ships
+with CLI/API/Web UI workflows, transparent YAML policy rules, eval gates, and an
+optional local AI reviewer.

docs/assets/demo/adlint-report.json

@@ -0,0 +1,118 @@
+{
+  "decision": "high_risk",
+  "enabled_modules": [
+    "brand_safety",
+    "health_claims",
+    "platform",
+    "privacy"
+  ],
+  "landing_page": {
+    "disclaimers": [],
+    "fetch_error": null,
+    "forms": [],
+    "headings": [],
+    "pricing_text": [],
+    "title": null,
+    "tracking_scripts": [],
+    "url": null,
+    "visible_claims": []
+  },
+  "logging_enabled": false,
+  "model": {
+    "enabled": false,
+    "provider": null,
+    "status": "disabled"
+  },
+  "policy_hits": [
+    {
+      "category": "health_claims",
+      "description": "Health or wellness claim likely requiring substantiation.",
+      "evidence": [
+        {
+          "source": "body",
+          "text": "Our clinically proven supplement helps you lose 20 pounds and melts fat."
+        }
+      ],
+      "policy_id": "unsupported_health_claim",
+      "recommended_action": "Remove or qualify the claim and provide substantiation.",
+      "severity": "high"
+    },
+    {
+      "category": "health_claims",
+      "description": "Weight-loss and body-image claims can trigger platform and FTC review.",
+      "evidence": [
+        {
+          "source": "body",
+          "text": "Our clinically proven supplement helps you lose 20 pounds and melts fat."
+        }
+      ],
+      "policy_id": "weight_loss_claim",
+      "recommended_action": "Avoid absolute body or fat-loss language and route for review.",
+      "severity": "high"
+    },
+    {
+      "category": "health_claims",
+      "description": "Before-and-after framing can imply atypical guaranteed results.",
+      "evidence": [
+        {
+          "source": "headline",
+          "text": "Are you overweight? See a before and after transformation"
+        }
+      ],
+      "policy_id": "before_after_claim",
+      "recommended_action": "Add context, substantiation, and typical-results disclosure.",
+      "severity": "medium"
+    },
+    {
+      "category": "platform_policy",
+      "description": "Meta ads should not imply knowledge of a viewer's health, body, or medical condition.",
+      "evidence": [
+        {
+          "source": "headline",
+          "text": "Are you overweight? See a before and after transformation"
+        }
+      ],
+      "policy_id": "meta_personal_attributes_health",
+      "recommended_action": "Reframe the ad around the product or service benefit without implying personal health attributes.",
+      "severity": "high"
+    },
+    {
+      "category": "platform_policy",
+      "description": "Meta health and appearance ads can be rejected for unrealistic results or negative self-perception framing.",
+      "evidence": [
+        {
+          "source": "headline",
+          "text": "Are you overweight? See a before and after transformation"
+        },
+        {
+          "source": "body",
+          "text": "Our clinically proven supplement helps you lose 20 pounds and melts fat."
+        }
+      ],
+      "policy_id": "meta_health_appearance_results",
+      "recommended_action": "Avoid transformation framing and use qualified wellness-support language.",
+      "severity": "high"
+    }
+  ],
+  "recommended_actions": [
+    "Remove or qualify the claim and provide substantiation.",
+    "Avoid absolute body or fat-loss language and route for review.",
+    "Reframe the ad around the product or service benefit without implying personal health attributes.",
+    "Avoid transformation framing and use qualified wellness-support language.",
+    "Add context, substantiation, and typical-results disclosure."
+  ],
+  "requires_review": true,
+  "risk_score": 0.9,
+  "safer_rewrites": [
+    {
+      "body": "Our developed with evidence-informed guidance supplement helps you lose 20 pounds and melts fat. Results vary.",
+      "cta": "Learn more",
+      "headline": "Are you overweight? See a before and after transformation"
+    },
+    {
+      "body": "Designed to complement healthy habits. Individual results vary.",
+      "cta": "Learn more",
+      "headline": "Support your wellness routine with daily nutrition"
+    }
+  ]
+}

docs/assets/demo/adlint-report.md

@@ -0,0 +1,76 @@
+# AdLint Report
+
+- Decision: `high_risk`
+- Risk score: `0.90`
+- Requires review: `true`
+- Model status: `disabled`
+
+## Policy Hits
+
+### unsupported_health_claim
+
+- Severity: `high`
+- Category: `health_claims`
+- Recommended action: Remove or qualify the claim and provide substantiation.
+- Evidence:
+  - `body`: Our clinically proven supplement helps you lose 20 pounds and melts fat.
+
+### weight_loss_claim
+
+- Severity: `high`
+- Category: `health_claims`
+- Recommended action: Avoid absolute body or fat-loss language and route for review.
+- Evidence:
+  - `body`: Our clinically proven supplement helps you lose 20 pounds and melts fat.
+
+### before_after_claim
+
+- Severity: `medium`
+- Category: `health_claims`
+- Recommended action: Add context, substantiation, and typical-results disclosure.
+- Evidence:
+  - `headline`: Are you overweight? See a before and after transformation
+
+### meta_personal_attributes_health
+
+- Severity: `high`
+- Category: `platform_policy`
+- Recommended action: Reframe the ad around the product or service benefit without implying personal health attributes.
+- Evidence:
+  - `headline`: Are you overweight? See a before and after transformation
+
+### meta_health_appearance_results
+
+- Severity: `high`
+- Category: `platform_policy`
+- Recommended action: Avoid transformation framing and use qualified wellness-support language.
+- Evidence:
+  - `headline`: Are you overweight? See a before and after transformation
+  - `body`: Our clinically proven supplement helps you lose 20 pounds and melts fat.
+
+## Recommended Actions
+
+- Remove or qualify the claim and provide substantiation.
+- Avoid absolute body or fat-loss language and route for review.
+- Reframe the ad around the product or service benefit without implying personal health attributes.
+- Avoid transformation framing and use qualified wellness-support language.
+- Add context, substantiation, and typical-results disclosure.
+
+## Safer Rewrites
+
+### Option 1
+
+- Headline: Are you overweight? See a before and after transformation
+- Body: Our developed with evidence-informed guidance supplement helps you lose 20 pounds and melts fat. Results vary.
+- CTA: Learn more
+
+### Option 2
+
+- Headline: Support your wellness routine with daily nutrition
+- Body: Designed to complement healthy habits. Individual results vary.
+- CTA: Learn more
+
+
+## Decision-Support Disclaimer
+
+AdLint is a preflight decision-support tool. It does not provide legal advice, guarantee platform approval, or make definitive statutory violation determinations.

docs/release_v0.1.0.md

@@ -0,0 +1,62 @@
+# AdLint v0.1.0 release notes
+
+AdLint is an open-source, local-first preflight tool for ads, landing pages, and
+growth campaigns before they hit platform review.
+
+Think **ESLint for risky ad claims**: transparent policy-as-code checks,
+evidence-backed findings, safer rewrite suggestions, and eval gates that run
+locally.
+
+## What ships in v0.1.0
+
+- **CLI preflight**: scan JSON/YAML campaign configs and export JSON or Markdown reports.
+- **Local API + Web UI**: paste ad copy, choose platform/industry/modules, and review findings locally.
+- **Policy-as-code**: inspectable YAML rules for health claims, platform policies, privacy, disclosure, landing-page mismatch, and brand safety.
+- **Platform modules**: initial Google, TikTok, LinkedIn, and Meta Ads heuristic coverage.
+- **Evidence-based output**: every finding includes matched copy, severity, category, and a recommended action.
+- **Safer rewrites**: deterministic rewrite suggestions for common high-risk or review-required findings.
+- **Local-first posture**: no default raw ad persistence; optional run logging/storage are opt-in.
+- **Eval gates**: seed evals, benchmark evals, real-case fixtures, policy coverage validation, and PR preflight checks.
+- **Optional local AI reviewer**: Ollama-compatible model review can add decision-support metadata, but deterministic rules remain the trusted baseline.
+
+## Demo
+
+![AdLint Web UI review](assets/adlint-ui-review.png)
+
+The screenshot intentionally uses risky health/weight-loss copy so the review
+surface shows policy hits, evidence, and rewrite suggestions. Risk scores are
+heuristic decision-support signals, not statistical compliance probabilities.
+
+Example report output is available at:
+
+- `docs/assets/demo/adlint-report.md`
+- `docs/assets/demo/adlint-report.json`
+
+## Honest scope
+
+AdLint is decision-support software. It does **not** provide legal advice,
+guarantee platform approval, or make definitive statutory determinations.
+
+The Meta Ads module is intentionally framed as **initial heuristic coverage**,
+not full Meta policy parity. See `docs/meta_ads_scope.md` for source references,
+coverage notes, and non-goals.
+
+## Good first contributions
+
+- Add public-source/paraphrased eval cases.
+- Add policy rules with positive and near-miss examples.
+- Improve the optional local AI reviewer and measure whether it adds signal or noise.
+- Add demo assets, docs, and first-run workflow polish.
+
+## Launch positioning
+
+Suggested announcement line:
+
+> I open-sourced AdLint: a local-first linting tool for ads, landing pages, and
+growth campaigns before they hit platform review.
+
+Hooks:
+
+- Runs locally; no ad copy leaves your machine by default.
+- Policy-as-code + evals, not black-box compliance theater.
+- CLI/API/Web UI for growth teams that want preflight feedback before launch.

tests/test_ui_static.py

@@ -153,3 +153,7 @@ def test_geist_style_system_font_and_restrained_surfaces_are_preserved() -> None
     assert "line-height: 0.98;" in STYLES_CSS
     assert ".primary-button," in STYLES_CSS
     assert "border-radius: 5px;" in STYLES_CSS
+
+
+def test_platform_select_includes_meta_ads() -> None:
+    assert '<option value="meta">Meta</option>' in INDEX_HTML