import pytest from autoshorts.strategy.spine_v2 import ( AIDisclosureDecision, AudienceNeed, ClaimRisk, ContentBriefV2, ExperimentHypothesis, HumanTexture, ReviewPackageV2, SaturationRisk, SeriesRegistry, StrategyScoreV2, VideoCandidateV2, ViewerEmotion, build_demo_candidates_v2, build_review_package_v2, render_review_package_v2, validate_candidate_v2, validate_review_package_v2, ) def make_hypothesis() -> ExperimentHypothesis: return ExperimentHypothesis( statement="Tests whether visible decision-target fixes drive saves.", expected_winning_metric="saves_per_view", ) def make_brief(**overrides) -> ContentBriefV2: data = dict( brief_id="decision-summary-brief", series_id="decision_design", topic="AI summaries without a decision target", audience_need=AudienceNeed.CLARITY, job_to_be_done="When I review a meeting, I want decision evidence, so I can choose the next action.", viewer_identity="office_worker", emotion_before=ViewerEmotion.CONFUSED, emotion_after=ViewerEmotion.IN_CONTROL, audience_problem="AI summaries hide the one decision that matters.", payoff="Add a decision target before asking for the summary.", search_intent_phrase="better meeting summary prompt", saturation_risk=SaturationRisk.MEDIUM, human_texture=HumanTexture.MINI_CASE, claim_risk=ClaimRisk.LOW, ai_disclosure_required=AIDisclosureDecision.NO, experiment_hypothesis=make_hypothesis(), platforms=("youtube", "tiktok", "instagram"), target_duration_seconds=38, ) data.update(overrides) return ContentBriefV2(**data) def make_candidate(**overrides) -> VideoCandidateV2: data = dict( candidate_id="decision-design-summary-target-38s", version="v2.0.0", title="Your AI summary has no decision target", series_id="decision_design", platforms=("youtube", "tiktok", "instagram"), duration_seconds=38, audience_need=AudienceNeed.CLARITY, job_to_be_done="When I review a meeting, I want decision evidence, so I can choose the next action.", viewer_identity="office_worker", emotion_before=ViewerEmotion.CONFUSED, emotion_after=ViewerEmotion.IN_CONTROL, hook="Your AI summary is useless because it has no decision target.", first_frame="Split-screen: 47-minute transcript vs. useless AI summary stamped USELESS.", visible_fail="The AI summary says 'great discussion' but misses the launch decision.", mechanism="Without a decision target, AI compresses every sentence equally.", fix="Before summarizing, state the decision and ask for blockers, owners, risks, and next steps.", before_after="Before: generic summary. After: decision evidence with risks and owner.", takeaway="Don't ask for a summary. Ask for decision evidence.", save_reason="Viewer can copy the decision-target sentence into the next meeting summary prompt.", share_reason="Every office worker has seen useless meeting summaries.", follow_reason="Follow for small systems that stop digital work from wasting your life.", search_intent_phrase="better meeting summary prompt", saturation_risk=SaturationRisk.MEDIUM, human_texture=HumanTexture.MINI_CASE, claim_risk=ClaimRisk.LOW, claims=("AI summaries need a decision target to preserve relevance.",), ai_disclosure_required=AIDisclosureDecision.NO, experiment_hypothesis=make_hypothesis(), expected_winning_metric="saves_per_view", platform_fit={"youtube": "strong", "tiktok": "strong", "instagram": "medium"}, risks=("medium saturation",), visual_structure="motion-led mechanism funnel with transcript cards, not slideshow/text cards", anti_example="A useless AI summary with no decision target.", human_texture_note="messy meeting transcript with launch decision", ) data.update(overrides) return VideoCandidateV2(**data) def test_content_brief_v2_requires_strategic_spine_fields(): brief = make_brief(series_id="", save_reason="") if False else None with pytest.raises(TypeError): ContentBriefV2(brief_id="missing-required") invalid = make_candidate(save_reason="") result = validate_candidate_v2(invalid) assert not result.is_valid assert "save_reason is required" in result.errors def test_quality_gates_block_missing_mechanism_and_first_frame_conflict(): candidate = make_candidate(mechanism="", first_frame="Plain title card with text only") result = validate_candidate_v2(candidate) assert not result.is_valid assert "mechanism is required" in result.errors assert "visible first-frame conflict is required" in result.errors assert "candidate is not renderable until all hard gates pass" in result.errors def test_anti_ai_slop_blocks_generic_hooks_and_slideshow_structure(): candidate = make_candidate( title="Top 5 AI Tools That Will Change Your Life", hook="Nobody talks about this AI tool will change your life.", visual_structure="pure slideshow with text cards and generic AI background", human_texture=HumanTexture.NONE, ) result = validate_candidate_v2(candidate) assert not result.is_valid assert "generic AI-slop hook/title detected" in result.errors assert "videos without concrete human texture are blocked" in result.errors assert "pure slideshow/text-card structure is blocked" in result.errors def test_strategy_score_v2_uses_100_point_model_and_blocks_low_scores(): candidate = make_candidate() score = StrategyScoreV2.from_candidate(candidate) assert 75 <= score.total <= 93 assert score.render_allowed assert score.problem_urgency == 13 assert score.practical_payoff == 13 weak = StrategyScoreV2.from_candidate(make_candidate(save_reason="", share_reason="", follow_reason="")) assert weak.total < 80 assert not weak.render_allowed assert "share/save/follow potential below threshold" in weak.reject_reasons def test_series_registry_accepts_new_series_and_rejects_unknown(): registry = SeriesRegistry.default() assert registry.validate_series_id("digital_red_flags").is_valid assert registry.get("attention_traps").name == "Attention Traps" assert not registry.validate_series_id("top_ai_tools").is_valid def test_review_package_v2_contains_hashes_strategy_risk_and_approval_command(): candidate = make_candidate(media_hash="abc123") package = build_review_package_v2(candidate) validation = validate_review_package_v2(package) text = render_review_package_v2(package) assert validation.is_valid assert isinstance(package, ReviewPackageV2) assert package.script_hash assert package.media_hash == "abc123" assert "Candidate ID: decision-design-summary-target-38s" in text assert "Series: Decision Design" in text assert "Visible Fail:" in text assert "AI Disclosure: no" in text assert "Experiment Hypothesis:" in text assert "APPROVE decision-design-summary-target-38s v2.0.0" in text def test_approval_command_is_version_and_hash_bound(): package = build_review_package_v2(make_candidate()) command = package.approval_command assert command.startswith("APPROVE decision-design-summary-target-38s v2.0.0 ") assert package.script_hash in command def test_build_demo_candidates_v2_returns_one_candidate_per_requested_series(): candidates = build_demo_candidates_v2() assert [candidate.series_id for candidate in candidates] == [ "ai_output_autopsy", "digital_red_flags", "workflow_teardown", "decision_design", "attention_traps", ] assert all(validate_candidate_v2(candidate).is_valid for candidate in candidates) assert all(StrategyScoreV2.from_candidate(candidate).render_allowed for candidate in candidates)