feat(hands): improve 6 lower-scoring hands — system prompts and SKILL.md depth
- browser: 5→7 phases, SPA detection, error recovery decision tree, 3 new settings - strategist: framework integration methodology, 7 anti-patterns, uncertainty quantification - lead: remove clip language, add BANT/MEDDIC qualification, 3 new settings + CRM export - researcher: CRAAP→CRAAP+, 7-step conflict resolution, 6-item cognitive bias audit - collector: concrete change classification (structural/content/metadata), 5-factor scoring, 2 new settings - apitester: OWASP Top 10 checklist, 4 load test profiles, contract testing phase, GraphQL/Webhook patterns
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@@ -182,6 +182,60 @@ description = "Analyze and track sentiment trends over time"
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setting_type = "toggle"
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default = "false"
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[[settings]]
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key = "source_reliability_threshold"
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label = "Source Reliability Threshold"
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description = "Minimum source tier required to include a data point (lower tiers are discarded unless they are the sole source for a structural change)"
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setting_type = "select"
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default = "tier_3"
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[[settings.options]]
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value = "tier_1"
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label = "Tier 1 only (official/primary sources)"
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[[settings.options]]
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value = "tier_2"
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label = "Tier 2+ (institutional and above)"
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[[settings.options]]
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value = "tier_3"
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label = "Tier 3+ (professional and above)"
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[[settings.options]]
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value = "tier_4"
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label = "Tier 4+ (community and above)"
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[[settings.options]]
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value = "tier_5"
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label = "All sources (no filtering)"
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[[settings]]
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key = "change_significance_threshold"
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label = "Change Significance Threshold"
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description = "Minimum significance score (0-100) for a change to be classified as IMPORTANT. Changes below this threshold are classified as MINOR."
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setting_type = "select"
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default = "60"
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[[settings.options]]
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value = "40"
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label = "40 (more sensitive — more alerts)"
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[[settings.options]]
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value = "50"
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label = "50 (balanced)"
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[[settings.options]]
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value = "60"
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label = "60 (default)"
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[[settings.options]]
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value = "70"
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label = "70 (stricter — fewer alerts)"
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[[settings.options]]
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value = "80"
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label = "80 (very strict — only critical-level)"
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# ─── Agent configuration ─────────────────────────────────────────────────────
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[agent]
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@@ -288,23 +342,40 @@ Relation types:
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Compare current collection against previous state:
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1. Load `collector_knowledge_base.json` (previous snapshot)
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2. Identify CHANGES:
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- New entities not in previous snapshot
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- Changed attributes (e.g., person changed company, new funding round)
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- New relationships between known entities
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- Disappeared entities (no longer mentioned)
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3. Score each change by significance (critical/important/minor):
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- Critical: leadership change, acquisition, major funding, product launch
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- Important: new partnership, hiring surge, pricing change, competitor move
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- Minor: blog post, minor update, mention in article
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2. Classify each difference into one of three change categories:
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- **Structural change**: entity appeared/disappeared, relationship added/removed, organizational restructure (e.g., new subsidiary, person left company, product deprecated)
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- **Content change**: attribute value updated on an existing entity (e.g., funding amount increased, role title changed, version number bumped, pricing modified)
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- **Metadata change**: source count changed, confidence level shifted, last_seen timestamp updated, but the core fact is unchanged
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If `alert_on_changes` is enabled and critical changes found:
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- event_publish with change summary
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3. Deduplicate cross-source overlaps before scoring:
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- Normalize entity names (strip legal suffixes, lowercase, expand abbreviations)
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- If 2+ sources report the same fact about the same entity, merge into one data point with the highest confidence and list all source URLs
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- If sources conflict on a fact (e.g., different funding amounts), keep both entries and flag as "conflicting — requires resolution"
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4. Compute a significance score (0-100) for each change using this algorithm:
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- **Base score by category**: structural = 60, content = 40, metadata = 5
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- **Source reliability modifier**: Tier 1 (official/primary) = +20, Tier 2 (institutional) = +10, Tier 3 (professional) = +5, Tier 4-5 = +0
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- **Source freshness modifier**: published within 24h = +10, within 7d = +5, older than 30d = -10
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- **Corroboration modifier**: confirmed by 2+ independent sources = +10, single source only = +0, contradicted by another source = -15
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- **Focus area relevance**: change directly matches `focus_area` = +10, tangentially related = +0
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- Cap final score at 100, floor at 0
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5. Map significance score to alert tier using `change_significance_threshold` (default 60):
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- Score >= 80: CRITICAL — leadership change, acquisition, major funding (>$10M), product discontinuation, regulatory action
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- Score >= threshold (default 60): IMPORTANT — new product launch, partnership, hiring surge (>5 roles), pricing change, significant competitor move
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- Score < threshold: MINOR — blog post, minor update, conference mention, individual job posting
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6. Filter sources by `source_reliability_threshold` (default "tier_3"):
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- Discard data points where ALL supporting sources fall below the configured threshold tier
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- Exception: if a below-threshold source is the ONLY source for a structural change, keep it but downgrade confidence to "low" and flag for corroboration in the next cycle
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If `alert_on_changes` is enabled and any change scores CRITICAL:
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- event_publish with change summary including: entity name, change category, significance score, top source URL
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If `track_sentiment` is enabled:
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- Classify each source as positive/negative/neutral toward the target
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- Track sentiment trend vs previous cycle
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- Note significant sentiment shifts in the report
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- Note significant sentiment shifts (score delta > 2 in one cycle) in the report
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---
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@@ -435,6 +506,14 @@ description = "每次采集扫描处理的最大来源数量"
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label = "情感追踪"
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description = "分析并追踪随时间变化的情感趋势"
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[i18n.zh.settings.source_reliability_threshold]
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label = "来源可靠性阈值"
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description = "纳入数据点所需的最低来源等级（低于阈值的来源将被丢弃，除非它是某一结构性变更的唯一来源）"
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[i18n.zh.settings.change_significance_threshold]
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label = "变更显著性阈值"
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description = "变更被归类为「重要」的最低显著性分数（0-100），低于此阈值的变更归类为「次要」"
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# ─── Japanese (日本語) ────────────────────────────────────────────────────
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[i18n.ja]
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@@ -474,6 +553,14 @@ description = "各収集スキャンで処理するソースの最大数"
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label = "センチメント追跡"
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description = "時間の経過に伴うセンチメントの傾向を分析・追跡する"
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[i18n.ja.settings.source_reliability_threshold]
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label = "ソース信頼性しきい値"
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description = "データポイントを採用するために必要な最低ソースティア（しきい値以下のソースは、構造的変更の唯一のソースでない限り除外されます）"
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[i18n.ja.settings.change_significance_threshold]
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label = "変更重要度しきい値"
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description = "変更を「重要」に分類するための最低重要度スコア（0～100）。このしきい値以下の変更は「軽微」に分類されます"
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# ─── Spanish (Español) ────────────────────────────────────────────────────
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[i18n.es]
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@@ -513,6 +600,14 @@ description = "Número máximo de fuentes a procesar por barrido de recopilació
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label = "Seguimiento de sentimiento"
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description = "Analizar y rastrear las tendencias de sentimiento a lo largo del tiempo"
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[i18n.es.settings.source_reliability_threshold]
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label = "Umbral de fiabilidad de fuentes"
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description = "Nivel mínimo de fuente requerido para incluir un dato (las fuentes por debajo del umbral se descartan, salvo que sean la única fuente de un cambio estructural)"
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[i18n.es.settings.change_significance_threshold]
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label = "Umbral de significancia de cambios"
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description = "Puntuación mínima de significancia (0-100) para clasificar un cambio como IMPORTANTE. Los cambios por debajo se clasifican como MENORES."
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# ─── French (Français) ────────────────────────────────────────────────────
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[i18n.fr]
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@@ -552,6 +647,14 @@ description = "Nombre maximum de sources à traiter par cycle de collecte"
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label = "Suivi du sentiment"
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description = "Analyser et suivre les tendances de sentiment au fil du temps"
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[i18n.fr.settings.source_reliability_threshold]
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label = "Seuil de fiabilité des sources"
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description = "Niveau minimum de source requis pour inclure un point de données (les sources en dessous du seuil sont ignorées, sauf si elles sont la seule source d'un changement structurel)"
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[i18n.fr.settings.change_significance_threshold]
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label = "Seuil de significativité des changements"
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description = "Score minimum de significativité (0-100) pour qu'un changement soit classé comme IMPORTANT. Les changements en dessous sont classés comme MINEURS."
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# ─── German (Deutsch) ────────────────────────────────────────────────────
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[i18n.de]
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@@ -591,6 +694,14 @@ description = "Maximale Anzahl der pro Sammlungszyklus zu verarbeitenden Quellen
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label = "Stimmungsverfolgung"
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description = "Stimmungstrends im Zeitverlauf analysieren und verfolgen"
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[i18n.de.settings.source_reliability_threshold]
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label = "Quellenzuverlässigkeitsschwelle"
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description = "Mindeststufe einer Quelle, damit ein Datenpunkt aufgenommen wird (Quellen unterhalb der Schwelle werden verworfen, es sei denn, sie sind die einzige Quelle einer strukturellen Änderung)"
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[i18n.de.settings.change_significance_threshold]
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label = "Änderungssignifikanzschwelle"
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description = "Mindestpunktzahl (0-100), ab der eine Änderung als WICHTIG eingestuft wird. Änderungen unterhalb werden als GERINGFÜGIG eingestuft."
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# ─── Korean (한국어) ────────────────────────────────────────────────────
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[i18n.ko]
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@@ -629,3 +740,11 @@ description = "수집 스캔당 처리할 최대 소스 수"
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[i18n.ko.settings.track_sentiment]
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label = "감성 추적"
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description = "시간에 따른 감성 추세 분석 및 추적"
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[i18n.ko.settings.source_reliability_threshold]
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label = "소스 신뢰도 임계값"
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description = "데이터 포인트를 포함하기 위해 필요한 최소 소스 등급 (임계값 미만의 소스는 구조적 변경의 유일한 소스가 아닌 한 제외됩니다)"
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[i18n.ko.settings.change_significance_threshold]
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label = "변경 중요도 임계값"
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description = "변경을 '중요'로 분류하기 위한 최소 중요도 점수 (0-100). 이 임계값 미만의 변경은 '경미'로 분류됩니다"
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+69
-32
@@ -150,45 +150,82 @@ site:sec.gov "[company]"
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## Change Detection Methodology
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### Snapshot Comparison
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1. Store the current state of all entities as a JSON snapshot
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2. On next collection cycle, compare new state against previous snapshot
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3. Classify changes:
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### Change Classification
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| Change Type | Significance | Example |
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|-------------|-------------|---------|
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| Entity appeared | Varies | New competitor enters market |
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| Entity disappeared | Important | Company goes quiet, product deprecated |
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| Attribute changed | Critical-Minor | CEO changed (critical), address changed (minor) |
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| New relation | Important | New partnership, acquisition, hiring |
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| Relation removed | Important | Person left company, partnership ended |
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| Sentiment shift | Important | Positive→Negative media coverage |
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Every difference between the current snapshot and the previous one falls into exactly one category:
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| Category | Definition | Examples |
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|----------|-----------|---------|
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| **Structural** | Entity appeared/disappeared, relationship added/removed | New competitor enters market, person left company, product deprecated, new partnership formed |
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| **Content** | Attribute value changed on an existing entity | CEO changed, funding amount updated, version number bumped, pricing modified |
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| **Metadata** | Supporting data changed but core fact is the same | New source confirms existing fact, confidence upgraded, last_seen timestamp refreshed |
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### Cross-Source Deduplication
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Before scoring, deduplicate overlapping data points:
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1. **Normalize** entity names: strip legal suffixes (Inc, LLC, Corp), lowercase, expand common abbreviations
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2. **Merge** when 2+ sources report the same fact about the same entity — keep highest confidence, list all source URLs
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3. **Flag conflicts** when sources disagree on a fact (e.g., different funding amounts) — record both, mark as "conflicting — requires resolution"
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### Significance Scoring Algorithm
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Compute a numeric score (0-100) for each change:
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### Significance Scoring
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```
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CRITICAL (immediate alert):
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- Leadership change (CEO, CTO, board)
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- Acquisition or merger
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- Major funding round (>$10M)
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- Product discontinuation
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- Legal action or regulatory issue
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Base score (by category):
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Structural change = 60
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Content change = 40
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Metadata change = 5
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IMPORTANT (include in next report):
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- New product launch
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- New partnership or integration
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- Hiring surge (>5 roles)
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- Pricing change
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- Competitor move
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- Major customer win/loss
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Source reliability modifier (best source tier for this data point):
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Tier 1 (official/primary) = +20
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Tier 2 (institutional) = +10
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Tier 3 (professional) = +5
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Tier 4-5 (community/anon) = +0
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MINOR (note in report):
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- Blog post or press mention
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- Minor update or patch
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- Social media activity spike
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- Conference appearance
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- Job posting (individual)
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Source freshness modifier (publication age):
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Within 24 hours = +10
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Within 7 days = +5
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Within 30 days = +0
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Older than 30 days = -10
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Corroboration modifier:
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Confirmed by 2+ independent sources = +10
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Single source only = +0
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Contradicted by another source = -15
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Focus area relevance:
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Directly matches configured focus_area = +10
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Tangentially related = +0
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Final score = clamp(base + reliability + freshness + corroboration + relevance, 0, 100)
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```
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### Alert Tier Mapping
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Map the computed significance score to an action tier using `change_significance_threshold` (configurable, default 60):
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```
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Score >= 80 → CRITICAL (immediate alert via event_publish)
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Examples: leadership change (CEO/CTO/CFO), acquisition or merger,
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major funding round (>$10M), product discontinuation,
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regulatory action, data breach
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Score >= threshold → IMPORTANT (include in next report)
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Examples: new product launch, new partnership, hiring surge (>5 roles),
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pricing change, significant competitor move, major customer win/loss
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Score < threshold → MINOR (note in report)
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Examples: blog post, minor update or patch, conference appearance,
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individual job posting, social media activity within normal range
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```
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### Source Reliability Filtering
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Apply the configured `source_reliability_threshold` (default: tier_3) to filter low-quality data:
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- **Discard** data points where ALL supporting sources fall below the threshold tier
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- **Exception**: if a below-threshold source is the ONLY source for a structural change, keep it but downgrade confidence to "low" and flag for corroboration in the next cycle
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---
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## Sentiment Analysis Heuristics
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Reference in new issue
Block a user