القائمة
Knowledge base analytics, usage reporting, and effectiveness measurement
يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.
اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/a5c-ai/babysitter --skill knowledge-analyticsيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
Reference for querying the Atlas knowledge graph through its MCP tools — the SECONDARY enrichment/comparison layer that adds best-practice context to systems you have ALREADY scanned from your real sources (`az`, repos, dirs). Use when you need to look up nodes, edges, kinds, clusters, stats, or wiki pages in Atlas to compare against your real inventory. (atlas graph, query atlas, atlas mcp, search the graph, graph neighbors, atlas record, atlas kinds, enrichment layer)
Atlas turns your STATED NEED into a real systems atlas by SCANNING your actual sources (Azure via `az`, git repos, local dirs) and process/data mining them, THEN enriching against the Atlas knowledge graph. Use this skill when asked to inventory/map your real systems, scan your cloud + repos + directories, mine the real processes or data they contain, or collect their real constraints/gotchas. (atlas, scan my systems, inventory our azure account, map my repos, real systems atlas, process mining, data mining, collect nuances, system discovery)
This skill should be used when the user asks to "find skills in the wild", "assimilate popular workflows", "discover SKILL.md files in repos", "research external skills", "find workflow patterns", "survey the skill landscape", "what skills exist out there", or wants to investigate public repositories for extractable processes, babysitter plugins, and reusable procedural insights. Searches GitHub for SKILL.md files, classifies repos by archetype, and maintains structured research under docs/reference-repos/.
عرض SKILL.md
استنادا إلى تصنيف SOC المهني
| name | knowledge-analytics |
| description | Knowledge base analytics, usage reporting, and effectiveness measurement |
| allowed-tools | ["Read","Write","Glob","Grep","Bash","WebFetch"] |
| metadata | {"specialization":"knowledge-management","domain":"business","category":"Analytics","skill-id":"SK-019"} |
| graph | {"domains":["domain:knowledge-management"],"skillAreas":["skill-area:data-analytics","skill-area:data-governance","skill-area:data-quality"],"roles":["role:information-architect","role:data-analyst","role:analytics-engineer"]} |
The Knowledge Analytics skill provides comprehensive capabilities for measuring, analyzing, and reporting on knowledge management effectiveness. This skill enables organizations to understand how knowledge is being used, identify gaps, and continuously improve their knowledge management initiatives through data-driven insights.
This skill integrates with:
task: Set up knowledge base analytics
skill: knowledge-analytics
parameters:
platform: google-analytics
tracking:
page_views: true
engagement_time: true
scroll_depth: true
search_queries: true
custom_dimensions:
- content_type
- topic_category
- content_owner
task: Analyze content effectiveness
skill: knowledge-analytics
parameters:
time_range: 90d
metrics:
- views
- unique_visitors
- avg_time_on_page
- bounce_rate
- helpful_votes
segmentation: content_type
output: content-effectiveness-report.pdf
task: Analyze search performance
skill: knowledge-analytics
parameters:
data_source: search-logs
analysis:
- zero_result_queries
- low_click_queries
- refinement_patterns
- popular_queries
time_range: 30d
recommendations: true
task: Identify knowledge gaps
skill: knowledge-analytics
parameters:
sources:
- search_logs
- support_tickets
- user_feedback
gap_types:
- missing_content
- outdated_content
- low_quality_content
output: gap-analysis-report.md
task: Calculate knowledge management ROI
skill: knowledge-analytics
parameters:
metrics:
- ticket_deflection
- time_saved
- cost_avoidance
- productivity_gain
baseline_period: previous_year
cost_inputs:
avg_support_ticket_cost: 50
avg_employee_hourly_rate: 75
| KPI | Description | Benchmark |
|---|---|---|
| Monthly Active Users | Unique users accessing KB | Growth > 5% MoM |
| Page Views per Session | Average pages viewed | > 2.5 |
| Search Usage Rate | % users using search | > 60% |
| Return Visitor Rate | % returning users | > 40% |
| KPI | Description | Benchmark |
|---|---|---|
| Content Freshness | % content updated in 90d | > 30% |
| Content Coverage | Topics with content | > 85% |
| Helpful Rating | % positive feedback | > 80% |
| Time to Resolution | Avg time to find answer | < 3 min |
| KPI | Description | Benchmark |
|---|---|---|
| Zero-Result Rate | % searches with no results | < 5% |
| Search Success Rate | % searches leading to click | > 70% |
| Refinement Rate | % queries requiring refinement | < 20% |
| Top-3 Click Rate | % clicking top 3 results | > 60% |
| KPI | Description | Benchmark |
|---|---|---|
| Ticket Deflection Rate | % tickets avoided | > 20% |
| Self-Service Rate | % issues resolved via KB | > 50% |
| Onboarding Time Reduction | Time saved in onboarding | > 30% |
| Knowledge Reuse Rate | % content reused | > 40% |