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uplo-knowledge-management

AI-powered knowledge management intelligence. Search taxonomies, content curation records, expertise directories, and communities of practice with structured extraction.

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uplo-knowledge-management

# UPLO Knowledge Management — Organizational Learning & Expertise Intelligence This is the meta-skill: knowledge management about knowledge management. Your organization's KM infrastructure — taxonomies, controlled vocabularies, expertise directories, community of practice charters, content lifecycle policies, lessons learned repositories, and knowledge audit results — is indexed in UPLO. Use this skill to understand, maintain, and improve how your organization captures, organizes, and shares what it knows. ## Session Start ``` get_identity_context ``` As a KM practitioner, you likely have broad read access across the organization. But KM strategy documents, knowledge audit findings, and expertise gap analyses may be restricted if they reveal competitive intelligence vulnerabilities. ## Example Workflows ### Knowledge Audit for a Business Unit The Product Engineering division has experienced 40% turnover in the past year. The KM team needs to assess what institutional knowledge is at risk. ``` search_with_context query="subject matter experts and knowledge domain owners within Product Engineering and their documented areas of expertise" ``` ``` search_knowledge query="knowledge transfer and documentation requirements in the offboarding process" ``` ``` search_knowledge query="lessons learned and after-action review submissions from Product Engineering in the past 18 months" ``` Cross-reference the expertise directory with the departure list to identify critical knowledge areas that lost their primary expert without a documented successor. ### Taxonomy Governance Review The enterprise taxonomy has grown organically and several business units are requesting new terms that may overlap with existing ones. The KM team needs to rationalize. ``` search_knowledge query="enterprise taxonomy governance policy including term proposal process and review committee membership" ``` ``` search_with_context query="controlled vocabulary terms related to 'customer engagement' across all business units and their usage frequency" ``` ``` search_knowledge query="taxonomy change log and approved term additions from the past 12 months" ``` ## When to Use - A KM analyst needs to find which communities of practice are active, dormant, or recently dissolved and why - Someone asks whether the organization has a knowledge retention strategy for employees approaching retirement eligibility - The CKO wants a dashboard view of content freshness across all knowledge repositories — what percentage of articles were reviewed in the past year - A department head asks how to set up a new community of practice and what governance structure is required - The IT team is evaluating a new collaboration platform and needs to understand current knowledge sharing patterns and tool adoption metrics - An executive asks for evidence that the KM program is delivering measurable value — ROI metrics, reuse rates, time-to-competency improvements - A content steward wants to know the disposition rules for records that have passed their retention period ## Key Tools for Knowledge Management **search_with_context** — KM questions are inherently cross-cutting. A query like `query="which knowledge domains have no designated owner and what content exists in those domains"` requires traversing the expertise directory, domain taxonomy, and content inventory simultaneously. This is your primary tool. **search_knowledge** — Use for specific KM artifacts: `query="community of practice charter template and facilitation guidelines"` or `query="content lifecycle policy including review frequency and archival criteria"`. KM frameworks tend to be well-documented, so direct searches work when you know what you are looking for. **export_org_context** — The KM team's best friend. The full organizational context export reveals the state of institutional knowledge: which areas are well-documented, which have gaps, how knowledge flows between teams. Use this for annual KM program assessments. **report_knowledge_gap** — This is the tool KM practitioners should use most aggressively. Every gap you report feeds back into the organizational twin's health score: `topic="machine learning model deployment procedures" description="Data Science team deploys 12 models to production but no standardized deployment documentation exists; knowledge is held by 2 senior engineers"` **flag_outdated** — Content staleness is the KM team's eternal battle. When you encounter documents past their review date or referencing defunct organizational structures, flag them: `entry_id="..." reason="Article references the Digital Innovation Lab which was absorbed into Product Engineering in the Q2 2025 reorg; content owner and review cycle need reassignment"` **propose_update** — KM practitioners are uniquely positioned to propose content improvements. When you find a knowledge article that is partially correct but needs updating, use the formal proposal mechanism to route the correction to the content owner. ## Tips - KM is about connections, not just content. The most valuable KM queries are the ones that reveal relationships: who knows what, which teams share knowledge, where expertise is concentrated vs. distributed. Default to `search_with_context` over `search_knowledge` when exploring organizational capability. - Distinguish between explicit knowledge (documented) and tacit knowledge (expertise held by individuals). When a search returns no documentation for a topic, check the expertise directory — the knowledge may exist in someone's head but not on paper. Report this as a knowledge gap with a recommendation to capture it. - Content freshness is a leading indicator of KM health. When you surface documents, always note their last review date. A perfectly accurate article that has not been reviewed in 3 years signals a governance failure even if the content is still correct. - Communities of practice are social structures, not just document collections. When advising on CoP health, look beyond content output to membership activity, event frequency, and cross-functional participation. A CoP with great documentation but no active discussion is a library, not a community.

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文件大小: 6.43 KB | 发布时间: 2026-4-14 13:54

v1.0.0 最新 2026-4-14 13:54
Initial release: AI-powered knowledge management skill for organizational learning.

- Enables structured search across taxonomies, expertise directories, content curation records, and communities of practice.
- Provides example KM-focused workflows, such as knowledge audits, taxonomy governance, and organizational knowledge health assessments.
- Details essential tools including search_with_context, search_knowledge, export_org_context, report_knowledge_gap, flag_outdated, and propose_update.
- Offers guidance, best practices, and tips for KM practitioners to identify knowledge gaps, manage content lifecycle, and optimize knowledge sharing.

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