"search", "find article", "how to"?
search_articles / find_related
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Communication & knowledgePublic skills
Knowledge Base Management
Search-first knowledge management for AI agents — find articles, detect gaps, create content, collect feedback, and grow the KB from resolved issues via mcp-knowledge-base.
What this skill teaches
A reusable playbook for a specific kind of work.
An MCP server tells an agent which actions are available. A skill adds the judgment around those actions: how to recognize the job, which sequence to follow, what to avoid, and how to decide that the result is complete.
Manage knowledge base — search articles, find related content, create drafts, publish articles, collect feedback, and detect knowledge gaps. Use when searching for solutions, creating KB articles, finding related content, identifying gaps, or improving article quality.
Architecture
How Knowledge Base Management guides an ADK-Rust agent.
The skill stays readable and portable because it contains instructions rather than service credentials or business data. ADK-Rust supplies it to the agent, the agent chooses from its reviewed tool boundary, and the connected MCP server performs the authenticated operation.
01
User request
The agent receives a goal expressed in ordinary language.
02
Knowledge Base Management skill
Matches intent, supplies the decision guide, and narrows the tool boundary.
03
ADK-Rust agent
Plans the workflow and streams each meaningful step through the runtime.
04
mcp-knowledge-base
Executes authenticated operations against the system that owns the capability.
05
Verified result
The skill's completion rules shape the evidence returned to the user.
Decision guide
How the agent turns a request into the right action.
These routes come directly from the skill instructions. They help the model recognize intent and select a focused tool or workflow instead of improvising across the entire capability surface.
"create article", "document this"?
create_draft
"update", "improve", "outdated"?
suggest_update
"gaps", "missing", "what's needed"?
get_knowledge_gaps
"feedback", "helpful?"?
record_feedback
Proven workflows
Repeatable sequences for useful outcomes.
A workflow joins several tool calls into a task the user actually recognizes. The skill explains the sequence and the intended result while ADK-Rust streams the agent's progress through the shared runtime.
011-2 calls
Search & Resolve
Find answer without creating a ticket
022 calls
Create Article
Draft + publish from resolved issues
031 calls
Gap Analysis
Identify missing content by query frequency
041 calls
Feedback Loop
Track article helpfulness
Tool boundary
The skill may use 9 documented tools.
This allowlist is declared by the skill. It keeps the agent focused on the actions needed for this job while mcp-knowledge-base retains responsibility for authentication, validation, and the connected system.
search_articles
get_article
find_related
create_draft
suggest_update
publish_article
record_feedback
list_articles
get_knowledge_gaps
Working rules
What the agent should do.
- Always search before creating (avoid duplicates)
- Cite sources — never present ungrounded info as KB content
- Track article freshness — flag stale content
- Create articles from resolved incidents (grow the KB)
Operating boundaries
What the agent should avoid.
- Don't publish without review
- Don't present outdated articles without flagging staleness
Install and connect
Add the skill beside the capability it expects.
Install the repository where your ADK-Rust skill loader can discover it, connect mcp-knowledge-base, and confirm the declared tools are available before asking the agent to use the workflow.
Install the skill
git clone https://github.com/zavora-ai/skill-knowledge-base-management.git \
~/.skills/skills/knowledge-base-managementADK-Rust loading shape
let skills = SkillLoader::from_dir("~/.skills/skills").await?;
let skill = skills.load("knowledge-base-management").await?;
let agent = LlmAgentBuilder::new("agent")
.instruction(skill.instructions())
.tools(skill.allowed_tools(toolset)?)
.build()?;The repository's compatibility statement: Requires mcp-knowledge-base server connected.
Official documentation
Read the complete skill package.
The repository remains authoritative for its exact instructions, examples, helper scripts, assets, MCP requirements, license, and later updates.
Keep exploring
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Source record
Repository metadata for this skill entry.
- License
- Apache-2.0
- Allowed tools
- 9
- References
- 3
- Revision
- 60be6b1e77d1
- Updated
- May 31, 2026