Skip to main content
Glama
tomschell
by tomschell

kg_capture

Capture knowledge nodes for decisions, insights, progress, questions, and ideas. Automatically links related content, normalizes tags, and attaches session context for traceable reasoning.

Instructions

Primary tool for capturing knowledge nodes. Use this to record decisions, progress updates, insights, questions, and ideas. Automatically creates relationships, normalizes tags, and links to sessions. This is your main entry point for adding knowledge to the graph.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoFree-form tags for categorization. Will be normalized (lowercase, dash-separated). Examples: 'frontend', 'api-design', 'bug-fix'.
typeNoType of knowledge node: 'idea' for thoughts/concepts, 'decision' for choices made, 'progress' for work updates, 'insight' for learnings/discoveries, 'question' for open questions, 'session' for session summaries.idea
ticketNoTicket/issue ID for automatic tagging. Will be normalized and prefixed as 'ticket:123'.
contentYesThe main content of the knowledge node. Be specific and include context. This is the primary information being captured.
projectNoProject name for automatic tagging. Will be normalized and prefixed as 'proj:project-name'.
auto_linkNoWhether to automatically create relationships to related nodes based on content similarity and tags.
sessionIdNoID of a session node to link this capture to. Used for grouping related work within a session.
importanceNoImportance level: 'high' for critical decisions/blockers, 'medium' for regular work, 'low' for minor notes.medium
includeGitNoWhether to capture current Git context (branch, commit hash). Useful for linking knowledge to specific code states.
visibilityNoVisibility level: 'private' (only you), 'team' (shared with team), 'public' (fully public). Defaults to private.
workstreamNoWorkstream name for automatic tagging. Will be normalized and prefixed as 'ws:workstream-name'.
link_to_sessionNoWhether to create a relationship to the specified session. Only applies if sessionId is provided.
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses key automatic behaviors (relationship creation, tag normalization, session linking) which adds value, but it omits other side effects, return format, or error handling, leaving some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loaded with the primary purpose, and contains no redundant or filler content. Every sentence adds meaningful information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Although the schema covers parameters thoroughly, the tool is complex (12 params) with no output schema or annotations. The description covers the use case and automatic behaviors but does not mention return values or potential side effects, leaving some contextual gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% parameter descriptions, so the baseline is 3. The tool description adds no parameter-specific meaning beyond what the schema already provides, so no extra credit is warranted.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as the primary capture mechanism for knowledge nodes, enumerates specific record types (decisions, progress, insights, questions, ideas), and positions it as the main entry point, effectively distinguishing it from sibling tools like kg_capture_session.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description states explicitly when to use the tool ('Use this to record decisions, progress updates, insights, questions, and ideas') and frames it as the primary entry point, but it does not mention alternatives or exclusion cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/tomschell/personal-kg-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server