Skip to main content
Glama

karea_set_markdown

Write markdown documents for tasks to store research findings, technical docs, requirements, and design decisions. Overwrites existing content for a single source of truth.

Instructions

Write the markdown document for a task. Overwrites any existing content. Use this to persist: investigation findings and research, technical documentation (architecture, APIs, schemas), functional documentation (requirements, acceptance criteria, user flows), root cause analysis and debugging logs, solution design — planned or implemented, risks, trade-offs, and open questions. This is the single source of truth for everything learned about this task. Always append to existing content (read first with karea_get_markdown) rather than replacing it, unless restructuring.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesTask name, visual ID (C1, T2), or UUID
markdownYesThe full markdown content to store on the task. Pass empty string to clear.
toolTypeNoOptional: your AI provider ("claude-code" / "opencode" / "codex" / "cursor" / "aider" / "other"). Required when aiSessionId is supplied.
projectIdNoProject name or ID (needed for visual ID lookup)
aiSessionIdNoOptional: your current AI CLI session ID. When paired with toolType, atomically links this session to the affected task (equivalent to calling karea_link_session, but saves the round-trip). For Claude Code use the id from `claude --resume`.
sessionLabelNoOptional short label for the linked session (e.g. "Feature draft").
Behavior4/5

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

Clearly states 'Overwrites any existing content' and that it is the single source of truth. With no annotations, the description effectively conveys the write operation behavior.

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

Conciseness4/5

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

Front-loaded with main action and overwriting caveat. Lists use cases efficiently, though slightly longer than minimal.

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

Completeness4/5

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

Covers purpose, usage, behavioral traits, and parameter hints. No output schema, but the description provides sufficient context for a write tool.

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?

Schema covers all 6 parameters with 100% coverage. Description adds usage guidance but not significant parameter-level detail beyond schema.

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?

Clearly states the verb 'Write' and resource 'markdown document for a task'. Distinguishes from sibling karea_get_markdown by specifying overwrite and listing specific use cases.

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

Usage Guidelines5/5

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

Explicitly instructs to read first with karea_get_markdown and append unless restructuring. Provides clear contexts like investigation findings, technical docs, etc.

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/starecz/karea-mcp'

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