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moa_board_write

Write markdown entries to a shared blackboard for sharing contracts, decisions, status, and pointers across agents and sessions. Keys overwrite values; reference large files instead of embedding.

Instructions

Write an entry to the shared blackboard (last-write-wins per key). value is markdown, max 96KB — put large content in files and reference them. Use the blackboard for contracts/decisions/status/pointers across agents and sessions; one-shot instructions belong in dispatch prompts instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesEntry key (unique within the scope; rewriting replaces the value)
tagsNoOptional tags for moa_board_read tag filtering
scopeNoBoard scope: "workspace" (default — persisted, shared by all sessions of this project), "global" (persisted, cross-project), or "task:<task_id>" (debate-local, archived with the task).
valueYesMarkdown payload, ≤ 96KB
authorNoWho writes this entry (default "anonymous"). Subagents should pass their own agent id.
workspaceNoOptional absolute project path for workspace scope; omitted keeps the server workspaceCwd default.
Behavior4/5

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

Since no annotations are provided, the description carries the full burden. It discloses last-write-wins per key, the 96KB max value size, and recommends putting large content in files. However, it does not mention return values or error behavior, which is a gap for a write operation.

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 two sentences, front-loaded with the primary action, and every clause earns its place. It is compact yet covers action, semantics, constraints, and usage guidance without waste.

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?

Given 6 parameters, no annotations, and no output schema, the description covers the core purpose, usage context, and key behavioral traits. It lacks info on return values, but for a write tool with strong guidance and schema coverage, this is a minor gap.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds value beyond schema by explaining 'last-write-wins per key' and advising to 'put large content in files and reference them', which provides practical guidance for the value parameter. Other parameters are sufficiently documented in the 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?

The description clearly states the tool's function: 'Write an entry to the shared blackboard' with the added 'last-write-wins per key' semantics. It distinguishes itself from sibling board tools (read, delete, list) by specifying the write operation and its overwriting behavior.

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?

Explicit guidance is provided: 'Use the blackboard for contracts/decisions/status/pointers across agents and sessions; one-shot instructions belong in dispatch prompts instead.' This clearly states when to use the tool and when not to, naming an alternative context.

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

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