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Robot Actions — Remote Device Control

agent_memory_append

Append a block to the calling user's persistent agent memory. Use this when the user explicitly says "remember X", "save this", or "note for next time" — DO NOT auto-update on every interaction. Memory is auto-prepended to your system prompt on every chat in this user's account. Cap: 10240 bytes total; over-cap appends return 413. Markdown is encouraged; keep entries terse and factual (preferences, project context, references), not verbose.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
blockYesMarkdown block to append. Will be separated from existing content by a blank line.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and does so well: it discloses that memory is persistent, auto-prepended to the system prompt on every chat, capped at 10240 bytes, and that over-cap appends return 413. It also gives content guidance (Markdown encouraged, terse and factual). This goes well beyond the schema and gives the agent a clear picture of side effects and constraints.

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?

Three dense sentences with no wasted words. The core action is front-loaded, and the usage triggers, negative guidance, persistence behavior, cap, error code, and content style are all packed efficiently. Every sentence earns its place.

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

Completeness5/5

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

For a single-parameter tool with no annotations and no output schema, this description is remarkably complete. It covers when to use it, what it does, the persistence side effect, size constraints, failure mode, and content guidance. An agent has everything needed to invoke it correctly.

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 the baseline is 3. The description adds value beyond the schema by advising Markdown and specifying the desired content style ('terse and factual', 'preferences, project context, references'). This helps the agent compose the block parameter appropriately, though it doesn't add technical parameter details like encoding or length.

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 states a specific action and resource: 'Append a block to the calling user's persistent agent memory.' It clearly distinguishes itself from the sibling agent_memory_replace by using 'append' and describing the persistent memory context. No ambiguity about what the tool does.

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 gives explicit trigger conditions: use when the user says 'remember X', 'save this', or 'note for next time', and explicitly warns DO NOT auto-update on every interaction. It does not explicitly name agent_memory_replace as the alternative for overwriting existing memory, but the append-versus-replace distinction is largely implied by the tool names and action verb.

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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