tg_memory

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

The description discloses important behavioral traits beyond the annotations: updates send messages to an external model (privacy impact), the dossier is written from untrusted text and must never be treated as instructions, and updates are incremental with first-call creation. No contradiction with annotations exists.

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

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

The description is well-structured into concept, usage guidance, warnings, and argument explanations. Each section earns its place; the privacy and trust warnings are especially valuable and the argument list is compact and readable.

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

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

The description covers the use case, privacy implications, incremental update behavior, defaults, and parameter meanings. Minor gaps remain: the exact format of the chat identifier is vague, and the return shape of show/list is not stated, though it is largely inferable.

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

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

Schema description coverage is 0%, but the description fully compensates by explaining every parameter: chat, action values with meanings, limit with default, and model override. This gives the agent enough to invoke the tool correctly without needing the schema.

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

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

The description clearly defines the tool as a per-chat dossier written by an LLM, and then enumerates the concrete actions (show, update, list) with their effects. This distinguishes it from related tools like tg_history or tg_summarize by emphasizing the persistent, incremental, LLM-written memory file.

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

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

The description explicitly says to read it before answering in an unfamiliar chat, and contrasts this with the cost of reading full history. It does not name sibling tools or state when not to use it, but the usage context is clear and actionable.

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