tool_conversation_heartbeat

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

With no annotations, the description fully discloses behavior: it tracks turn count, returns consolidate true at configured intervals, and provides statistics. It clarifies that the tool prompts consolidation rather than automatically executing it, avoiding ambiguity. No contradictions.

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 appropriately sized: a short declarative sentence followed by a bullet list of return fields. Every sentence contributes meaning, and the key information is front-loaded.

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?

Given the tool's simplicity (no parameters, no output schema), the description is complete. It explains when to use it, what it returns, and how to interpret the result. No gaps for an agent to understand its role in the dialogue loop.

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?

The tool has zero parameters, making schema coverage 100% by default. The description adds significant value by explaining all return fields (turn_count, consolidate, turns_since_consolidation, next_consolidation_at) and their semantics, which is well beyond the baseline of 4.

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 states the tool's purpose: tracking conversation turns and automatically triggering memory consolidation. It uses specific verbs ('追踪轮次并自动触发记忆固化') and distinguishes it from siblings that deal with memory operations (e.g., store_memory, decay_memories).

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?

Explicitly states '每轮对话结束时调用此工具' (call at the end of each conversation round). It also explains that when consolidate=true is returned, the agent should perform a memory consolidation via store_memory. However, it does not explicitly mention when not to use it or provide alternatives, so it loses a point.

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