recall_chat_history

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

With no annotations supplied, the description carries the full burden and discloses return format (synthesized summaries with source metadata), date bound semantics (inclusive UTC), mode behavior (quality vs speed), and token consumption. It does not discuss failure modes or rate limits, but covers the most relevant behaviors.

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 longer than average but well-structured with WHEN TO USE, HOW TO USE, and output-format note. Most lines earn their place, though the alias sentence adds little functional value.

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 purpose, when to use, how to use key parameters, and return behavior, which is sufficient for a 9-parameter tool with no output schema. It omits edge cases like the 15-query parallel cap or failure behavior, but those are minor for selection/invocation.

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?

Although schema coverage is 100%, the description adds practical value by suggesting maxTokens range (300-1000), giving ISO 8601 date examples, and explaining parallel queries for complex topics. This goes beyond the schema's field descriptions without fully clarifying every parameter interaction.

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 opening sentence 'Search and synthesize context from the user's past AI conversations' states a specific verb and resource, and the later note 'Returns synthesized summaries (not raw conversation logs)' distinguishes it from raw-log retrieval tools like get_full_conversation. The alias 'MemoryPlugin inject tool' reinforces its role in injecting recall context.

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 WHEN TO USE section explicitly lists situations (past decisions, patterns, preferences, relationships, projects) and even suggests proactive use. It lacks explicit when-not-to-use instructions or named alternatives, so it stops short of a 5.

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