journal_dialogue

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

No annotations provided, so the description carries full burden. It discloses key behaviors: refusal for private entries, creation of a new entry with specific structure (preceded_by, content format, tags), and that the LLM writes the reaction. This is comprehensive.

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 fairly concise with two sentences, but the second sentence is lengthy and contains many details. It is front-loaded with the main purpose, but could be slightly more streamlined.

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 complexity, the description covers all necessary aspects: purpose, parameter meanings, behavioral outcomes, and failure conditions. No output schema exists, but the description explains the resulting entry structure sufficiently.

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 coverage is 100%, but the description adds context beyond the schema: entry_id must refer to a user-shared entry, and user_response is the reply text. This enhances understanding of the parameters' roles.

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: handling a user's reply to a shared entry, triggering an LLM reaction and creating a new reflection entry. It distinguishes from sibling tools like journal_write or journal_introspect by focusing on dialogue interaction.

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 explains when to use the tool (user replies to a shared entry) and when not (refuses if visibility=self). However, it does not explicitly mention alternative tools for similar tasks, though context implies the specific dialogue scenario.

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