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

The description discloses behavior beyond annotations: it auto-snapshots full entry conditions (grade, flags, positioning, regime) via an internal check_trade, explains historical grading logic (nearest check_trade within ±6h, same asset+side), never re-grades on today's tape, and notes ungraded trades when no match. It also mentions the journal is private and returns trade_id + entry assessment. Annotations only say readOnly=false, which the description aligns with.

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 with clear sections for live logging, historical backfill, related tools, return value, and privacy. Every sentence adds value, and the length is appropriate given the tool's complexity (9 parameters, no output schema). No redundant or filler content.

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 high parameter count and lack of output schema, the description is remarkably complete. It covers the primary use case, backfill scenario, auto-grading behavior, related tools, return value, and privacy. It even notes the Pro status. There is sufficient information for an AI agent to correctly invoke the tool.

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?

With 0% schema description coverage, the description fully compensates by explaining each parameter: entry defaults to live price, opened_at is for historical backfill and requires explicit entry, and optional params are listed (stop, target, size_usd, leverage, thesis). It also clarifies the semantic nuance of opened_at and the grading interaction, which goes beyond 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 states the verb and resource: 'Log a REAL trade entry into your private n0brains journal the moment it fills.' It distinguishes from sibling tools like close_trade and get_journal by focusing on entry logging, and it specifies real trades vs backfill.

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 provides clear context for when to use the tool: immediately after a fill, and for historical backfill with opened_at. It explicitly mentions alternatives: 'Close with close_trade; read back with get_journal.' However, it doesn't explicitly state when not to use the tool, though the context is sufficient.

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