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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile needs no restating. The description adds value by disclosing that input is a free-form natural-language account and that output includes a traced classical causal chain plus prescriptive remediation ('chỉ dẫn pháp hóa giải'), but says nothing about depth, length, or how the diagnosis is bounded.

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?

It is a single front-loaded sentence with the diagnosing action and causal-tracing outcome stated early, followed by a compact parenthetical of use cases. The parenthetical is long but each item is informative rather than filler.

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?

Since there is no output schema, the description carries the burden of conveying what comes back, and it does so briefly (causal tracing plus remedial guidance). Combined with complete schema coverage and rich annotations, the remaining gap is mainly sibling differentiation against karma_chart_read, which keeps it out of the top band.

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% for the single 'text' parameter, so the baseline is 3. The description does contribute example content categories (financial hardship, marriage, health, injustice, past mistakes) that hint at what to put in the free-form text, but adds no length, formatting, or language constraints beyond what the schema already states.

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 states a specific verb ('Chẩn đoán' — diagnose) and resource ('căn nguyên nghiệp quả' — karma root cause), and the parenthetical lists the concrete problem domains it handles (finance, marriage, health, grievance, past misdeeds). It does not distinguish itself from the sibling karma_chart_read, which sounds like an adjacent karma-reading capability, so an agent cannot fully disambiguate from the text alone.

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 enumerated problem categories imply when to reach for this tool (user describes a concrete life difficulty in natural language), which is a usable but implicit signal. There is no explicit when-not guidance, no mention of prerequisites, and no routing to alternatives such as karma_chart_read or search_yinyang_guides, leaving overlap resolution to inference.

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