agent_market_scan

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

No annotations provided. The description compensates by declaring read-only (READ) and public (PUBLIC), plus small return size (~3KB). This discloses the safety profile and impact. It doesn't mention rate limits, but the core behavioral traits are covered.

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 long but well-organized with sections (purpose, scenarios, keywords, parameters, auth, risk, related tools). It front-loads the purpose and uses clear headings. Some redundancy (keyword lines) could be trimmed, but structure aids scanning.

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 no output schema, the description covers return content (top N sorted), data volume, and links to downstream tools. It also specifies auth and risk. It does not detail exact output format, but for a scanning tool this is adequate. The workflow context adds completeness.

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% with descriptions for all 3 parameters. The tool description repeats parameter info almost verbatim (defaults, enum meanings), adding no new semantic value. Baseline 3 is appropriate; the description does not enhance understanding 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 it scans market anomalies (gainers, losers, volume surges, funding rate anomalies). It differentiates from siblings like okx_get_ticker (single ticker) and okx_quick_market (deep analysis) by being a one-click scan. Use cases are concrete: '今天有什么机会', detecting surges, arbitrage targets.

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 explicitly lists scenarios: 'Agent回答今天有什么机会', finding sudden surges, funding rate arbitrage. It also provides a workflow chain: scan → okx_quick_market → agent_quick_trade, guiding when to use this versus deeper analysis tools. However, it does not explicitly state when NOT to use it.

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