analyze_error_text

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

No annotations are provided, so the description carries the full behavioral burden. It says the analysis is 'intelligent' but never discloses that this is an LLM-backed call, nor any latency, cost, input-size limit, or failure behavior — relevant given the sibling check_llm_status. Only the 'no log file needed' note adds any behavioral context.

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?

Two short, front-loaded sentences: the capability first, then the parameter. Nothing is padded, though the docstring-style 'Args:' block is slightly formulaic for a single obvious parameter.

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?

An output schema exists, so return values need not be explained. For a single-parameter analysis tool this is close to adequate, but with zero annotations the description leaves undisclosed how the analysis is performed and any limits on the pasted text.

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 description coverage is 0%, so the description must carry the parameter meaning, and it does: error_text is the raw error message or exception stack text. It compensates for the empty schema description, though it adds no constraints such as size limits or accepted formats.

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 names a specific verb (智能根因分析 / intelligent root-cause analysis) and a specific resource (a piece of error/stack text pasted directly by the user). The parenthetical '无需日志文件' implicitly separates it from the log-file siblings such as analyze_log and read_log_tail, so an agent can route correctly without opening either schema.

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?

It gives a clear condition for use: the user has pasted raw error text and no log file is involved. This contrasts with the file-oriented siblings (list_log_files, analyze_log), though it never names an alternative tool or states an explicit exclusion, so it falls 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.