get_qa_context

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

No annotations are provided, so the description bears the full burden. It explains what the tool reads, the fallback behavior, and the optional parameter's effect. However, it does not mention any side effects, rate limits, or idempotency, though as a read operation these are less critical. The description is fairly transparent.

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 a single dense paragraph that packs a lot of information. While it is concise, the flow could be improved by splitting usage instructions from fallback behavior. Still, every sentence serves a purpose.

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 has only one optional parameter, no output schema, and no annotations, the description is remarkably complete. It explains the return value (whole file with section list or single section), the fallback content, and the integration with sibling tools (generate_test, init_qa_knowledge). No gaps are apparent.

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?

The input schema has 100% coverage, but the description adds significant value: it explains the optional 'section' parameter is case-insensitive, supports partial matching, and when omitted returns the whole file plus a list of section names. This goes beyond the schema's basic description.

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 reads 'qa-knowledge.md' for business context and provides a specific verb ('讀取') and resource. It distinguishes itself from siblings like 'init_qa_knowledge' (creates the file) and 'generate_test' (uses context), making its role unambiguous.

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 gives explicit usage guidance: first call to get content, then pass as business_context to generate_test. It also explains the fallback to built-in knowledge if the file is missing and suggests running 'init_qa_knowledge' later, providing clear when-to-use and alternatives.

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