decompile_stack_trace

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

No annotations exist, so the description carries the full burden of behavioral disclosure. It hints at the output (structured JSON root-cause analysis) but never says whether the call is read-only, whether it accepts only single tracebacks, whether it makes external calls, or what limitations exist; a caller cannot predict side effects from either the description or the empty annotations.

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?

One front-loaded sentence with no filler. It is efficient, though it could use one more sentence of practical guidance without becoming padded.

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?

For a simple, single-parameter tool, the definition is nearly adequate, but there is no output schema and the phrase "structured JSON root-cause analysis" does not give the shape of the return value. Because the description is the only source of return information, that gap matters more here than it would with a documented output.

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?

There is a single required parameter (traceback_text) with 100% schema description coverage, so the parameter is already documented. The description adds nothing about how the traceback should be formatted, whether chained exceptions are accepted, or how truncation is handled, so it earns the baseline, not more.

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 uses a specific verb and resource ("Decompiles Python tracebacks") and states the produced artifact ("structured JSON root-cause analysis"), which is enough for an agent to know what the tool does. It stops short of differentiating itself from the sibling tools, though their names suggest different domains, so the split is inferable rather than stated.

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?

Usage is only implied: an agent must infer that this tool is for when it has a raw Python traceback and wants root-cause analysis, and that it is not a test-generation or assertion-auditing tool. There are no explicit when-not conditions, no prerequisites, and no named alternative.

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