parse_adr_markdown

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

With no annotations, the description carries full burden for behavioral traits. It states the tool is static and has no persistence, and returns null on missing required sections. This provides key transparency about side effects and error conditions.

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 concise—one sentence plus a return note. The version prefix 'v2.1.0' is minor but does not harm. It is front-loaded and to the point, earning a high score.

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 simplicity (1 param, no output schema, no annotations), the description covers the main behavior and return case. However, it does not specify what constitutes valid ADR markdown or the full structure of DecisionInput, leaving some gaps for an agent.

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 a clear description for the single parameter 'text' ('Raw ADR markdown text'). The tool description adds minimal extra meaning beyond that, so a baseline of 3 is appropriate.

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 the tool's action: parsing ADR markdown into a DecisionInput shape. It specifies the source (hand-written or exported) and distinguishes itself from sibling tools like export_decision_as_adr_markdown by being the inverse operation.

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 implies when to use (when you have ADR markdown and want a structured DecisionInput) but does not explicitly mention when not to use or compare with alternative parsing tools. It is clear enough for straightforward usage.

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