Get Pipeline Status

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, establishing it as a safe, read-only operation. The description adds value by detailing the return content (phases, files, percentage, next action), but does not disclose any additional behavioral traits (e.g., whether it requires a running pipeline, rate limits, or side effects). No contradiction with 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?

The description is a single, well-structured sentence that lists key return fields. No redundant or extraneous information. It is front-loaded with the core purpose ('Returns the current pipeline status') and efficiently details the content. Every word earns its place.

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's simplicity (2 optional params, no output schema), the description adequately covers the return fields and intended use. It could be more complete by noting the return format (e.g., JSON) or potential error conditions, but for a basic status query, it provides sufficient context for an AI agent to use it correctly. Annotations cover safety fully.

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% description coverage for both parameters (spec_dir and feature_number), each with clear, self-explanatory descriptions. The tool description does not add any further semantic information beyond what the schema already provides. Baseline score of 3 is appropriate when schema does the heavy lifting.

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 explicitly states the tool returns 'current pipeline status' and lists specific fields (current phase, completed phases, etc.). It clearly distinguishes this from siblings like sdd_advance_phase (which advances the pipeline) and sdd_context_status (which might return context rather than pipeline status), making the purpose specific and 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 provides no guidance on when to use this tool versus alternatives (e.g., sdd_checkpoint, sdd_context_status). It only states what it does, without mentioning preconditions, exclusion criteria, or when not to use it. This lack of usage context limits its utility for an AI agent choosing between similar tools.

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