observation_plan_get_progress

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

With no annotations, the description carries the full burden. It discloses the attribution logic (plan_id embedded in target name, fallback to target name, matching by image type/filter/exposure) and the exclusion behavior for quality thresholds. It implies a read-only operation but does not explicitly state so, nor does it mention potential edge cases like missing files. Still, it is substantially transparent about its behavior.

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 reasonably concise given the complexity, with each sentence adding essential detail. It is front-loaded with the core purpose, then explains attribution, parameters, and usage in a logical order. It avoids redundancy but is slightly long due to necessary technical detail.

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?

The tool has an output schema, so return values need not be described. The description covers the input parameters, the logic, and the usage context. It lacks explicit error handling or assumptions about file existence, but for an agent it provides enough to decide when to call and what to expect. It is complete for typical use.

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 0%, so the description must compensate. It explains file_path as the observation-plan JSON file and explains max_hfr and min_detected_stars as quality thresholds. However, it does not mention max_guiding_rms_arcsec at all, leaving that parameter semantically unexplained. This partial coverage warrants a score of 3.

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 states a specific verb ('Returns') and resource ('per-frame-type acquisition progress for an observation-plan JSON file') with detailed metrics (total_count, acquired_count, remaining_count). It clearly distinguishes itself from siblings by focusing on progress computation and explicitly routes to sequence_load_plan as the next step.

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?

Explicitly states 'Use this before sequence_load_plan to decide what still needs acquiring,' giving a clear when-to-use directive. It also explains when to pass quality thresholds (max_hfr/min_detected_stars) and how they affect results, covering the main use case without ambiguity.

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