Describe Image

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

With no annotations, the description carries the full burden and does so: it discloses local execution, licensing, deterministic decoding with reproducibility guarantees, and the hallucination risk inherent to generative captioning. It also explains the max_new_tokens escape hatch for truncated output — behavioral context no structured field provides.

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?

Front-loads the purpose, then behavior, then the routing caveat in three tight paragraphs. The opening clause 'an AI says what it sees' is mildly redundant with the name but the rest earns its place with zero filler.

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?

Output schema exists, so return values need no explanation, and the tool is a single-shot read. The description covers execution model, reproducibility, failure mode, and the alternative tool — nothing an agent needs to call it correctly is missing.

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 description coverage is 100%, so the schema already documents detail tiers, image_path, and max_new_tokens semantics. The description only echoes the tier concept ('same image at the same tier') without adding syntax or format detail. Baseline 3 applies.

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?

States a specific verb and resource ('Describe an image in prose') and names the underlying mechanism (Florence-2, local, deterministic). It implicitly contrasts with read_text (OCR) and explicitly with image_verify, so an agent can distinguish it from siblings.

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 names when NOT to use it ('for verifying a specific claim about the image, prefer ai-eyes-mcp's image_verify') and explains the tier behavior that selects output depth. This is the when/when-not/alternative pattern at full strength.

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