schema_markup

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

With no annotations, the description carries the full burden. It does disclose two real traits: output contains placeholders rather than fabricated values, and it returns instructions meant to be carried out. It says nothing about format, size, or validation guarantees, so disclosure is partial rather than complete.

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?

Two short sentences with no filler, and the core capability is front-loaded. The second sentence is a meta-instruction to the agent rather than a property of the tool, but it is brief and does carry behavioral value.

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 3-param generation tool with no annotations and no output schema, the description covers the essential behavior (placeholder-based JSON-LD, instructions to execute) but leaves the return shape and the meaning of the output enum (notes | code) to the schema. Adequate but with clear gaps.

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%, so type/output/subject are already documented in the schema, which sets the baseline at 3. The description's 'any Schema.org type' and placeholder wording loosely echo the type and subject params but add no syntax, format, or selection detail beyond the schema.

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 output (valid JSON-LD for any Schema.org type) and a distinguishing trait (placeholders instead of invented values). None of the siblings (gsc_audit, traffic_drop, keyword_clusters, ai_citations, competitor_gap, content_refresh, article_draft) do schema generation, so it is distinguishable, though it never explicitly contrasts itself with them.

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 can infer it is for generating JSON-LD markup for a page, and 'placeholders instead of invented values' hints it is a template rather than a data-populated result. There is no when-to-use, when-not, or named alternative, so guidance stays at the implied level.

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