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Generate Posts From Product

generate_from_product

A plain post about exactly ONE of the user's products, built on that product's own main photo (no new picture is drawn). For two or more products in one post, a product together with a person, or a new picture of the product, use generate_posts with productIds (and characters). Runs asynchronously — the user is notified when posts are ready.

Input Schema

NameRequiredDescriptionDefault
countNoNumber of posts to generate (default 1; only more when the user asks for more)
topicNoOptional angle or occasion for the posts (e.g. 'summer sale')
productIdYesProduct id from list_products (e.g. 'shopify-42' or 'feed-17')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations cover the safety profile (not read-only, not destructive, not idempotent), so the description's added value is what it contributes beyond that: it discloses the async execution model and the user-notification behavior, plus the 'no new picture is drawn' constraint. It stops short of stating permissions or rate limits, so a 4 is warranted.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences: the positive scope first, then the routing rule to the sibling. Every clause earns its place and no filler is present.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an async generation tool with no output schema, the description covers the key facts an agent needs: the input constraint, the async/notification behavior, and the sibling routing. It could note how to check generation progress (e.g. via get_generation_status), but the notification statement largely closes that gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so all three parameters (productId, count, topic) are already documented with examples in the schema. The description reinforces the single-product constraint but adds no syntax or format detail beyond what the schema provides; baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (generate) and resource (a plain post from one product), and pins the exact constraint: exactly ONE product, built on that product's own main photo. It explicitly distinguishes itself from generate_posts, so an agent can route correctly without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Spells out both when to use this tool (one product, no new image) and the exact conditions that select the alternative — two or more products, product+person, or a new picture — naming generate_posts and even the relevant arguments (productIds, characters). Nothing is left to inference.

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

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