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eonik-ai

eonik-mcp

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get_category_topics

Retrieve a brand's watched category topics as hashtag bundles with Instagram post counts, revealing the wider field. Use returned topic IDs to load hashtag posts via get_competitor_assets.

Instructions

The category conversation pulled by hashtag: every watched TOPIC (a named hashtag bundle, e.g. 'UPSC prep' = #upsc #ssc #currentaffairs) with its captured Instagram post count. Topics are the wider field, not owned competitors. Load a topic's posts with get_competitor_assets(competitor_id=topic_id, channel='instagram_hashtag'). Facts only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brand_idNoWhich brand's topics. Defaults to the brand this request is about.
Behavior3/5

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

With no annotations, the description carries the transparency burden. It implies a read-only operation through the verb 'get' and the phrase 'Facts only,' but it does not explicitly state side effects, permissions, or that no modifications occur. A more explicit statement would improve transparency.

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

Conciseness2/5

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

The description is redundant and somewhat tangled. Phrases like 'The category conversation pulled by hashtag' and 'every watched TOPIC ... with its captured Instagram post count' repeat similar information, and the pointer to another tool could be integrated more cleanly. A more streamlined structure would improve clarity.

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

Completeness3/5

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

Without an output schema, the description gives a basic idea of the return content (topics and Instagram post counts) and notes 'Facts only' to imply data reliability. It lacks details on the exact structure or fields, but is sufficient for a basic understanding.

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?

The sole parameter 'brand_id' is fully described in the schema, including its default behavior. The description adds no extra detail beyond the schema, so it meets the baseline but does not enhance understanding.

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

Purpose4/5

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

The description clearly states that the tool retrieves category topics (hashtag bundles) along with their Instagram post counts, and distinguishes topics from competitors. The verb 'get' and resource 'category topics' are explicit, though the phrasing is somewhat verbose.

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

Usage Guidelines3/5

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

The description provides a pointer to a related tool (get_competitor_assets) for loading a topic's posts, which gives some context on when to use this tool vs. that one. However, it does not explicitly enumerate scenarios or compare with other sibling tools, leaving usage guidance implicit.

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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