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lupikovoleg

instagram-mcp

by lupikovoleg

search_instagram

Search Instagram by topic using adaptive deep pagination. Filter by media type, freshness, and provide query variants for targeted results.

Instructions

Search Instagram by topic with adaptive deep pagination, optional client-supplied query_variants, media filtering, and freshness filters. If limit is omitted, the server targets up to 50 final results by default. In MCP mode this tool is deterministic and does not call OpenRouter internally.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
limitNo
media_onlyNo
today_onlyNo
days_backNo
query_variantsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

The description adds behavioral info beyond annotations: adaptive deep pagination, default limit of 50, and determinism in MCP mode with no OpenRouter calls. However, it lacks details on authentication, rate limits, destructive/read-only nature, and other behavioral aspects that would be needed given no annotations.

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?

Three sentences front-loaded with purpose, each sentence adds value without redundancy. The description is compact and well-structured.

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?

Given the complexity (6 params, 0% schema coverage) and existence of an output schema, the description covers basic search functionality and defaults. However, it does not explain the relationship to sibling tools (e.g., how results are retrieved) or the output format, leaving gaps for an agent to integrate with other tools.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It groups parameters conceptually (e.g., media filtering, freshness filters, query variants) but does not provide detailed semantics for each parameter. The high-level mapping is insufficient for agents to understand parameter constraints or formats.

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?

The description clearly states the tool searches Instagram by topic, listing specific features like adaptive pagination, query variants, media filtering, and freshness filters. It distinguishes itself from sibling tools, which are primarily getters for specific entities or downloads.

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 implies usage for topic-based searching but provides no explicit guidance on when to use this tool vs alternatives or when not to use it. The sibling list contains no other general Instagram search, so context is helpful but not explicit.

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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