Influship

find_lookalike_creators

Read-only

Find creators SIMILAR to one or more seed creators.

Use this when the user already knows a creator they like and wants more like them (e.g., "find creators like @therock", "find more creators like these three I just booked"). Seeds are blended via creator-profile + visual-style + fact embeddings to surface similar accounts.

Seeds are passed in seed_creator_ids (canonical UUIDs) and/or seed_profiles (platform + username; resolve handles via autocomplete_creators first if needed). Returns a ranked list of similar creators with scores. limit caps results (default 25, max 100). Use the flat follower, engagement-rate, and verified fields to constrain results.

Use semantic_search_creators instead when you have a topic/niche but no seed. Use match_creators when you have specific candidates and want to score their fit against a brief.

Examples:

User: "Find creators like @niickjackson on Instagram" -> use this tool with seed_profiles: [{ platform: "instagram", username: "niickjackson" }].
User: "Find news creators with 1M+ followers" -> use semantic_search_creators, not this tool.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum results to return.
`cursor`	No	Pagination cursor from a previous response.
`verified`	No	When set, only return verified or unverified creators.
`max_followers`	No	Maximum follower count.
`min_followers`	No	Minimum follower count.
`seed_profiles`	No	Seed creators identified by platform and username.
`seed_creator_ids`	No	Seed creators identified by canonical Influship creator UUID.
`max_engagement_rate`	No	Maximum engagement rate as a percentage from 0 to 100.
`min_engagement_rate`	No	Minimum engagement rate as a percentage from 0 to 100.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`ok`	No
`data`	No
`count`	No
`results`	No
`has_more`	No
`not_found`	No
`next_cursor`	No
`suggested_followups`	No

TDQS

A5/5.0

Behavior5/5

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

Beyond annotations (readOnlyHint=true, destructiveHint=false), the description adds behavioral context: seeds are blended via 'creator-profile + visual-style + fact embeddings', results are 'a ranked list of similar creators with scores', and handles resolution via 'autocomplete_creators first if needed'. It also notes the ability to constrain via flat fields. No contradiction with 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?

The description is front-loaded with a clear purpose sentence, then organized into usage, seed semantics, alternatives, and examples. It is thorough yet concise, with every sentence contributing value—no redundancy or fluff.

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

Completeness5/5

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

Given 9 optional parameters, an output schema, and annotations, the description covers all necessary context: when to use, how seeds are blended, parameter relationships, constraints, and alternatives. The output schema handles return details, so no omission is evident.

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

Parameters5/5

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

Though schema coverage is 100%, the description adds significant meaning: explains seed_profiles/seed_creator_ids usage, handle resolution prerequisite, and that flat follower/engagement/verified fields can be used as filters. Examples illustrate seed_profiles structure. This goes well beyond the schema descriptions.

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 states 'Find creators SIMILAR to one or more seed creators' with a specific verb, resource, and distinguishing scope. It explicitly contrasts with siblings: 'Use semantic_search_creators instead when you have a topic/niche but no seed' and 'Use match_creators when you have specific candidates and want to score their fit against a brief.'

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?

The description clearly specifies when to use: 'Use this when the user already knows a creator they like and wants more like them' with concrete examples. It also provides exclusions and alternatives ('Use semantic_search_creators instead...', 'Use match_creators when...'), satisfying all guidelines for usage differentiation.

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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TDQS

A3.9/5.0

Disambiguation2/5

Multiple tools have unclear boundaries: `autocomplete_creators` and `search_creators` both claim the exact same example query ('Who is that fitness coach called Jane?') as their primary use case, creating direct routing conflicts. `get_creator` and `get_profile` also overlap heavily for exact platform+username lookups, with descriptions admitting the choice depends on whether 'profile metrics are the main need' — a thin distinction. `search_creators` further muddies things by dual-routing to legacy semantic search, making it a hybrid that competes with both `autocomplete_creators` and `semantic_search_creators`.

Naming Consistency4/5

The naming follows a mostly consistent verb_noun snake_case pattern: `get_*` covers record fetching, with clear singular/batch pairs like `get_instagram_post`/`get_instagram_posts` and transcript variants. Minor deviations exist (`semantic_search_creators` prefixes a modifier, and `autocomplete_`, `find_`, `match_`, `lookup_`, `render_` each introduce different verbs), but the style is uniform and the verb typically reflects the operation type.

Tool Count3/5

At 28 tools the server is heavy, but the scope is genuinely broad — three platform-specific data surfaces (Instagram, TikTok, YouTube), each requiring profile/video/transcript/listing operations, plus creator search, matching, and rendering. The count is inflated by redundancy, though: four `render_*` tools that could collapse into one parameterized tool, and batch variants of the Instagram raw-data endpoints. It is borderline acceptable for the platform-multiplied domain rather than chaotic bloat.

Completeness4/5

The tool surface covers the full read-only creator workflow: fuzzy lookup (autocomplete/search), exact profile fetch (get_profile/lookup_profiles), discovery (semantic_search/find_lookalike), fit scoring (match_creators), content evidence (get_posts), and presentation (render_*). Notable gaps include no Instagram-specific profile endpoint (odd given TikTok/YouTube have dedicated ones), no YouTube comments, and no audience-demographic data, but agents can complete realistic workflows without dead ends.

find_lookalike_creators

Input Schema

Output Schema

TDQS

Glama MCP Gateway

TDQS

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