Influship

get_profile

Read-only

Fetch a single social profile by (platform, username).

Always use this first when the user gives an exact handle on a specific platform (for example "@niickjackson on Instagram") and you need the full profile: bio, follower/engagement metrics, recent activity, growth, and the canonical creator ID. Pass exactly the username they typed without the @ sign — case-insensitive matching is handled server-side. Do not use search_creators for an exact platform+username lookup.

Examples:

User: "Pull @niickjackson on Instagram" -> use this tool with platform "instagram" and username "niickjackson".
User: "Tell me about instagram.com/niickjackson" -> parse the platform and username, then use this tool.
User: "Is @niickjackson a fit for Pixel?" -> use this tool first, then call get_posts and/or match_creators if the task needs content or fit analysis.

Returns the profile record plus the underlying creator record. If you already have a creator UUID, use get_creator instead. For batch lookups by handle, use lookup_profiles.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`platform`	Yes	Social platform for the username.
`username`	Yes	Public username or handle. A leading @ is accepted.

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

A4.7/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds meaningful behavioral context: case-insensitive matching is handled server-side, the @ sign should be omitted despite the schema accepting it, and the response includes both the profile record and underlying creator record. This goes beyond what annotations alone convey.

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?

Despite being longer than average, the description is tightly structured: a lead sentence, explicit usage policy, three clarifying examples, and alternative-tool routing. Every section earns its place, especially given the large sibling set that could be confused with this tool.

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?

With a full input schema, an output schema, and read-only annotations, the description covers everything an agent needs: trigger conditions, parameter formatting, alternatives, and response contents. Nothing essential for correct invocation is missing.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds value by clarifying how to pass the username ('exactly the username they typed without the @ sign'), that matching is case-insensitive, and how to extract platform and username from URL-style user input. This reduces ambiguity beyond the schema's property 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 starts with a specific verb and resource ('Fetch a single social profile by (platform, username)') and immediately distinguishes it from siblings like search_creators, get_creator, and lookup_profiles. The purpose is unambiguous even before reading the 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?

The description explicitly states when to use this tool ('Always use this first when the user gives an exact handle on a specific platform'), when not to ('Do not use search_creators for an exact platform+username lookup'), and names alternatives for other cases ('use get_creator instead', 'use lookup_profiles'). Concrete examples make the routing decision trivial.

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.

get_profile

Input Schema

Output Schema

TDQS

Glama MCP Gateway

TDQS

Resources