Influship

lookup_profiles

Read-only

Batch-fetch up to 100 profiles by (platform, username) pairs.

Use this when the user has a list of handles and you need profile data for all of them at once (e.g., "give me follower counts for these 30 accounts I'm considering" or "which of @a @b @c are real accounts?"). One round-trip beats 30 calls to get_profile.

Use this for exact batch handle lookup, not semantic discovery. For one exact platform+username pair, use get_profile. For partial or fuzzy handle/name input, use search_creators or autocomplete_creators. Use semantic_search_creators only for topical/niche/audience discovery where false-positive semantic matches are acceptable.

Examples:

User: "Compare @a, @b, and @c on Instagram" -> use this tool for the exact handle batch.
User: "Give me follower counts for these 30 accounts" -> use this tool.
User: "Find wellness creators in Austin" -> use semantic_search_creators, not this tool.

The response splits results into data (profiles found) and not_found (the (platform, username) pairs that weren't recognized). Profiles are returned in no particular order — re-correlate via the platform/username fields if you need to preserve input order.

Input Schema

Name	Required	Description	Default
`profiles`	Yes	Profiles to lookup

Output 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

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedOct 23, 2026

addedInput schema / $ref

Added value: +"#/definitions/ProfilesLookupRequest"

addedInput schema / definitions / ProfilesLookupRequest

Added value: +{
+  "description": "Batch lookup profiles request",
+  "examples": [
+    {
+      "profiles": [
+        {
+          "platform": "instagram",
+          "username": "fitness_coach_jane"
+        },
+        {
+          "platform": "instagram",
+          "username": "wellness_guru"
+        },
+        {
+          "platform": "instagram",
+          "username": "healthy_eating_tips"
+        }
+      ]
+    }
+  ],
+  "properties": {
+    "profiles": {
+      "description": "Profiles to lookup",
+      "items": {
+        "$ref": "#/definitions/ProfileLookupItem"
+      },
+      "maxItems": 100,
+      "minItems": 1,
+      "type": "array"
+    }
+  },
+  "required": [
+    "profiles"
+  ],
+  "type": "object"
+}

removedOutput schema / properties / next_cursor / anyOf

Removed value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]

addedOutput schema / properties / next_cursor / type
```
Added value: +[
+  "string",
+  "null"
+]
```

First observedMay 28, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already establish read-only, closed-world, non-destructive behavior, and an output schema exists, so the bar is lower. The description still adds genuinely useful behavior: results split into `data` and `not_found` (partial-failure disclosure) and profiles return in arbitrary order requiring re-correlation. It does not mention auth or rate-limit behavior, keeping it below a 5.

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

Conciseness4/5

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

Purpose and the primary routing rule are front-loaded, and the return-shape caveat is placed last where an agent will look for it. It loses a point for repetition: the '30 accounts / follower counts' scenario is stated twice and the social-proof question is covered by three overlapping examples.

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?

For a single-parameter, read-only batch lookup with an output schema, everything an agent needs is present: input shape, batch ceiling, routing to five siblings, response partitioning, and the ordering caveat. Nothing material 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 coverage is 100% so the baseline is 3; the description nonetheless clarifies that each entry is a (platform, username) pair and that the ceiling is 100 entries. The enum restriction on platform is left to the schema, a minor residual gap.

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 and resource (batch-fetch profiles) plus the key constraints: max 100, keyed by (platform, username) pairs. An agent can immediately distinguish this from the single-record and search siblings.

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?

Gives explicit when-to-use conditions ('a list of handles', 'one round-trip beats 30 calls'), names the alternatives and the conditions that select them (get_profile for one pair, search_creators/autocomplete_creators for fuzzy input, semantic_search_creators for topical discovery), and reinforces with worked user-utterance examples including a negative case.

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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