render_creator_profileUse this when the user wants a visual deep dive on one canonical creator ID. It fetches the current creator record plus up to six recent posts and may consume Influship account or API usage.
| Name | Required | Description | Default |
|---|---|---|---|
| creator_id | Yes | Canonical Influship creator ID. |
| Name | Required | Description | Default |
|---|---|---|---|
| view | Yes | ||
| posts | Yes | ||
| creator | Yes | ||
| postsUnavailable | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide no safety hints (all false), so the description carries the burden. It discloses that the operation may consume Influship account or API usage, and specifies the fetched scope (current record plus up to six recent posts). It does not mention rate limits or auth, but the usage warning adds material value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the use trigger, and no filler. Each sentence conveys either the use case or the behavioral scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single well-documented parameter, an output schema, and a clear description, the tool definition is complete. The description sufficiently covers purpose, behavior, and cost implication without needing to elaborate return fields.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already fully documents creator_id with format, pattern, and description; coverage is 100%. The description's 'canonical creator ID' phrasing only reinforces the schema without adding new syntax or semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'fetches' and defines scope: visual deep dive on a single canonical creator ID, with current record plus up to six recent posts. It clearly distinguishes from sibling tools like render_creator_comparison or get_creator by emphasizing 'one canonical creator ID' and 'visual deep dive.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: when user wants a visual deep dive on one canonical creator ID. It does not name alternatives or exclusions, so it misses the full 5, but the trigger condition is clear and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools have overlapping boundaries: autocomplete_creators and search_creators are described as near-equivalent fuzzy lookups, get_creator and get_profile both resolve exact platform+username input, and the Instagram/TikTok post helpers overlap with generic get_posts. The descriptions work hard to disambiguate, but an agent would frequently need to choose between two or three equally plausible tools.
Most tools follow a clear verb_noun snake_case pattern, such as get_youtube_video, search_creators, match_creators, and render_creator_profile. Minor inconsistencies exist: singular/plural variants (get_instagram_post vs get_instagram_posts), list_ vs get_ for video listing, and search_creators carrying legacy semantic behavior under a lookup-sounding name.
Twenty-eight tools places the server in the 'too many' range, and the count is inflated by near-duplicates like autocomplete_creators/search_creators, get_creator/get_profile, and singular/batch transcript variants. Even with three social platforms and rendering helpers, the surface would be more focused around 18–22 tools.
The core influencer research workflow is well covered: handle resolution, batch lookup, semantic discovery, lookalikes, posts, transcripts, YouTube search, matching, and comparison rendering. Gaps are minor—there is no creator shortlist persistence or cross-platform comment support—but the main discovery-to-match path has no dead ends.