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Starlecta influencer tools

Global Account Check

audit_influencer
Read-only

Reads one public Instagram account live and returns dated, counted metrics: followers, engagement rate over the latest items with n, average likes and comments, median Reel plays, posting frequency, Stories seen now, last post. Public accounts with 10,000+ followers. Not a score. Limited daily. Accounts Starlecta tracks every day show more in lookup_influencer.

Input Schema

NameRequiredDescriptionDefault
handleYesInstagram handle, with or without @

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, and the description adds genuinely new behavioral context: a live (uncached) read, a hard follower threshold that changes success behavior, a daily quota, and the interpretive note 'Not a score'. It doesn't say what happens for private or under-threshold accounts, which would be the natural next disclosure.

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?

Front-loaded with the verb, resource, and return surface, and nearly every clause carries information (eligibility, quota, metric list, sibling routing). The telegraphic fragments ('Not a score. Limited daily.') are dense but slightly ragged to read.

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

Completeness4/5

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

With no output schema, the description compensates by enumerating return fields including sample sizes ('with n') and dated metrics. Combined with the eligibility gate and quota note, an agent has enough to call it correctly; missing only error/failure behavior and any auth prerequisites.

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

Parameters3/5

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

Schema coverage is 100% with a single well-documented handle parameter including a regex pattern, so the schema does the work. The description adds only the implicit constraint that the account must be public and 10k+; it offers no syntax or format detail beyond the schema.

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 ('Reads one public Instagram account live') and immediately enumerates the returned metrics, so the agent knows exactly what the tool produces. It also distinguishes itself from the closest sibling by naming lookup_influencer and describing the difference (daily-tracked accounts show more there).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives concrete eligibility ('Public accounts with 10,000+ followers'), a rate constraint ('Limited daily'), and a routing rule to lookup_influencer for accounts Starlecta tracks daily. It stops short of an explicit 'use this instead of search_influencers/compare_influencers when...' statement, so some inference is still required.

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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