Skip to main content
Glama

Starlecta influencer tools

Search influencers by filters

search_influencers
Read-only

Count of matching influencers and up to two open cards. Filters: category code, tier (nano, micro, macro, mega), follower bounds, measured engagement only.

Input Schema

NameRequiredDescriptionDefault
tierNo
categoryNoCategory code, e.g. beauty, fashion_style, tech_business_education
er_measuredNo
followers_maxNo
followers_minNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful behavior: results are capped at a count plus at most two 'open cards', and er_measured is described as measured-engagement-only. However 'open cards' is undefined and there is no note on default behavior with zero filters.

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?

Two compact sentences with no filler. The ordering is slightly off — the return value is front-loaded ahead of what the tool actually does — but nothing is wasted.

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

Completeness3/5

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

For a 5-parameter tool with no required params and no output schema, the description does convey the key return shape (count plus up to two cards). It still leaves the undefined 'open cards', the all-optional default behavior, and result capping rationale unexplained.

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 description coverage is only 20% (category only), so the description must compensate; it partially does by explaining er_measured ('measured engagement only') and restating the tier enum values. It adds nothing for followers_min/followers_max bounds semantics (inclusive? units?) beyond self-explanatory names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description leads with a return-value statement ('Count of matching influencers and up to two open cards') rather than stating the action; the verb 'search' exists only in the name/title. The filter list does imply a filtered influencer search, but nothing distinguishes it from siblings like ai_search_influencers or lookup_influencer.

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

Usage Guidelines2/5

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

No guidance on when to use this versus ai_search_influencers, lookup_influencer, or compare_influencers, and no prerequisites or exclusions. The only usage-ish signal is the phrase 'measured engagement only', which constrains one filter but does not route the agent among alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.