Skip to main content
Glama

Hyperhuman

Create drop

create_drop

Creates a social drop from an exercise, exercise group, workout, or program. Use when the user wants to create social media content from existing content.

Input Schema

NameRequiredDescriptionDefault
titleNo
localeNo
team_idNo
source_idNo
source_idsNo
source_typeYes

Output Schema

NameRequiredDescriptionDefault
_viewTypeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds nothing beyond that: it does not say whether the drop is published immediately or only drafted, whether repeated calls create duplicates, or what permissions/team scoping apply. For a mutation tool that generates outward-facing content, that is a real gap.

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 short sentences with the action statement first and the usage condition second; no filler. It could have been tighter with a third line covering the single-vs-batch source option, but nothing present is wasted.

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

Completeness2/5

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

An output schema exists, so return values need not be explained. Still, with six completely undocumented parameters, an unusual anyOf requirement structure, and no behavioral detail about what creating a drop actually does, the description leaves an agent under-equipped for a mutating, content-generating tool.

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

Parameters2/5

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

Schema description coverage is 0% across six parameters. The description only implicitly ties source_type to the four source kinds; it does not explain the anyOf choice between source_id and source_ids, the 7-item cap on source_ids, or what title, locale and team_id control. It compensates for only a small fraction of the missing schema documentation.

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

Purpose4/5

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

The description gives a specific verb plus a well-scoped resource ('Creates a social drop') and enumerates the four valid source kinds, which maps directly onto the source_type enum. It is clear what the tool produces, but it does not differentiate itself from nearby siblings such as export_drop, update_drop, or regenerate_drop_copy.

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

Usage Guidelines3/5

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

'Use when the user wants to create social media content from existing content' supplies a clear triggering intent. However, there are no exclusions and no named alternatives, so an agent must infer on its own why it would pick this over export_drop or regenerate_drop_copy.

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.

Resources