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Glama

Finish giveaway

finish_giveaway
Destructive

Finalize a giveaway by selecting winners from a list of participants.

Instructions

Rate limit: 100 requests / 10 seconds per shop. See Rate limiting.

Finish giveaway and select winners

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesNative id
accountNoExact private shop profile label; not a provider identity or authorization proof.
confirmNoExplicit approval for this exact provider effect or local private-file operation.
payloadNoComplete current native JSON body; cannot mix with native body flags or payload_file.
participantsNo
payload_fileNoAbsolute regular non-symlink native JSON body file, at most1MiB. Cannot mix with payload or body flags.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare destructiveHint=true, idempotentHint=false, readOnlyHint=false and openWorldHint=true, so the safety profile is largely covered. The description adds a useful operational constraint (100 requests / 10 seconds per shop), but omits what an agent most needs to know here: that selecting winners is irreversible and presumably requires the confirm/approval flow surfaced in the schema.

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 lines with no filler. The only structural nit is ordering: the rate-limit boilerplate is front-loaded ahead of the actual statement of what the tool does, which is the more important content for tool selection.

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?

For a destructive, non-idempotent, open-world mutation with 6 parameters, nested objects and no output schema, the description is far too thin: it never warns that finishing is irreversible, never distinguishes the two 'finish/giveaway' siblings, and never explains the confirm/payload/payload_file parameter families an agent must reason about.

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 83%, so the schema already documents id, account, confirm, payload and payload_file. The description adds no parameter-level meaning (e.g. the participants vs payload vs payload_file distinction) beyond what the schema provides, so the baseline 3 applies.

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?

"Finish giveaway and select winners" gives a specific verb (finish) and resource (giveaway) plus the concrete consequence of the call. However, it does not distinguish itself from the near-identical sibling finish_giveaway_draw (nor from create_giveaway / create_giveaway_checkout), so an agent cannot tell from the description alone which of these two 'finish' tools to pick.

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?

The description states no when-to-use condition, no prerequisites, and never names an alternative. A rate-limit line is the only operational guidance, and it does not help the agent choose between finish_giveaway and finish_giveaway_draw.

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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