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Viral Manager

get_crew_upload_stats

Read-only

Count the videos delivered by crew members (editors, clippers, posters) per day, week or month. Reads the full upload history: a delivered video still counts after its file was deleted or its assignment purged. Use it for 'how many videos did my editors upload today / this week / on a given date'.

Input Schema

NameRequiredDescriptionDefault
toNoEnd (ISO date or datetime, exclusive). Empty = now.
crewNoOnly this crew member (name or member_id, see list_crew). Empty = everyone.
fromNoStart (ISO date or datetime, inclusive). Empty = 30 days before `to`.
bucketNoPeriod groupingday
timezoneNoIANA time zone used to cut the days, e.g. Europe/ParisUTC

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuinely useful behavior beyond that: it reads full upload history and counts persist even after a video's file is deleted or its assignment purged, which materially affects how an agent should interpret results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tightly written sentences: purpose first, then the non-obvious counting-persistence behavior, then example queries. No filler, and the most important constraint is front-loaded.

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?

For a read-only aggregation tool with a fully documented schema, the description covers purpose, scope, and a subtle counting caveat. It does not sketch the shape of the returned counts (e.g., per-bucket totals), which is a minor gap given there is no output schema.

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 100%, so every parameter (to, from, crew, bucket, timezone) is already documented in the schema. The description echoes the day/week/month grouping but adds no syntax or format detail beyond what the schema provides, making the baseline 3 appropriate.

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?

The description names a specific verb (count) and resource (videos delivered by crew members), plus the grouping granularity (per day/week/month). It is clearly distinguishable from sibling stats tools like get_dashboard_stats or get_my_account_stats, which cover different scopes.

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?

It gives concrete use cases ('how many videos did my editors upload today / this week / on a given date') and scopes the tool to crew-delivered videos. It stops short of naming an alternative tool or stating when not to use it, so it is clear context without explicit exclusions.

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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