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qencode

by com.qencode

list_objects

Read-onlyIdempotent

Browse the contents of a Qencode Media Storage bucket.

Args:
    bucket: bucket name (see `list_buckets`). An unknown bucket fails with
        `bucket_not_found`.
    prefix: optional key prefix to filter by (e.g. `raw/`).
    continuation_token: pass the `next_token` from a previous truncated
        response to fetch the next page.

Returns `{objects: [{key, size, last_modified}], is_truncated}` plus
`next_token` when `is_truncated` is true. One call returns up to ~1000
objects; if the bucket (or prefix) holds more, `is_truncated` is true and
you page by re-calling with `continuation_token=next_token`.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bucketYes
prefixNo
continuation_tokenNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
objectsYes
next_tokenNo
is_truncatedYes

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description doesn't need to repeat safety. It adds valuable behavioral details beyond annotations: unknown bucket fails with 'bucket_not_found', one call returns up to ~1000 objects, and the response shape with is_truncated/next_token. This discloses error conditions and pagination behavior, enriching the agent's understanding.

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?

The description is well-structured with Args and Returns sections. It front-loads the purpose in one sentence, then methodically covers each parameter and return behavior. No wasted words; every sentence provides necessary information for correct invocation and pagination handling.

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

Completeness5/5

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

Given the tool's moderate complexity (3 params, pagination, error cases), the description is complete. It includes return shape, pagination mechanics, error behavior, and bucket discovery via list_buckets. Even with an output schema present, the description adds crucial context about limits and failure modes, making it fully sufficient for an agent to use the tool correctly.

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

Parameters5/5

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

With schema description coverage at 0%, the description fully compensates. Each parameter is explained with purpose and example: bucket (with error behavior), prefix (e.g. 'raw/'), and continuation_token (how to use next_token). It also documents the response structure and pagination limit, giving complete semantic meaning beyond the bare 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?

The description clearly states the tool's function: 'Browse the contents of a Qencode Media Storage bucket.' It identifies the resource (bucket objects) and specific actions (listing with prefix filtering and pagination). This distinguishes it from siblings like list_buckets, which lists buckets rather than their contents.

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?

Provides clear contextual guidance: references list_buckets for bucket names, explains prefix filtering with an example, and details pagination using continuation_token. It does not explicitly name alternatives or exclusions, but the cross-reference and pagination instructions convey when and how to use the tool. A minor gap is the lack of an explicit 'use this instead of X' statement.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools are clearly distinct (list_buckets vs list_objects, search vs fetch docs). Minor overlap exists between transcode_video and start_encode2_raw (both submit jobs) and between get_job_status and get_job_status_detailed, but the descriptions explicitly state when to use which, making misselection unlikely.

Naming Consistency4/5

Names overwhelmingly follow verb_noun (create_bucket, list_buckets, get_download_url, transcode_video). A few deviations like start_encode2_raw, wait_for_job, and download_url_to_bucket break the pure pattern, but the convention is still easily predictable.

Tool Count5/5

13 tools is well-scoped for a video encoding platform: bucket management, transcoding submission/status/wait, result retrieval, and docs search/read. Each tool serves a clear purpose without redundancy or bloat.

Completeness4/5

The set covers the main lifecycle: create bucket, ingest via copy, transcode (two entry points), poll status, fetch result, and generate download URLs. Missing cancel/delete operations for jobs and buckets are notable but not critical for core workflows, and the docs tools help fill knowledge gaps.

Resources