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BulkTranscripts YouTube

by co.bulktranscripts
OverviewDiscussionsAdmin

List a bulk job's results

list_bulk_results
Read-onlyIdempotent

One page of per-video outcomes for a bulk job: video id, title, channel, duration, word count and status (ok, cached, or error with a code). Never includes transcript text; fetch any listed video with get_transcript, which is free once the job has put it in the library. Pass next_cursor from the previous page to continue. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoItems per page, default 50.
cursorNonext_cursor from the previous page; omit for the first page.
run_idYesThe run_id from start_bulk_extract.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
itemsYes
totalNo
run_idYes
statusYes
next_cursorYesPass back as `cursor` for the next page; null on the last page.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "items": {
+      "items": {
+        "properties": {
+          "channel": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "duration": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "error": {
+            "properties": {
+              "code": {
+                "type": "string"
+              },
+              "message": {
+                "type": "string"
+              }
+            },
+            "required": [
+              "code",
+              "message"
+            ],
+            "type": "object"
+          },
+          "position": {
+            "type": "integer"
+          },
+          "status": {
+            "description": "ok, cached, error, skipped or quota.",
+            "type": "string"
+          },
+          "title": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "url": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "video_id": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "word_count": {
+            "type": [
+              "integer",
+              "null"
+            ]
+          }
+        },
+        "required": [
+          "position",
+          "status"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "next_cursor": {
+      "description": "Pass back as `cursor` for the next page; null on the last page.",
+      "type": [
+        "integer",
+        "null"
+      ]
+    },
+    "note": {
+      "type": "string"
+    },
+    "run_id": {
+      "type": "string"
+    },
+    "status": {
+      "type": "string"
+    },
+    "total": {
+      "type": "integer"
+    }
+  },
+  "required": [
+    "run_id",
+    "status",
+    "items",
+    "next_cursor"
+  ],
+  "type": "object"
+}
  2. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds meaningful traits beyond them: the result set 'never includes transcript text', the enumerable status values (ok, cached, error with a code), pagination via next_cursor, and that the call is free. Return format detail is modest but the added constraints are genuinely useful.

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?

Four short sentences, zero filler, and the most decision-relevant facts (scope, content exclusion, alternative tool, pagination) are front-loaded before the trailing cost note.

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?

For a paginated read tool with an output schema, safety annotations, and full schema coverage, the description supplies everything an agent needs: scope, status vocabulary, pagination mechanics, cost, and the follow-up tool for transcripts.

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 both limit and cursor are already documented in the schema. The description's cursor guidance ('Pass next_cursor from the previous page') restates the schema rather than adding new syntax or edge-case meaning, so the baseline 3 applies.

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?

States a specific verb+resource ('One page of per-video outcomes for a bulk job') and enumerates the returned fields (video id, title, channel, duration, word count, status). This clearly separates it from get_bulk_status (job-level status) without the agent needing to open either schema.

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?

Explicitly routes transcript retrieval to the sibling tool: 'fetch any listed video with get_transcript, which is free once the job has put it in the library.' It also explains continuation via next_cursor. It doesn't explicitly compare against get_bulk_status, but the conditions for use are clear.

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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