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by io.clueso
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Auto-generate sync points

auto_sync
Destructive

Run the agentic auto-sync pipeline on a clip with a source recording: detects natural sync points (UI changes, narrated steps) and inserts sync-marker nodes into its transcript. Required before voiceover TTS on video clips (clueso://docs/sync-points).

Skips (no run): "audio_extracted" (read-only transcript); "clip_busy" + held_by (retry later); "clip_too_long" + {clip_id, duration_label} (trimmed window over 5 min; never quote the limit): split_clip it into shorter clips and auto_sync each.

Returns once started; markers land a few seconds later, so poll get_clip before TTS.

Input Schema

NameRequiredDescriptionDefault
clip_idYesClip ID to auto-sync.
project_idYesProject ID.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • removedInput schema / properties / context
      Removed value: -{
-  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
-  "type": "string"
-}
    • removedInput schema / properties / conversation_id
      Removed value: -{
-  "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
-  "type": "string"
-}
    • removedInput schema / properties / llm_model
      Removed value: -{
-  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
-  "type": "string"
-}
    • changedInput schema / required
      Previous value: -[
-  "project_id",
-  "clip_id",
-  "context",
-  "llm_model"
-]New value: +[
+  "project_id",
+  "clip_id"
+]
  2. Changed4 schema fields changed
    • addedInput schema / properties / context
      Added value: +{
+  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
+  "type": "string"
+}
    • addedInput schema / properties / conversation_id
      Added value: +{
+  "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
+  "type": "string"
+}
    • addedInput schema / properties / llm_model
      Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[
-  "project_id",
-  "clip_id"
-]New value: +[
+  "project_id",
+  "clip_id",
+  "context",
+  "llm_model"
+]
  3. Changed2 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
  4. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations only say destructive/non-read-only; the description adds the crucial async contract ('Returns once started; markers land a few seconds later'), the concrete mutation (marker nodes inserted into the transcript), and the full set of skip outcomes with their payload fields (held_by, clip_id/duration_label). It is consistent with destructiveHint=true, since transcript content is modified.

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?

Front-loads the action, then the prerequisite, then the skip matrix, then the async return behavior. Dense but zero filler; the compact quoted stop-codes ('clip_busy' + held_by) pack a lot of routing information into few characters.

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?

With no output schema, the description takes on the return contract and does it ('returns once started'), plus polling guidance and failure semantics. An agent has everything needed to decide, call, and follow up correctly.

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

Parameters4/5

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

Schema coverage is 100%, so both parameters are already documented, and the baseline would be 3. The description adds eligibility semantics beyond the schema: the clip must have a source recording and must fall within a roughly 5-minute window, which constrains which clip_id is valid.

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 and resource ('Run the agentic auto-sync pipeline on a clip') plus the mechanism ('detects natural sync points (UI changes, narrated steps) and inserts sync-marker nodes into its transcript'). The 'auto-detect' framing implicitly separates it from the manual sibling add_sync_point.

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

Usage Guidelines5/5

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

Gives an explicit prerequisite ('Required before voiceover TTS on video clips'), enumerates the conditions under which it should not run, and routes the agent in each case: audio_extracted means read-only, clip_busy means retry later, clip_too_long means use split_clip then re-run. It also tells the agent to poll get_clip before TTS.

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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