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Clueso

by io.clueso

Add a sync point at a word + timestamp

add_sync_point

Insert one sync marker on a clip's transcript.

Use this when:

  • The user is explicit about WHERE the camera should pause / cut (e.g. "sync the word 'submit' to 4.2s of the demo").

  • auto_sync ran but missed a step you care about.

How matching works:

  • word: case-insensitive, punctuation-stripped. The first match in the transcript is used unless occurrence > 1.

  • occurrence: 1-indexed — pass 2 to target the SECOND time that word appears, 3 for the third, etc. Required when the word repeats.

  • timestamp_seconds: clip-relative seconds. When the clip has run TTS already (generated_timestamps present), the server inverse-maps this to original-recording seconds automatically.

Constraints: the clip MUST be a video clip with a source recording (otherwise the frame thumbnail can't be extracted). The transcript must already contain the word — if not, you'll get word_not_found with a 200-char excerpt of the transcript to help you retry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
wordYesTarget word (case-insensitive; trailing punctuation is stripped).
clip_idNoClip ID (preferred). If omitted, clip_index is used.
clip_indexNoZero-based clip index. Ignored if clip_id is provided.
occurrenceNo1-indexed match number when the word repeats. Defaults to 1 (first occurrence).
project_idYesProject ID.
sync_point_nameNoOptional label (e.g. 'Click submit'). Defaults to 'Sync point N' using the next order number.
timestamp_secondsYesClip-relative timestamp in seconds. Auto-mapped to original-recording seconds when the clip has generated_timestamps.

TDQS

A4.5/5.0
Behavior4/5

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

The annotations already indicate destructiveHint=false, readOnlyHint=false, and openWorldHint=false, so the description does not need to cover safety again. However, the description adds valuable behavioral context: it explains how word matching works (case-insensitive, punctuation-stripped, first match by default), the role of the occurrence parameter, and the timestamp auto-mapping behavior. It also discloses constraints (clip must be video with source recording, transcript must contain the word) and error handling (word_not_found with excerpt). This enriches the agent's understanding beyond annotations, though a minor gap is lack of detail on what happens after insertion (e.g., is the clip modified in place? Are there side effects on other sync points? Still, 4 is justified for solid transparency.

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?

The description is structured with a brief introduction, bullet-style usage guidance, and detailed notes on matching and constraints. The information is front-loaded with the core action and when-to-use, followed by specifics. It is not excessively verbose, but the 'How matching works' section could be slightly tighter. Overall, it earns its length and is easy to parse.

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?

Given the tool's complexity (7 parameters, 3 required, no output schema), the description covers the core semantics, matching logic, constraints, and error handling. It explains inputs well but does not describe the output or return value (e.g., what the agent receives after success, or how to interpret the result). Since there is no output schema, the agent would benefit from knowing the response format (e.g., sync point ID, confirmation). Nonetheless, for a mutation tool with no output schema, the description is largely complete for guiding correct invocation.

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 description coverage is 100%, so the schema already documents all parameters' types and basic roles. The description adds significant meaning beyond the schema: it explains the matching semantics for 'word' (punctuation-stripped, first match strategy), clarifies that 'occurrence' is 1-indexed and required for repeated words, and describes the auto-mapping of timestamp_seconds when generated_timestamps exist. It also implies the optionality of sync_point_name and the fallback between clip_id and clip_index. These details are not present in the schema alone and help the agent use parameters correctly. A score of 5 would require explicit examples or edge-case handling, but 4 is strong.

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 uses the specific verb 'Insert' and the resource 'sync marker on a clip's transcript', clearly distinguishing its purpose from sibling tools like 'auto_sync' (which runs automatic sync) and 'split_clip' (which cuts the clip). It states the tool adds a sync point at a specific word and timestamp, leaving no ambiguity.

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?

The description explicitly states when to use this tool: 'when the user is explicit about where the camera should pause/cut' and 'when auto_sync ran but missed a step you care about'. It also implies when not to use it (rely on auto_sync for automatic syncing) and gives context about matching behavior and constraints, providing clear guidance for the agent.

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

A4.1/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but there is notable overlap between remove_elements and remove_from_project(target='element'), which both remove elements from a clip. This duplication could cause an agent to misselect. Otherwise, tools like add_clips, add_elements, add_audio, and analyze_audio are well-differentiated.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern (e.g., add_clips, create_project, get_clip, update_elements). There are no camelCase or mixed conventions. Even compound names like voiceover_batch and auto_sync fit the pattern. This makes the tool set predictable for an agent.

Tool Count2/5

With 40 tools, the set is significantly larger than the 3-15 range that typically earns its place. While the domain of video creation is broad, several tools seem redundant (remove_elements vs remove_from_project) or narrowly scoped (get_design_guide, get_element_schema), inflating the count. The number feels heavy for the apparent scope.

Completeness4/5

The tool surface covers most lifecycle operations: create, read, update, delete for projects, clips, elements, audio, articles, and clueprints. Minor gaps exist, such as no explicit tool to delete a voiceover (only mute via update_clips) and no folder management beyond listing. Overall, agents can accomplish full workflows with few workarounds.

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