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Run a script that calls these tools

run_script
Destructive

Write a JavaScript program that calls this server's other tools. You have the whole language: loops, arithmetic, functions, conditionals, and values carried from one call into the next — all running next to the tools instead of across the conversation. Use it whenever code says the thing more directly than a sequence of separate calls would, which is often.

COMPUTE, don't hand-write. Anything you would otherwise work out in your head and type as literals is better computed here — eased keyframe tracks, staggered start times, grid coordinates, derived palettes, positions from measured text widths. This is usually what makes motion look right: sample a curve at ten points and emit the values, rather than guessing four.

DON'T COMMENT THE SCRIPT. Nobody reads it — it runs once and is gone. Comments, blank lines and explanatory names are pure cost here. Write it dense.

The one thing to remember: inside a script you see only what you return or log, so a tool's own rich output (layout measurements, layout_qa, new ids) has to be surfaced deliberately. That also makes a single-call script worthwhile when a read is fat — find takes no projection argument, so logging the 200 characters you need is a real saving.

A fat read is usually better narrowed at the source than filtered here: get_clip takes select, and get_element_schema takes fields (name what you're setting and a 15KB schema becomes ~200 bytes). get_element_schema returns TEXT by default, which you cannot index into — pass format: 'json' when you want to compute over the schema rather than log it.

CALLING TOOLS Every tool except run_script and get_script_job is a global function taking exactly the arguments it takes normally, and returning its parsed result (those two are excluded so a script cannot recurse into itself or poll its own job). Calls are synchronous — do NOT use async/await, and there are no imports.

sleep(ms) waits, synchronously like everything else here. Use it to poll a generation: generate_media and voiceover_batch return before their work lands, and get_clip(select:['busy']) says what is still being written. A sleep longer than the script's remaining time FAILS the run with a budget error rather than overrunning it or returning early (a run that hands off to a background job gets the job budget, and a sleep already waiting picks that up) — and it holds one of the few concurrent script slots while it waits, so poll on the order of seconds, not milliseconds.

const p = create_project({ title: "Launch" }); const made = add_clips({ project_id: p.projectId, kind: "blank", clips: [{ duration: 4 }] });

Use the BARE tool name. If your client shows these tools under a prefix, the prefixed form works too — mcp__clueso_connect__add_elements and clueso__add_elements both resolve to add_elements. tools() lists every callable name; call(name, args) invokes one by a name computed at runtime.

WHY IT IS CHEAPER What you construct never passes through the conversation. Build an array in a loop and send it in ONE batched call — a 24x24 dot grid is six lines here versus 576 elements of JSON:

const els = []; for (let r = 0; r < 24; r++) for (let c = 0; c < 24; c++) els.push({ x: c * 60, y: r * 60, width: 8, height: 8, type_data: { backgroundColor: "#C462F5" } }); add_elements({ project_id, defaults: { clip_index: 0, element_type: "rectangle" }, elements: els });

READ, THEN WRITE — this is how you edit in bulk:

const clip = get_clip({ project_id, clip_index: 0, select: ["elements.name", "elements.y"] }); const captions = clip.elements.filter(e => e.name.startsWith("caption")); update_elements({ project_id, defaults: { clip_index: 0 }, updates: captions.map(e => ({ element_id: e.id, y: e.y + 40 })) });

WHAT COMES BACK return a value to hand it back, and console.log anything you want to see — that output is all you pay for, so log summaries, not payloads. print_json(obj, maxBytes) logs an object and truncates it for you, which is safer than hand-rolling JSON.stringify(...).slice(...) at every call site. You get { ok, calls, writes_applied, result, stdout }. writes_applied matters because a script is NOT a transaction: if it throws on call nine, the first eight writes already landed, and that count is how you tell. A FAILED TOOL CALL THROWS. It does not return an error object, so a failure stops the script instead of letting it run on against bad state. Wrap a call in try/catch only when you genuinely intend to continue. You get every tool's normal result, so succeeded/failed counts, per-element layout (font_size_px, text_width_px, natural_width_px, line_count, fits_width/fits_height/fits plus adjusted when your height was replaced — widen to natural_width_px, not text_width_px) and layout_qa findings are all readable in the script. Check them and react. NO IMAGES are returned inside a script — a render in a loop would flood the reply. But you are not blind: get_clip({..., render: { save: true }}) gives the script a presigned_url and s3_key for the rendered frame, so it can render many frames, keep the URLs, and hand them on (update_clueprint takes one as source_url). _images_omitted counts the frames withheld; when the reply would be a bare array it arrives as {items, _images_omitted}. Call get_clip yourself, outside a script, when YOU need to look at one.

FINISHING Fast scripts return their result here. If one is still running after wait_seconds (default 45s) you get { job_id, status: "processing" } and it keeps running — poll get_script_job. Set idempotency_key on anything that builds, so a retry cannot run it twice — a key that already ran is never re-executed, failed runs included.

LIMITS: 200 tool calls, 45s of run time inline and 5 minutes once it hands off to a job, 16KB each of logged output and returned value. dry_run runs reads for real and only records writes. Anything costing credits errors as it normally would.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesJavaScript. Tools are globals called synchronously — no async/await, no imports, no network or filesystem. `return` a value to hand it back.
dry_runNoRead-only tools still run; anything that writes is recorded and skipped. Use it to check what a script would do before it does it.
wait_secondsNoHow long to hold this call open waiting for the script, default 45s. If it finishes in time you get the result here; if not you get a job_id to poll with get_script_job, and the script keeps running either way.
idempotency_keyNoPass a unique string so a retry cannot run the same build twice. If a script with this key already ran in this workspace, its job is returned and nothing executes again — including when that run FAILED, because a script is not a transaction and the writes it made before failing are still there. To act after a failure, read the project, repair what landed, and use a NEW key. Worth setting for anything that builds.
timeout_secondsNoWall-clock budget for the SCRIPT — separate from wait_seconds, which is only how long this call stays open. By default a script gets 45s while you are waiting on it, and is raised to 5 minutes the moment it outlives the wait and becomes a job you poll with get_script_job. Set this only to override BOTH with one fixed budget. Watch the slow tools: analyze_audio in 'transcript' or 'beats' mode, export_project and auto_sync take tens of seconds each and will eat a budget fast. analyze_audio in 'features' mode is ~1s and is fine to loop over.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / timeout_seconds / description
      Previous value: -"Wall-clock budget, default 45s. Raise it only if your client's own request timeout is longer — many cut off at 60s, and a script killed by the client reports nothing at all. Watch the slow tools: analyze_audio in 'transcript' or 'beats' mode, export_project and auto_sync take tens of seconds each and will eat a budget fast. analyze_audio in 'features' mode is ~1s and is fine to loop over."New value: +"Wall-clock budget for the SCRIPT — separate from wait_seconds, which is only how long this call stays open. By default a script gets 45s while you are waiting on it, and is raised to 5 minutes the moment it outlives the wait and becomes a job you poll with get_script_job. Set this only to override BOTH with one fixed budget. Watch the slow tools: analyze_audio in 'transcript' or 'beats' mode, export_project and auto_sync take tens of seconds each and will eat a budget fast. analyze_audio in 'features' mode is ~1s and is fine to loop over."
  2. 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: -[
      -  "code",
      -  "context",
      -  "llm_model"
      -]New value: +[
      +  "code"
      +]
  3. 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: -[
      -  "code"
      -]New value: +[
      +  "code",
      +  "context",
      +  "llm_model"
      +]
  4. 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
  5. Added

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the destructiveHint annotation, the description discloses critical behaviors: scripts are not transactions and partial writes persist; failed tool calls throw; execution is synchronous with no async/await; images are omitted inside scripts and replaced with `_images_omitted`; there are explicit budget/timeout limits; and idempotency applies even to failed runs. None of this contradicts the annotations.

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 long but well-organized with clear section headings and illustrative examples. The length is largely justified by the tool's complexity, and the key guidance is front-loaded. A slight deduction because some constraints (no async/await, no imports) appear in both the description and the schema, and the overall word count verges on over-explaining.

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 that there is no output schema, the description fully compensates by explaining the return shape (`{ ok, calls, writes_applied, result, stdout }`), the job-handoff mechanism, error behavior, limits, and what the script can observe (layout metrics, layout_qa). The agent has everything needed to call this tool correctly across the common and edge cases.

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?

Even though schema coverage is 100%, the description adds substantial operational meaning: `code` gets global-call restrictions, `dry_run` is clarified as executing reads for real while recording writes, `wait_seconds` vs `timeout_seconds` are sharply distinguished (wait time vs wall-clock script budget), and `idempotency_key` is explained with its failure-mode semantics. This goes well beyond the schema descriptions.

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 opens with a specific verb and resource: "Write a JavaScript program that calls this server's other tools." It clearly differentiates this tool from its siblings by framing it as an orchestration layer that composes the other tools programmatically, rather than being another domain-specific operation.

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?

It gives explicit when-to-use guidance: "Use it whenever code says the thing more directly than a sequence of separate calls would." It also names exclusions and alternatives, such as narrowing reads with get_clip's `select` and get_element_schema's `fields`, and telling the agent to "Call get_clip yourself, outside a script, when YOU need to look at one."

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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