Playbook

Get assets

get_assets

Read-only

Get full details for up to 100 assets in ONE call — the batch form of get_asset. Use it after list_assets or a search to read the fields those rows do not carry: description, colors, source_url, custom fields, dimensions and comment counts. Prefer it over calling get_asset in a loop; a 60-asset board is one call, not sixty. Tokens that do not exist, or that you cannot see, come back in not_found rather than failing the whole call — check it, because a missing asset is otherwise indistinguishable from one you forgot to ask for. Grouped child assets ARE returned here, unlike in list_assets, which lists only top-level rows.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "asset_tokens": "<asset_tokens>"
    },
    "name": "get_assets"
  }
}

Input Schema

Name	Required	Description
`asset_tokens`	Yes	Asset tokens to read (1-100 per call). The parameter name is `asset_tokens`, not `tokens`. Split a larger set and call again.
`organization`	No	Workspace slug, as returned by list_organizations. Omit it when the account has a single workspace — it is then resolved from your token. Pass it only when the account has several, or when you mean a workspace other than the obvious one.
`get_ai_payload`	No	Include each asset's `ai_agent_payload`. Default false here, UNLIKE get_asset, which always returns it: each payload can be up to 4 KB, so 100 of them is a very large response. The key is absent rather than null when not asked for.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 3, 2026
- removedInput schema / additionalProperties
```
Removed value: -false
```

Changed3 schema fields changedOct 5, 2026

addedInput schema / additionalProperties
```
Added value: +false
```

removedInput schema / properties / context

Removed value: -{
-  "description": "Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\"",
-  "type": "string"
-}

changedInput schema / required

Previous value: -[
-  "asset_tokens",
-  "context"
-]New value: +[
+  "asset_tokens"
+]

First observedOct 2, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already establish readOnly/non-destructive/no-open-world, and the description adds value beyond them: partial-failure semantics (missing or invisible tokens land in `not_found` instead of failing the call), the reason that key must be checked, and the inclusion of grouped child assets. These are non-obvious behaviors that annotations cannot express and that materially change how an agent interprets the response.

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-loaded with the core action and the batch framing, then layered with alternatives, failure behavior, and the list_assets contrast in descending order of importance. Every clause carries information — even the em-dash asides ("a 60-asset board is one call, not sixty") teach a usage heuristic rather than padding.

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?

There is no output schema, so the description must carry return semantics, and it does: it enumerates the field types only present here (description, colors, source_url, custom fields, dimensions, comment counts) and names the `not_found` key. For a 3-parameter read tool with full annotation and schema coverage, nothing an agent needs to invoke it correctly is missing.

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%, and the schema itself already documents the asset_tokens name caveat, the 1-100 limit, the organization resolution rule, and the get_ai_payload size tradeoff versus get_asset. The description adds the batching rationale but no parameter-level detail beyond what the schema provides, so the baseline of 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?

"Get full details for up to 100 assets in ONE call — the batch form of get_asset" names the specific verb, the resource, and the batch scope in one line, and immediately anchors it against the singular sibling get_asset. The later contrast with list_assets (which "lists only top-level rows") removes any ambiguity about which of the three retrieval tools to pick.

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?

Explicitly states the triggering context ("Use it after list_assets or a search") and the anti-pattern to avoid ("Prefer it over calling get_asset in a loop; a 60-asset board is one call, not sixty"). It also names a behavioral difference from list_assets regarding grouped child assets, which is exactly the kind of when-to-choose guidance an agent needs.

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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