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Get clueprint

get_clueprint
Read-only

Fetch clueprint data. Use include to control how much you pull back:

  • include="metadata": just the clueprint's name/description/tags/visibility/thumbnail.

  • include="tree": metadata + the full file tree (path, mime_type, and size per entry). Call this first when exploring an unfamiliar clueprint.

  • include="files": the contents of the files listed in file_paths (no metadata — call include='tree' first if you also need metadata). Text inline, binary as presigned GET URLs.

  • include="all": metadata + the file tree + the contents of every file in the clueprint (use sparingly on large clueprints).

Calling this also logs the clueprint as "used" (fire-and-forget) so the workspace's recents list stays accurate — no follow-up use_clueprint call needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
includeNoWhat to return: 'metadata' | 'tree' | 'files' | 'all'. Defaults to 'tree'.tree
file_pathsNoinclude='files' only: relative paths to read (e.g. ['design/colors.md', 'rules/voice.md']). Ignored for other modes.
clueprint_idYesID of the clueprint.

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description does not need to reiterate those. It adds significant behavioral context beyond annotations: it explains that calling the tool logs the clueprint as 'used' (fire-and-forget) for the recents list, and that binary files return presigned URLs. This excellent additional detail earns a high score; a 5 would require even more coverage, such as explicit mention of rate limits or size limits on responses.

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?

The description is well-structured with clear sections for each include mode, uses bullet points for readability, and front-loads the key verb. Every sentence provides direct value; there is no fluff or repetition of schema fields. The bonus detail about usage logging is a single, concise sentence at the end.

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 moderate complexity (3 parameters, 1 required, 1 enum) and the absence of an output schema, the description does a good job explaining return formats (metadata vs. tree vs. files with presigned URLs). It covers side effects (usage logging) and best practices for large clueprints. However, it lacks details on pagination or limits for very large clueprints, and the 'all' mode could use more caution about performance. A 5 would address these edge cases.

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 three parameters. The description adds substantial meaning beyond the schema for the 'include' parameter by explaining the effect and best practices for each enum value (e.g., 'metadata + the full file tree' and 'binary as presigned GET URLs'). For 'file_paths', it reinforces the dependency on include='files'. This is useful enrichment, earning a 4; a 5 would require adding similarly rich context for all parameters, which is already done well but not exhaustive for 'clueprint_id'.

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 clearly states the tool fetches clueprint data and uses a specific verb ('Fetch') along with the resource ('clueprint data'). It thoroughly distinguishes the various include modes, making it very clear what each call returns, which differentiates it from siblings like 'create_clueprint' or 'update_clueprint'.

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 provides explicit guidance on when to use each include mode, e.g., 'Call include="tree" first when exploring an unfamiliar clueprint' and 'use sparingly on large clueprints' for 'all'. It tells the agent exactly how to decide between modes, though it does not explicitly mention when not to use the tool, but the guidance is so clear that exclusions are implied. No alternative sibling tool is named for similar operations, but the tool itself covers many use cases.

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.