get_articleGet the article content as markdown. Screenshots appear as <SCREENSHOT {id}> placeholders. Returns the markdown text and a list of screenshot IDs.
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes | Project ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already confirm readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is clear. The description adds valuable context about the markdown format and how screenshots are represented ('Screenshots appear as <SCREENSHOT {id}> placeholders'), which annotations do not cover.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and every word earns its place. No fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple 1-param, read-only tool with full schema annotation, the description is mostly complete. It explains the return format and screenshot handling. However, it could mention if the markdown includes metadata or if any special error cases exist (e.g., article not found), but this is not a critical gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 the single parameter 'project_id'. The description does not add meaning beyond what the schema provides (e.g., no context on where to find the project ID or what it represents). Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs ('Get the article content') and identifies the resource ('article') and return format ('as markdown'). It distinguishes itself from sibling tools like 'update_article' and 'get_clip' by clearly indicating a read operation returning content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for reading article content and nothing else, but it does not explicitly state when to use this vs. other read tools like 'get_project' or 'get_clip'. No exclusions or alternatives are mentioned.
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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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.
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.
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.
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.