describe_project
Return a compact, human-readable summary of the current project — dimensions, fps, duration, an element breakdown by type, a per-track timeline (paint order low→high), and render-time warnings. Much cheaper to read than get_project's full JSON; use it to orient yourself or sanity-check structure ...
This record as markdown: /tools/dev-clipkit-clipkit/describe-project.md
What describe_project does on Clipkit
AI agents call describe_project to retrieve information from Clipkit without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
project_id | string | — | Which project to act on — the id returned by create_project / set_project / create_promo / load_project. Omit when working on a single local project. |
Parameters from the server's own tool schema.
Why describe_project is rated Low
describe_project retrieves and queries project metadata for inspection purposes only. It produces no modifications, executions, deletions, or financial effects. The lower cost compared to get_project and its use case (orientation, structure validation) confirm it is a pure Read operation with minimal blast radius if misused.
From the tool's definition Tool description states it 'Return[s] a compact, human-readable summary' and is 'Much cheaper to read than get_project's full JSON.' The verb 'describe' and explicit framing as a read-only orientation/sanity-check operation confirm no side effects.
Attacks that exploit this kind of access
The rule that runs describe_project safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Clipkit, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For describe_project, this is the rule to start with:
describe_project is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Clipkit, apply this rule, and every describe_project call is checked against it from then on.
Questions about describe_project
Return a compact, human-readable summary of the current project — dimensions, fps, duration, an element breakdown by type, a per-track timeline (paint order low→high), and render-time warnings. Much cheaper to read than get_project's full JSON; use it to orient yourself or sanity-check structure without dumping the whole source. It is categorised as a Read tool in the Clipkit MCP Server, which means it retrieves data without modifying state.
describe_project accepts 1 parameter: project_id. The full parameter table on this page comes from the server's own tool schema.
Register the Clipkit MCP server in PolicyLayer and add a rule for describe_project: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Clipkit. Nothing to install.
describe_project is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the describe_project rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for describe_project. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
describe_project is provided by the Clipkit MCP server (https://www.clipkit.dev/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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