get_project_contextRetrieve saved business, audience, product, goal, and agent-rule context for a project so AI agents can apply project-specific instructions.
Read the saved business, audience, products, goals and agent rules for this project.
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes | The public project ID. Project membership and token scopes are enforced. |
Changes observed during successful MCP inspections.
v0.17.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so safety behavior is covered. The description adds only the categories of data returned; it says nothing about permissions beyond the schema's note, volume, or caching, so it is modestly additive.
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?
One front-loaded sentence naming the action and the returned content with zero filler. Nothing could be removed without losing meaning.
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?
With one fully documented parameter and no output schema, the enumeration of returned fields (business, audience, products, goals, agent rules) fills the main gap an agent would have about what comes back. Only the when-to-use context and any permission caveats are missing.
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?
There is a single parameter with 100% schema description coverage, including its format pattern and the membership/token-scope enforcement note. The description adds no parameter-level detail, so the schema carries the full burden and baseline 3 applies.
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?
States a specific verb ('Read') plus the resource ('saved business, audience, products, goals and agent rules for this project'), enumerating exactly what data is retrieved. This clearly separates it from the sibling update_project_context, which mutates the same data.
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?
Usage is only implied by the read verb and the enumerated context fields; there is no explicit statement of when to call this versus alternatives like get_project or update_project_context. Adequate but leaves selection inference to the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.