Fetch project context and recent changes. Use minimal-token mode by default at session start; request full details when needed.
Get project context. Use lean=True (default) for minimal tokens at session start. Use lean=False for full details when needed.
| Name | Required | Description | Default |
|---|---|---|---|
| lean | No | Minimal tokens (default True) | |
| hours | No | Hours back for changes | |
| project_name | Yes | Project name |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnlyHint=true, idempotentHint=true, and openWorldHint=false, so the safety profile is covered. The description adds a token-cost/efficiency tradeoff between lean modes, which is genuine behavioral context, but says nothing about scope limits, data freshness, or what the two modes actually return.
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?
Two tightly written sentences with the core purpose front-loaded before the lean-mode guidance. Nothing is padded, though the second sentence spends its budget on parameter usage rather than on clarifying what 'context' contains.
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?
No output schema exists, so the description should help the agent anticipate what comes back — and it never defines what 'project context' comprises or how lean changes the payload beyond token count. For a read tool with annotations covering safety and a fully documented schema, this is adequate but leaves the key ambiguity unresolved.
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 all three parameters are already documented and baseline is 3. The description slightly enriches lean by tying each value to a use case ('minimal tokens at session start' / 'full details'), but adds nothing for hours or project_name beyond what the schema states.
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 clear verb and resource ('Get project context'), so the agent knows it retrieves something. But 'context' is undefined — it doesn't say whether that means learnings, recent changes, rules, or a summary — and no sibling is named or excluded, despite get_learnings, get_recent_changes, and list_projects sitting adjacent in the toolset.
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?
It says when to use lean=True ('at session start') versus lean=False ('when needed'), which is useful parameter-level guidance. However, it offers no tool-level guidance on when this tool is the right choice over the many other retrieval siblings, which is the more consequential decision.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.