Scan a project codebase to populate a knowledge graph with entities and relationships, enabling structured analysis of existing code.
Scan the project codebase and populate the knowledge graph with entities and relationships from existing code
| Name | Required | Description | Default |
|---|---|---|---|
| force | No | Re-seed already processed files | |
| project_dir | No | Project directory path (defaults to current) |
Changes observed during successful MCP inspections.
v0.7.3Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states that the tool populates the knowledge graph but does not disclose whether the operation is idempotent, whether it modifies existing data, or any side effects. The 'force' parameter hints at re-seeding but this behavior is not explained in the description.
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 a single sentence, direct, and front-loaded with the main action. 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?
With no output schema or annotations, the description is the sole source of behavioral context. It covers the high-level operation but lacks guidance on prerequisites, idempotency, return values, or potential side effects of running a mutating operation.
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% for both parameters (force and project_dir), so the description does not need to compensate. The description itself adds no parameter semantics beyond the schema.
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 clearly states the tool's function: 'Scan the project codebase and populate the knowledge graph with entities and relationships from existing code'. It uses a specific verb (scan/populate) and resource (codebase, knowledge graph), distinguishing it from siblings like query_fact (query) or record_event (record).
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 implied by the tool name 'seed_project' (initial population), but the description provides no explicit when-to-use guidance or alternatives. No mention of when to run this versus other ingestion tools like ingest_pr_reviews or record_event.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.