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Atharva-Jayappa

blast-scope-mcp

index_project

Rebuild or refresh the dependency graph for a project root to force a graph rebuild after large code changes.

Instructions

Build or refresh the dependency graph for a project.

Forces a graph rebuild for the given project root. Normally not required — assess_command auto-builds the graph on first use — but useful to refresh after a large code change.

Args: project_root: Absolute path to the project root directory.

Returns: Status dict confirming the project was indexed.

Example::

index_project("/home/user/my-project")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_rootYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states 'forces a graph rebuild' and returns a status dict, implying a mutation. However, it does not disclose whether the operation is idempotent, requires specific permissions, or has any side effects on the project files. The description is adequate but lacks depth on behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, uses a clear structure with an opening statement, usage guidance, args, returns, and an example. Every sentence adds value and there is no redundancy. It is well front-loaded with the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one required parameter, no output schema, no nested objects), the description covers the essential aspects: purpose, when to use, parameter explanation, return type, and an example. It lacks error scenarios or format validation, but overall it is complete enough for an AI agent to select and invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It explains project_root as 'Absolute path to the project root directory.' This adds basic meaning but does not specify constraints like path must exist, format, or that the project must already be recognized. The description is minimal and barely adds value beyond the parameter name.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool builds or refreshes the dependency graph for a project. It specifies the verb 'build or refresh' and resource 'dependency graph for a project'. It also distinguishes itself from the sibling tool 'assess_command' by noting that this tool forces a rebuild, while assess_command auto-builds on first use.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly provides usage guidance: 'Normally not required — assess_command auto-builds the graph on first use — but useful to refresh after a large code change.' This tells the agent when to use this tool and when not to, directly addressing the alternative sibling tool.

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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