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Auto-Scan Project Dependencies

gt_auto_scan
Read-onlyIdempotent

Automatically detect project dependencies and fetch best practices, security, or migration guidance for each library.

Instructions

Automatically detect all dependencies in a project and fetch latest best practices for each. Say "use gt" to invoke.

Reads: package.json, requirements.txt, pyproject.toml, Cargo.toml, go.mod, pom.xml, composer.json, build.gradle — whichever exist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectPathNoAbsolute path to the project directory. Defaults to current working directory. The tool will read package.json, requirements.txt, Cargo.toml, go.mod, etc.
topicNoWhat to look up for each detected dependency. Examples: 'latest best practices', 'security', 'performance', 'migration'. Leave empty for general best practices.
tokensPerLibNoMax tokens per library (default: 1500). Lower = more libraries covered.
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint, covering safety. The description adds specific behavioral context: the tool scans certain file types (package.json, etc.). This adds value beyond annotations, earning a 4.

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 very short (two sentences plus a list) and front-loaded. Every sentence provides essential information. The invocation hint 'Say "use gt" to invoke' is minor but does not detract. Very efficient.

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

Completeness3/5

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

Parameters are well documented via schema and description, and annotations provide safety context. However, there is no output schema or description of what the tool returns (e.g., format of best practices). Given the tool's complexity (scanning and fetching), this is a moderate gap.

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 100%, so baseline is 3. The description does not add meaning beyond the schema; it repeats file lists already in projectPath description. No new value for parameters.

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

Purpose4/5

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

Description clearly states the tool detects dependencies and fetches best practices. The verb 'detect' and 'fetch' and resource 'project dependencies' are specific. However, it does not explicitly differentiate from siblings like gt_best_practices or gt_resolve_library, so not a 5.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives. The description lists file types it reads, implying usage in projects with those files, but does not state when not to use or provide alternative tools. This is a significant gap.

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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