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tech_stack

Identify the technology stack of a project by scanning manifest and configuration files, returning sorted lists of languages, frameworks, databases, and tools.

Instructions

Detect a project's technology stack from its manifest and config files.

Looks for common manifests (pyproject.toml, requirements.txt, package.json, Dockerfile, docker-compose.yml, GitHub Actions workflows, Cargo.toml, go.mod, composer.json, build.gradle, and more), and inspects package.json / requirements.txt contents for known frameworks and databases.

Args: path: Filesystem path to the repo root.

Returns: Dict with sorted lists for languages, frameworks, databases, package_managers, ci_cd, and deployment, plus the manifest files that were found.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNo.
Behavior3/5

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

No annotations are provided, so the description must carry the full burden. It describes scanning files and inspecting contents, but does not disclose if modifications occur (it is read-only), error handling, or side effects. The return dict is listed, but behavioral details like path validation are missing.

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

Conciseness4/5

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

The description is concise, front-loads the main purpose, and includes Args and Returns sections. Every sentence adds value, though it could be slightly more succinct.

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

Completeness5/5

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

Given one parameter and no output schema, the description fully explains the input and details the return dict (languages, frameworks, databases, etc.). This is complete for the tool's complexity.

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

Parameters4/5

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

Despite 0% schema coverage, the description explains the 'path' parameter as 'Filesystem path to the repo root', adding meaning beyond the schema. This compensates for the schema gap, though no other parameters exist.

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's purpose: detect a project's technology stack from manifests and config files. It lists specific files and inspection details, distinguishing it from siblings which deal with file size, todos, git logs, health, and stats.

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

Usage Guidelines3/5

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

The description implies use for tech stack detection, but no explicit guidance on when to use vs alternatives or when not to use. Sibling tools have distinct purposes, so no direct competition, but no 'when-not' or alternative guidance is provided.

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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