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Vishu-ak

resumeforge

by Vishu-ak

Scaffold a bridge project repo

scaffold_bridge_project

Create a runnable starter repository for a bridge project with health endpoint, tests, CI, docker-compose, README, and build log to turn project gaps into demonstrable code.

Instructions

Generates a runnable starter repository for a bridge project: a Go, Python (FastAPI) or TypeScript service with a /health endpoint and a passing test, CI, a docker-compose for the stack's databases and brokers, a README carrying the build plan, results table and resume-bullet templates, and a BUILD_LOG. Java gets a Spring Initializr command. Pass a project from analyze_gaps or suggest_bridge_projects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jd_textNoUsed to name routes after the company's domain
projectYes
languageNoDefaults to the stack's main language
overwriteNo
output_dirNoLocal mode: parent folder. Defaults to ~/ResumeForge/projects
github_usernameNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations provide no strong safety profile beyond false hints, so the description must carry behavioral context. It usefully discloses generated artifacts (health endpoint, CI, docker-compose, README, BUILD_LOG) and the Java Spring Initializr special case. It does not mention side effects such as file creation/overwrite behavior, output location, or whether github_username triggers remote repository creation, so transparency is only partial.

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 a single information-dense sentence with a clear leading verb and resource, followed by a compact list of generated components and a brief Java exception. Every clause adds relevant detail, though the long enumeration makes it slightly less scannable than ideal.

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?

Given the tool's complexity (nested project object, six parameters, multiple language paths, no output schema), the description is reasonably complete about what gets generated and where the project input comes from. It lacks key invocation details such as overwrite semantics, output directory behavior, GitHub interaction, and what the tool returns after scaffolding, leaving meaningful gaps for an agent.

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 description coverage is 50%, and the description adds meaningful context by stating that the project object comes from analyze_gaps or suggest_bridge_projects and that Java is handled via Spring Initializr. However, it does not explain jd_text, overwrite, output_dir, or github_username beyond what the schema already provides, so it only partially compensates for the uncovered 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?

The description clearly states a specific verb and resource: it generates a runnable starter repository for a bridge project, and enumerates concrete artifacts. It also orients the agent by saying the project should come from analyze_gaps or suggest_bridge_projects, but it does not explicitly distinguish itself from sibling build_application_kit, so it stops just short of 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 Guidelines3/5

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

It implies when to use the tool by instructing 'Pass a project from analyze_gaps or suggest_bridge_projects,' which indicates a prerequisite and likely sequencing. However, it does not state when NOT to use this tool or name an alternative for similar scaffolding tasks, leaving some usage decisions to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.