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czwziy

scholar-toolkit-mcp

by czwziy

harness_init

Sets up project infrastructure for academic writing, creating a structured harness directory with writing rules, verification scripts, and a review checklist to enforce quality standards.

Instructions

Initialize harness infrastructure for academic paper writing.

Creates the following structure in the project directory:

  • CLAUDE.md: Project map for AI Agent (in project root)

  • .harness/: Harness directory containing:

    • rules.md: Writing rules (R0-R9)

    • verify.py: Automated verification script

    • checks/: Verification rule implementations

    • specs/manuscript-spec.yaml: Configurable standards

    • checklist.md: Manual review checklist

    • Harness.md: Usage guide

Args: project_dir: Target project directory path. Defaults to current working directory. force: If True, overwrite existing .harness/ directory. Defaults to False.

Returns: JSON string with initialization status and next steps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
forceNo
project_dirNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that files are created in the project directory and that force overwrites existing .harness/. This is sufficient, though it could mention any potential side effects or permissions needed.

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 well-structured with a summary, then a bullet list of created files, then Args. It is front-loaded and each sentence adds value, though it could be slightly more concise.

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?

The description covers the tool's purpose, created artifacts, parameters, and return value. Given the presence of an output schema and the tool's simplicity (init with only creation side effects), it is complete enough for correct invocation.

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

Parameters5/5

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

With 0% schema description coverage, the description compensates by detailing both parameters: project_dir (path, default) and force (overwrite behavior). This adds meaning beyond the schema's defaults and titles.

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 uses a specific verb ('Initialize') and clearly identifies the resource ('harness infrastructure for academic paper writing'). It lists the created files and structure, which distinguishes it from siblings like harness_list_rules and harness_verify.

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 does not explicitly state when to use this tool versus its siblings. While it is implied to be the first step before harness_verify, there is no direct guidance on prerequisites or exclusions.

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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