be-precise

Enforce precise file paths and verification steps for codebase edits.

Updated May 21, 2026
One-click install
npx skills add https://github.com/mica-agent/mica-solar-system --skill be-precise
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: be-precise
Source: https://github.com/mica-agent/mica-solar-system/tree/main/.qwen/skills/be-precise
Command: npx skills add https://github.com/mica-agent/mica-solar-system --skill be-precise

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Prevents vague, speculative actions by enforcing literal precision when writing code, editing files, or using tools in a software repository.

Core Features & Use Cases

  • File- and identifier-level specificity: Requires exact paths, function names, and existing patterns instead of approximate descriptions.
  • Verification-first workflow: Encourages checking for file existence with Glob/Read and using Grep context windows to reduce unnecessary reading.
  • Lean, performance-aware prompting: Promotes concise specificity to reduce drift and unnecessary context load during tool execution.

Quick Start

When you need to change something in the codebase, ask the model to act precisely by naming the exact file paths and functions to inspect or modify.

Frequently Asked Questions about be-precise

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I prevent AI from hallucinating file paths when editing code in a repository?

Preventing AI from hallucinating file paths requires enforcing exact path and identifier usage before making changes. This involves verification steps like using Glob and Read to confirm file existence, reducing speculative actions and context waste.

How do I use Grep context windows to reduce unnecessary file reading?

To reduce unnecessary file reading with Grep context windows, match exact identifiers and return surrounding lines. This focuses context load on validated details instead of reading entire repository files, keeping tool execution performance-lean.

What is the best way to ensure AI uses exact codebase details when running repository tools?

Ensuring exact codebase details when running repository tools involves applying literal precision constraints. Require the model to name exact paths and functions, preventing vague actions and aligning performance with local model constraints.

Why does AI drift away from the original prompt when navigating a large codebase?

AI drifts when navigating large codebases due to excessive context load and vague instructions. Mitigate this by using lean, performance-aware prompting that enforces file-level specificity and verification-first actions to anchor the model.