Skip to main content

Agent Skills

** PARITY GAP**: Grok One-Shot does not currently implement the Agent Skills system described in this document. This is a Claude Code feature planned for future implementation.

What Are Agent Skills?

Agent Skills are modular capabilities that extend an AI agent's functionality through organized folders containing instructions, scripts, and resources. Each Skill consists of a SKILL.md file with instructions that the AI reads when relevant, plus optional supporting files.

Status in Grok One-Shot

Current Status: Not Implemented

What Skills Enable (in Claude Code):

  • Extend AI capabilities: Package expertise into discoverable capabilities
  • Model-invoked: AI autonomously decides when to use them based on your request
  • Share expertise: Distribute Skills across teams via git or plugins
  • Reduce repetitive prompting: Encode common workflows as reusable Skills
  • Compose functionality: Combine multiple Skills for complex tasks

Example Use Cases:

  • PDF processing (extract text, fill forms, merge documents)
  • Code review checklists and standards
  • Project-specific workflows (deployment, testing, documentation)
  • Data analysis pipelines
  • Custom linting and validation

Alternative Approaches in Grok One-Shot

Since Skills aren't available yet, you can achieve similar outcomes through:

1. Project Context in GROK.md

Use the project's GROK.md file to encode domain knowledge and workflows:

# GROK.md

## PDF Processing

When working with PDF files:
1. Use `pypdf` for text extraction
2. Use `pdfplumber` for table extraction
3. Use `reportlab` for PDF generation

Example commands:
\`\`\`python
import pdfplumber
with pdfplumber.open("doc.pdf") as pdf:
text = pdf.pages[0].extract_text()
\`\`\`

## Code Review Standards

Always check:
- Error handling in all async functions
- Input validation for public APIs
- Test coverage for business logic
- Documentation for exported functions

2. Documentation in .agent/docs/

Create detailed guides in your project's .agent/docs/ directory:

# Project structure
.agent/
├── docs/
│ ├── workflows/
│ │ ├── pdf-processing.md
│ │ ├── deployment.md
│ │ └── code-review.md
│ └── standards/
│ ├── testing.md
│ └── security.md
└── docs-index.md

Grok One-Shot will load these on-demand when relevant.

3. Custom Slash Commands (Future)

Once custom slash commands are supported, you could create reusable prompts:

# .grok/commands/review-code.md (future)
---
description: Review code for best practices and potential issues
---

Review the specified code for:
1. Code organization and structure
2. Error handling
3. Performance considerations
4. Security concerns
5. Test coverage

4. Shell Scripts with MCP

Create helper scripts and expose them via MCP servers:

# scripts/pdf-extract.sh
#!/bin/bash
python3 -c "
import pdfplumber
import sys
with pdfplumber.open(sys.argv[1]) as pdf:
for page in pdf.pages:
print(page.extract_text())
" "$1"

Then reference these scripts in your GROK.md.

5. Session-Level Instructions

Provide detailed instructions at the start of each session:

> I'm working on PDF processing. When I ask you to extract PDF data, use pdfplumber for tables and pypdf for text. Always validate the file exists first and handle errors gracefully.

When Skills Are Implemented

Future Skills structure in Grok One-Shot would likely be:

~/.grok/skills/ # Personal Skills
.grok/skills/ # Project Skills
└── pdf-processing/
├── SKILL.md # Main skill definition
├── reference.md # Additional documentation
└── scripts/
└── extract.py # Helper scripts

Example SKILL.md (future):

---
name: pdf-processing
description: Extract text, fill forms, merge PDFs. Use when working with PDF files or when the user mentions PDFs, forms, or document extraction.
allowed-tools: Read, Write, Bash
---

# PDF Processing

## Instructions
1. Use pdfplumber for text extraction
2. Use pypdf for form filling
3. Always validate input files exist
4. Handle errors gracefully

## Examples
[Examples would go here]

Comparison: Skills vs Alternatives

FeatureSkills (Claude Code)GROK.md.agent/docs/
Auto-discoveryYes (model-invoked)No (always loaded)Yes (on-demand)
ShareableVia pluginsVia gitVia git
Tool restrictionsYes (allowed-tools)NoNo
Multiple filesYesSingle fileYes
Progressive loadingYesNoYes

See Also


Want this feature? Consider:

  • Opening a feature request in the Grok One-Shot repository
  • Using GROK.md and .agent/docs/ as interim solutions
  • Creating comprehensive documentation for your workflows

Last Updated: 2025-11-07