recommendation-letter-assistant

What This Skill Does

The Recommendation Letter Assistant is a specialized AI agent skill designed to help faculty and mentors generate standardized, high-quality letters of recommendation for students and mentees. It bridges the gap between raw, unstructured information about a candidate and the formal, nuanced writing style required by academic institutions and hiring committees. By leveraging a structured execution path, this skill ensures that letters remain consistent, evidence-based, and aligned with professional norms. It utilizes a packaged Python script (scripts/main.py) to process user-provided data, applying templates and predefined heuristics to draft content that minimizes bias and maximizes impact. The assistant relies on reference materials stored in the references/ directory, allowing it to adapt to specific institutional requirements or industry standards while ensuring the final output is both reviewable and reproducible.

Installation

To integrate this skill into your OpenClaw environment, use the following command in your terminal:

clawhub install openclaw/skills/skills/aipoch-ai/recommendation-letter-assistant

Ensure that you have Python 3.10 or higher installed, as this is the baseline for the script's execution. It is recommended to verify the installation immediately after by running python -m py_compile scripts/main.py to ensure all dependencies are resolved.

Use Cases

This skill is ideal for faculty members managing high volumes of recommendation requests. Common use cases include: drafting letters for PhD, Masters, or Undergraduate admissions; providing endorsements for scholarship applications; writing professional references for internships; and standardizing the tone and structure of letters across different departments. It is particularly useful when the mentor has the necessary data (e.g., student CV, project performance, specific milestones) but lacks the time to draft a polished, formal document from scratch.

Example Prompts

1. "Draft a strong recommendation letter for Sarah Jenkins for her PhD application to MIT, highlighting her research performance in my Advanced Robotics course and her contribution to the 2024 autonomous drone project."
2. "Write a standard internship recommendation letter for David Chen, focusing on his technical skills in Python and his collaborative efforts during our team's summer research phase."
3. "Generate a letter of support for Maria Garcia's scholarship application, emphasizing her leadership role in the IEEE student chapter and her academic consistency over the last three semesters."

Tips & Limitations

To get the best results, always provide clear, bulleted factual data about the candidate before running the script. The tool is most effective when given explicit anecdotes rather than vague praise. Note that this skill is a writing assistant and not an autonomous decision-maker; all generated letters should be reviewed by the faculty member to ensure accuracy and personal tone. The assistant is bounded by the templates provided in the references/ folder; if you require a highly specific or non-standard format, you may need to update the configuration or reference files accordingly.