Helps faculty and mentors draft standardized recommendation letters for.
26
17%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/Academic Writing/recommendation-letter-assistant/SKILL.mdQuality
Discovery
22%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This description is truncated mid-sentence and critically incomplete, failing to convey what the skill fully does or when it should be used. It has a narrow domain hint (recommendation letters for faculty/mentors) but lacks concrete actions, trigger terms, and a 'Use when...' clause. The incomplete sentence significantly undermines its utility for skill selection.
Suggestions
Complete the truncated sentence and add specific actions such as 'Drafts, customizes, and formats academic recommendation letters with standardized structure, tone adjustment, and student-specific details.'
Add an explicit 'Use when...' clause with trigger terms like 'recommendation letter', 'letter of recommendation', 'reference letter', 'LOR', 'academic reference', or 'student recommendation'.
Include common variations and file types users might mention, such as 'graduate school applications', 'scholarship recommendations', or 'faculty endorsements' to improve trigger term coverage.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description mentions 'draft standardized recommendation letters' which is a single vague action. The sentence appears truncated ('letters for.'), and it doesn't list concrete capabilities like formatting, customizing tone, or generating specific sections. | 1 / 3 |
Completeness | The 'what' is weakly stated and the sentence is truncated, making it incomplete. There is no 'when' clause or explicit trigger guidance, and the description literally ends mid-sentence with 'for.' which suggests critical information is missing. | 1 / 3 |
Trigger Term Quality | Contains some relevant keywords like 'recommendation letters', 'faculty', and 'mentors' that users might naturally say. However, it misses common variations like 'letter of recommendation', 'reference letter', 'LOR', or 'academic recommendation'. | 2 / 3 |
Distinctiveness Conflict Risk | The mention of 'faculty and mentors' and 'recommendation letters' provides some niche specificity, but the truncated and vague nature could overlap with general letter-writing or document-drafting skills. | 2 / 3 |
Total | 6 / 12 Passed |
Implementation
12%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is almost entirely generic boilerplate with very little domain-specific content about recommendation letter writing. The actual useful information (input parameters, output format, feature list) is buried among extensive scaffolding sections (Risk Assessment, Security Checklist, Lifecycle Status, Evaluation Criteria) that consume tokens without adding value. The skill fails to provide any concrete letter templates, example outputs, competency frameworks, or writing guidance that would make it actionable for its stated purpose.
Suggestions
Replace boilerplate sections (Risk Assessment, Security Checklist, Lifecycle Status, Evaluation Criteria) with actual recommendation letter templates, example paragraphs, and competency frameworks specific to medical/academic contexts.
Add a concrete example showing input parameters mapped to a complete letter draft output, demonstrating the expected quality and format.
Remove circular self-references ('See ## Features above') and consolidate the workflow into a single clear sequence with domain-specific validation steps (e.g., 'Verify all ACGME competencies are addressed').
Provide actual content for the claimed features (structured templates, competency-based suggestions, specialty-specific customization) rather than just listing them as bullet points.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose and repetitive. Multiple sections reference each other circularly ('See ## Features above', 'See ## Prerequisites above', 'See ## Workflow above'). Contains extensive boilerplate (Risk Assessment, Security Checklist, Lifecycle Status, Evaluation Criteria) that adds no actionable value for the task of drafting recommendation letters. The actual domain-specific content (letter templates, competency suggestions) is never provided—just listed as features. Much of the content is generic scaffolding that could apply to any skill. | 1 / 3 |
Actionability | Despite the length, there is no concrete guidance on how to actually draft a recommendation letter. No letter templates, no example outputs with real content, no competency frameworks, no sample paragraphs. The 'executable' guidance is limited to running a mysterious `scripts/main.py` with no indication of what it does. The code examples are just `py_compile` and `--help` commands, not actual letter generation workflows. | 1 / 3 |
Workflow Clarity | There is a numbered workflow (steps 1-5) and an example run plan (steps 1-4), but they are generic process steps that could apply to any skill. No validation checkpoints specific to letter writing (e.g., checking competency coverage, verifying tone, ensuring MSPE alignment). The error handling section provides reasonable fallback guidance, but the workflow itself lacks domain-specific sequencing for letter drafting. | 2 / 3 |
Progressive Disclosure | Circular self-references ('See ## Features above', 'See ## Prerequisites above') add confusion rather than navigation. References to `scripts/main.py` and `references/` directory exist but no bundle files are provided, making these dead references. The document is a monolithic wall of boilerplate with no meaningful content separation—everything is inline in one massive file with no clear hierarchy between essential and supplementary information. | 1 / 3 |
Total | 5 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
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Table of Contents
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