recommendation-letter-assistant
Helps faculty and mentors draft standardized recommendation letters for.
28
11%
Does it follow best practices?
Impact
Pending
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 incomplete—the sentence literally cuts off mid-phrase ('letters for.'), leaving the reader unsure of the full capability. It lacks a 'Use when...' clause, has limited trigger term coverage, and provides only a single vague action. The description needs significant revision to be functional for skill selection.
Suggestions
Complete the truncated sentence to specify what the recommendation letters are for (e.g., 'graduate school applications', 'academic positions', 'scholarships').
Add an explicit 'Use when...' clause with trigger terms like 'recommendation letter', 'letter of recommendation', 'LoR', 'reference letter', 'academic reference'.
List specific concrete actions such as 'Generates structured recommendation letters, customizes tone for different programs, incorporates academic achievements and research contributions.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description mentions 'draft standardized recommendation letters' which is one action, but the sentence is incomplete ('letters for.' ends abruptly), making it vague and unclear about what the full scope of capabilities is. | 1 / 3 |
Completeness | The 'what' is partially stated but incomplete (the sentence cuts off at 'for.'), and there is no 'when' clause or explicit trigger guidance whatsoever. The missing 'Use when...' clause alone would cap this at 2, but the incomplete 'what' drops it to 1. | 1 / 3 |
Trigger Term Quality | Contains some relevant keywords like 'recommendation letters', 'faculty', and 'mentors' that users might naturally use, but the incomplete sentence limits coverage and misses variations like 'letter of recommendation', 'reference letter', 'LoR', or 'grad school'. | 2 / 3 |
Distinctiveness Conflict Risk | The mention of 'recommendation letters' and 'faculty and mentors' provides some niche specificity that distinguishes it from generic writing skills, but the incomplete description and lack of detail could still cause overlap with general letter-writing or document-drafting skills. | 2 / 3 |
Total | 6 / 12 Passed |
Implementation
0%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 minimal domain-specific content for recommendation letter writing. The features list promises structured templates, competency-based suggestions, and specialty-specific customization, but none of these are actually provided. The repeated circular references between sections, extensive security/risk/lifecycle scaffolding, and absence of any concrete letter-writing guidance make this skill ineffective for its stated purpose.
Suggestions
Replace the generic workflow with a concrete letter-drafting sequence: e.g., 1) Determine letter type based on relationship, 2) Select opening template, 3) Map key_strengths to competency paragraphs, 4) Draft closing with ranking language, 5) Review for tone and specificity.
Add actual letter templates or examples showing how input parameters map to output paragraphs—e.g., a sample input with applicant_name, key_strengths, and the resulting letter_draft.
Remove all boilerplate sections that don't contribute to letter writing (Risk Assessment, Security Checklist, Lifecycle Status, Evaluation Criteria, Audit-Ready Commands) and replace with domain content like competency frameworks, specialty-specific language, and strength/weakness framing examples.
Eliminate circular self-references ('See ## Features above') and consolidate the content into a clear, linear structure with the letter-writing guidance front and center.
| 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 letter drafting. Generic scaffolding like 'Performance optimization' and 'Additional feature support' wastes tokens. The actual domain-specific content (letter templates, competency suggestions) is never provided. | 1 / 3 |
Actionability | Despite listing input parameters and output format, there is no concrete guidance on how to actually draft a recommendation letter. The 'scripts/main.py' is referenced repeatedly but no actual code or letter-writing logic is provided. The workflow steps are entirely generic ('Confirm the user objective', 'Validate that the request matches') with no domain-specific instructions for letter composition, tone, structure, or content generation. | 1 / 3 |
Workflow Clarity | The workflow section contains only generic meta-process steps ('Confirm the user objective', 'Validate that the request matches the documented scope') with no letter-writing-specific sequence. There are no validation checkpoints for letter quality, no feedback loops for reviewing draft content, and no concrete steps for transforming input parameters into a well-structured recommendation letter. | 1 / 3 |
Progressive Disclosure | Circular self-references ('See ## Features above', 'See ## Prerequisites above') add confusion rather than navigation. References to 'references/' directory are vague with no specifics about what guidance exists there. The document is a monolithic wall of boilerplate sections with no meaningful content hierarchy—critical domain content (letter templates, competency frameworks, specialty customization) is entirely absent despite being listed as features. | 1 / 3 |
Total | 4 / 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 | |
- Repository
- aipoch/medical-research-skills
- Commit
8277276
- Reviewed
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