postdoc-fellowship-matcher
Match postdoc applicants to eligible fellowships based on nationality and research area
Install with Tessl CLI
npx tessl i github:aipoch/medical-research-skills --skill postdoc-fellowship-matcher44
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
40%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
The description identifies a clear niche (postdoc fellowship matching) with good distinctiveness, but lacks explicit trigger guidance and could benefit from more specific action verbs and keyword variations. The missing 'Use when...' clause significantly limits Claude's ability to know when to select this skill.
Suggestions
Add a 'Use when...' clause with trigger terms like 'postdoctoral funding', 'fellowship eligibility', 'find fellowships', or 'postdoc opportunities'
Expand keyword coverage to include variations like 'postdoctoral', 'grants', 'funding', 'eligibility requirements', and 'academic positions'
Add more specific actions beyond 'match' such as 'filter by eligibility criteria', 'recommend fellowships', or 'check nationality requirements'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (postdoc applicants, fellowships) and the core action (match), but only mentions two criteria (nationality, research area) without detailing what 'matching' entails or additional capabilities. | 2 / 3 |
Completeness | Describes what the skill does but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. | 1 / 3 |
Trigger Term Quality | Includes relevant terms like 'postdoc', 'applicants', 'fellowships', 'nationality', and 'research area' that users might say, but misses common variations like 'postdoctoral', 'funding opportunities', 'grants', or 'eligibility'. | 2 / 3 |
Distinctiveness Conflict Risk | The combination of 'postdoc applicants', 'fellowships', 'nationality', and 'research area' creates a clear, specific niche that is unlikely to conflict with other skills. | 3 / 3 |
Total | 8 / 12 Passed |
Implementation
22%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is essentially a placeholder that describes what a fellowship matcher should do without providing any actual implementation or matching logic. The fellowship database lists names without eligibility criteria, and the extensive boilerplate (risk assessment, security checklist, lifecycle status) consumes tokens without enabling Claude to perform the task.
Suggestions
Add concrete eligibility rules for each fellowship (nationality requirements, years post-PhD limits, eligible research fields) in a structured format Claude can use for matching
Provide the actual matching logic or algorithm, either as executable Python code or clear decision rules
Remove or drastically reduce boilerplate sections (risk assessment, security checklist, evaluation criteria, lifecycle status) that don't help Claude perform the matching task
Add example input/output showing how an applicant profile maps to eligible fellowships with reasoning
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill includes substantial boilerplate (risk assessment table, security checklist, evaluation criteria, lifecycle status) that adds little value for Claude's task execution. The core matching functionality could be conveyed in far fewer tokens. | 2 / 3 |
Actionability | The skill provides only a CLI invocation example but no actual implementation, no code for the matching logic, and no concrete guidance on how fellowships are matched to criteria. The fellowship database is just a list of names with no eligibility rules. | 1 / 3 |
Workflow Clarity | There is no workflow described - just a single command invocation. No steps for how to actually perform matching, no validation of inputs, no guidance on handling edge cases like partial matches or missing data. | 1 / 3 |
Progressive Disclosure | The content is organized into sections, but there are no references to external files for detailed fellowship eligibility rules, matching algorithms, or examples. The structure exists but doesn't effectively organize actionable content. | 2 / 3 |
Total | 6 / 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 | |
- Reviewed
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