blockbuster-therapy-predictor
Predict which early-stage biotechnology platforms (PROTAC, mRNA, gene editing, etc.) have the highest potential to become blockbuster therapies. Analyzes clinical trial progression, patent landscape maturity, and venture capital funding trends to generate investment and R&D prioritization scores. Trigger when: User asks about technology investment potential, platform selection, or therapeutic modality comparison.
Install with Tessl CLI
npx tessl i github:aipoch/medical-research-skills --skill blockbuster-therapy-predictor79
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
100%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 is a strong skill description that clearly articulates specific capabilities (predicting biotech platform potential through multi-factor analysis), provides concrete examples of platforms, and includes an explicit trigger clause. The description uses appropriate third-person voice and balances domain-specific terminology with natural language triggers that users would employ.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Predict which early-stage biotechnology platforms...have the highest potential', 'Analyzes clinical trial progression, patent landscape maturity, and venture capital funding trends', 'generate investment and R&D prioritization scores'. Names specific platforms (PROTAC, mRNA, gene editing) as examples. | 3 / 3 |
Completeness | Clearly answers both what (predict biotech platform potential, analyze clinical/patent/VC data, generate scores) AND when with explicit 'Trigger when:' clause specifying technology investment potential, platform selection, or therapeutic modality comparison. | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'technology investment potential', 'platform selection', 'therapeutic modality comparison', plus domain-specific but recognizable terms like 'PROTAC', 'mRNA', 'gene editing', 'blockbuster therapies', 'clinical trial', 'venture capital funding'. | 3 / 3 |
Distinctiveness Conflict Risk | Highly specific niche combining biotechnology platforms, clinical trial analysis, patent landscape, and VC funding trends. The combination of biotech-specific terminology and investment/R&D prioritization creates a distinct trigger profile unlikely to conflict with general investment or general biotech skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides excellent actionable CLI documentation with clear examples and parameter tables, but is severely bloated with unnecessary sections (security checklists, risk assessments, lifecycle status, evaluation criteria) that waste tokens and obscure the core functionality. The content reads more like a product README than a focused skill instruction, explaining concepts Claude already understands.
Suggestions
Remove security checklist, risk assessment, lifecycle status, and evaluation criteria sections - these are boilerplate that don't help Claude execute the skill
Condense the supported technologies table to a simple list or remove entirely since Claude can discover this from the tool itself
Move the scoring methodology details to a referenced file (e.g., METHODOLOGY.md) and keep only essential usage information in the main skill
Add a brief workflow for handling analysis failures or validating output quality before presenting results
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with extensive boilerplate that Claude doesn't need (security checklists, risk assessments, lifecycle status, evaluation criteria). The feature list, supported technologies table, and lengthy disclaimers add significant token overhead without actionable value. | 1 / 3 |
Actionability | Provides fully executable CLI commands with clear parameter documentation. The bash examples are copy-paste ready, and the output examples show exactly what to expect from different invocations. | 3 / 3 |
Workflow Clarity | The usage section shows clear command patterns, but there's no workflow for multi-step analysis processes. Missing validation checkpoints for verifying data quality or handling errors when analysis fails. | 2 / 3 |
Progressive Disclosure | References to 'references/' directory exist but are vague. The document is monolithic with inline content (security checklists, risk tables, evaluation criteria) that should be in separate files or omitted entirely. | 2 / 3 |
Total | 8 / 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
Table of Contents
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