promptify
Transform user requests into detailed, precise prompts for AI models. Use when users say "promptify", "promptify this", or explicitly request prompt engineering or improvement of their request for better AI responses.
Install with Tessl CLI
npx tessl i github:intellectronica/agent-skills --skill promptify88
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
89%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 well-structured description with explicit 'Use when' triggers and distinctive terminology ('promptify'). The main weakness is that the 'what' portion could be more specific about the concrete actions involved in prompt transformation. Overall, it effectively enables skill selection with minimal conflict risk.
Suggestions
Expand the capabilities section with specific actions like 'adds context, structures instructions, specifies output formats, and clarifies constraints'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (prompt engineering) and a general action ('Transform user requests into detailed, precise prompts'), but lacks multiple specific concrete actions like 'add context', 'structure instructions', 'specify output format', etc. | 2 / 3 |
Completeness | Clearly answers both what ('Transform user requests into detailed, precise prompts for AI models') and when ('Use when users say "promptify", "promptify this", or explicitly request prompt engineering or improvement'). | 3 / 3 |
Trigger Term Quality | Includes natural trigger terms users would actually say: 'promptify', 'promptify this', 'prompt engineering', 'improvement of their request'. These are specific and likely match real user language. | 3 / 3 |
Distinctiveness Conflict Risk | The unique trigger term 'promptify' and the specific focus on prompt engineering for AI models creates a clear niche that is unlikely to conflict with other skills like general writing or editing. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured, concise skill that clearly defines the promptify task. The main weakness is the lack of concrete input/output examples demonstrating the transformation process, which would make the skill more actionable. The writing guidelines are specific and useful, but showing them applied to a real example would strengthen the skill significantly.
Suggestions
Add 1-2 concrete examples showing a vague user request transformed into a detailed prompt, demonstrating the guidelines in action
Include a brief example of the expected output format to clarify what 'specification language' looks like in practice
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is lean and efficient, with no unnecessary explanations of concepts Claude already knows. Every section serves a clear purpose and the guidelines are direct without padding. | 3 / 3 |
Actionability | Provides clear guidelines and structure but lacks concrete examples of input/output transformations. A before/after example showing a vague request transformed into a detailed prompt would significantly improve actionability. | 2 / 3 |
Workflow Clarity | For this simple, single-purpose skill, the 3-step process (read, plan, rewrite) is clear and unambiguous. No validation checkpoints are needed since this is a text transformation task with no destructive operations. | 3 / 3 |
Progressive Disclosure | For a skill under 50 lines with no need for external references, the content is well-organized with clear sections (Core Task, Process, Writing Guidelines, Output). The structure is appropriate for the skill's scope. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 13 / 16 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
metadata_version | 'metadata' field is not a dictionary | Warning |
license_field | 'license' field is missing | Warning |
body_examples | No examples detected (no code fences and no 'Example' wording) | Warning |
Total | 13 / 16 Passed | |
- Reviewed
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