erpnext-code-interpreter
Intelligent agent for interpreting vague ERPNext development requests and producing concrete technical specifications. Use when receiving unclear requirements like 'make invoice auto-calculate', 'add approval workflow', 'sync with external system'. Triggers: user gives vague requirement, need to clarify scope, translate business need to technical spec, determine which ERPNext mechanisms to use, create implementation plan.
Install with Tessl CLI
npx tessl i github:OpenAEC-Foundation/ERPNext_Anthropic_Claude_Development_Skill_Package --skill erpnext-code-interpreter84
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-crafted skill description with strong trigger terms and excellent completeness. The explicit 'Use when' clause with concrete examples and the 'Triggers:' section provide clear guidance for skill selection. The main weakness is that the capabilities could be more specific about what concrete outputs or actions the skill produces beyond 'technical specifications'.
Suggestions
Add 2-3 more specific concrete actions the skill performs, such as 'generates doctype schemas', 'maps business workflows to ERPNext mechanisms', or 'creates implementation checklists'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (ERPNext development) and describes the general action (interpreting vague requests, producing technical specifications), but doesn't list multiple concrete specific actions like 'create doctype schemas', 'configure workflows', or 'generate API integrations'. | 2 / 3 |
Completeness | Clearly answers both what (interpreting vague ERPNext requests and producing technical specifications) AND when (explicit 'Use when' clause with examples and a 'Triggers:' section listing specific scenarios). | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'vague requirement', 'clarify scope', 'business need', 'technical spec', 'implementation plan', plus concrete examples like 'make invoice auto-calculate', 'add approval workflow', 'sync with external system'. | 3 / 3 |
Distinctiveness Conflict Risk | Very specific niche targeting ERPNext development requirements clarification. The combination of 'ERPNext', 'vague requirements', and 'technical specifications' creates a distinct trigger profile unlikely to conflict with general coding or documentation skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
70%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 interpretive agent skill with excellent progressive disclosure and clear workflow. Its main weakness is that it's more of a thinking framework than an actionable implementation guide - it tells Claude how to analyze requests but doesn't provide executable code for the actual interpretation process. The ASCII box diagrams add visual noise without proportional clarity benefit.
Suggestions
Replace ASCII box diagrams with simpler markdown lists or tables to reduce token overhead while maintaining clarity
Add a concrete worked example showing the full interpretation process from vague request to completed specification output
Consider whether the mechanism selection matrix and pattern recognition sections can be consolidated to reduce redundancy
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is reasonably efficient but includes some redundancy - the ASCII box diagrams add visual bulk without proportional value, and some sections repeat concepts (e.g., mechanism selection appears in both the matrix and pattern recognition sections). | 2 / 3 |
Actionability | Provides good conceptual guidance with clear decision matrices and question frameworks, but lacks executable code examples. The output specification template is helpful but the skill is more about process/thinking than concrete implementation steps. | 2 / 3 |
Workflow Clarity | The 5-step interpretation workflow is clearly sequenced with explicit steps. The agent output checklist provides validation checkpoints. For an interpretive/planning skill (not a destructive operation), the workflow is appropriately structured. | 3 / 3 |
Progressive Disclosure | Excellent structure with clear overview content and well-signaled one-level-deep references to workflow.md, examples.md, and checklists.md. Content is appropriately split between the main skill and reference files. | 3 / 3 |
Total | 10 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Reviewed
Table of Contents
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