forecast-generator
Forecast Generator - Auto-activating skill for Data Analytics. Triggers on: forecast generator, forecast generator Part of the Data Analytics skill category.
33
Quality
0%
Does it follow best practices?
Impact
95%
1.00xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./planned-skills/generated/12-data-analytics/forecast-generator/SKILL.mdQuality
Discovery
0%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 essentially a placeholder with no substantive content. It only provides the skill name, a redundant trigger term, and a generic category label. The description completely fails to communicate what forecasting capabilities are available or when users should invoke this skill.
Suggestions
Add specific actions the skill performs, e.g., 'Generates time series forecasts, predicts future values from historical data, creates trend projections with confidence intervals'
Include a 'Use when...' clause with natural trigger terms like 'predict future sales', 'forecast demand', 'project trends', 'time series analysis', 'what will happen next'
Specify the types of forecasts supported (e.g., sales forecasting, demand planning, financial projections) to distinguish from other analytics skills
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only names the skill ('Forecast Generator') and category ('Data Analytics') without describing any concrete actions. There are no specific capabilities listed like 'generate time series forecasts', 'predict trends', or 'analyze historical data'. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the name, and the 'when' clause is just the skill name repeated. There is no explicit guidance on when Claude should select this skill or what problems it solves. | 1 / 3 |
Trigger Term Quality | The only trigger terms listed are 'forecast generator' repeated twice, which is the skill name itself rather than natural user language. Missing common variations users would say like 'predict', 'projection', 'future trends', 'time series', 'forecasting'. | 1 / 3 |
Distinctiveness Conflict Risk | The generic 'Data Analytics' category and lack of specific triggers means this could easily conflict with any other analytics-related skill. Nothing distinguishes it from general data analysis, reporting, or other forecasting approaches. | 1 / 3 |
Total | 4 / 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 content is essentially a placeholder template with no actual instructional value. It describes what a forecast generator skill would do in abstract terms but provides zero concrete guidance, code examples, or workflows for generating forecasts. The entire content is meta-description rather than actionable instruction.
Suggestions
Add concrete, executable code examples for common forecasting methods (e.g., time series with pandas, ARIMA, exponential smoothing)
Include a clear workflow with steps: data preparation, model selection, validation, and output generation
Provide specific SQL queries or Python code for extracting and preparing data for forecasting
Remove all meta-description content ('This skill provides...', 'When to Use...') and replace with actual forecasting instructions and examples
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that provides no actual value. Phrases like 'provides automated assistance' and 'follows industry best practices' are vague filler that Claude doesn't need. | 1 / 3 |
Actionability | There is zero concrete guidance - no code, no commands, no specific examples of how to actually generate forecasts. The content only describes what the skill claims to do without showing how. | 1 / 3 |
Workflow Clarity | No workflow is provided whatsoever. There are no steps, no sequence, and no validation checkpoints for forecast generation tasks. | 1 / 3 |
Progressive Disclosure | The content is a monolithic block of meta-description with no actual instructional content to organize. There are no references to detailed materials or examples. | 1 / 3 |
Total | 4 / 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 — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Commit
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- Reviewed
Table of Contents
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