entry-signals
Entry signal patterns with historical success rates. Use when deciding whether to open a position.
51
23%
Does it follow best practices?
Impact
100%
1.05xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./data/skills-md/0xhubed/agent-trading-arena/entry-signals/SKILL.mdQuality
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 establishes a trading context and includes an explicit 'Use when' clause, which is positive. However, it lacks concrete actions describing what the skill does (e.g., analyze candlestick patterns, compute indicator signals, generate trade recommendations) and misses common natural language trigger terms users would employ when seeking trading entry guidance.
Suggestions
Add specific concrete actions the skill performs, e.g., 'Identifies candlestick patterns, evaluates technical indicator signals, and computes historical win rates for trade setups.'
Expand trigger terms to include natural user language like 'buy signal', 'when to enter a trade', 'trade setup', 'technical analysis', 'should I buy'.
Clarify the domain more precisely—does this cover stocks, crypto, forex, options?—to reduce overlap with other trading-related skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description mentions 'entry signal patterns' and 'historical success rates' but does not list any concrete actions (e.g., scan charts, calculate indicators, backtest strategies). The language is abstract and does not specify what the skill actually does. | 1 / 3 |
Completeness | The 'when' clause ('Use when deciding whether to open a position') is present and explicit, but the 'what' portion is weak—it only vaguely references 'entry signal patterns with historical success rates' without explaining what the skill concretely does. | 2 / 3 |
Trigger Term Quality | Terms like 'entry signal', 'open a position', and 'success rates' are somewhat relevant to trading contexts, but common user variations like 'buy signal', 'trade entry', 'when to buy', 'technical analysis', or 'trading strategy' are missing. | 2 / 3 |
Distinctiveness Conflict Risk | The trading/position-opening context provides some niche, but 'entry signal patterns' is broad enough to overlap with other trading-related skills (e.g., backtesting, technical analysis, portfolio management). More specific triggers would reduce conflict risk. | 2 / 3 |
Total | 7 / 12 Passed |
Implementation
7%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 data dump of trading signal patterns with no actionable guidance on how to use them. It suffers from extreme redundancy (near-duplicate entries with minor parameter variations), truncated signal names that obscure meaning, and a complete lack of decision-making workflow. The content would be more useful as a structured data file (JSON/YAML) referenced by an actual skill that explains how to evaluate and act on these signals.
Suggestions
Add a clear decision workflow: e.g., 'When evaluating entry: 1. Check top signals matching current conditions, 2. Require success rate > X% AND confidence > Y%, 3. Confirm with at least 2 independent signals, 4. Validate risk parameters before entering'
Deduplicate near-identical signal entries - consolidate variants of 'Multi-timeframe bullish alignment' into a single entry with parameter ranges instead of listing each minor variation separately
Add concrete examples showing how to apply signals: e.g., 'Given BTC showing bullish SMA crossover on 15m + bullish MACD on 1h + neutral Bollinger → enter long with confidence 82%'
Move the raw signal data table to a separate reference file (e.g., signals_data.md) and keep SKILL.md focused on the decision-making process and usage instructions
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with massive redundancy. The table contains near-duplicate entries (e.g., multiple 'Multi-timeframe bullish alignment' rows with slightly different confidence values), and the Signal Details section repeats nearly identical descriptions for each variant. The truncated signal names make the table hard to parse while still consuming many tokens. | 1 / 3 |
Actionability | The skill provides no concrete guidance on how to use these signals. There are no executable code examples, no specific entry/exit logic, no commands, and no clear instructions on how to combine signals or make a trading decision. It's purely descriptive data without actionable steps. | 1 / 3 |
Workflow Clarity | There is no workflow defined. The skill describes signal patterns but provides no sequence of steps for evaluating signals, no decision tree for when to enter a position, and no validation checkpoints. The description says 'Use when deciding whether to open a position' but the content doesn't explain how. | 1 / 3 |
Progressive Disclosure | The content has some structure with a summary table, detailed breakdowns, and a confidence guide. However, it's a monolithic file with repetitive content that could benefit from better organization. The Signal Details section only covers 5 of 30 signals, which is inconsistent. | 2 / 3 |
Total | 5 / 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.
- Repository
- NeverSight/skills_feed
- Commit
f772de4
- Reviewed
Table of Contents
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