Detect behavioral patterns like chasing highs, selling too early, emotional trading, and principle violations across recorded investment decisions and thoughts.
Run behavior pattern detection on all recorded decisions and thoughts.
Detects: 追高, 过早卖出, 情绪化交易, 原则违反.
Results are saved to the behavior_patterns table.
Returns:
dict: Detection results with count and pattern list
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it does add real value by disclosing that results are written to the behavior_patterns table (a mutation side effect) and by summarizing the return shape. It still omits whether the run is idempotent, how expensive it is, what happens with zero recorded data, and whether any permission is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The first sentence front-loads the action and scope, and the detection list plus persistence note are compact. The trailing 'Returns:' block with a Python-style 'dict:' line is slightly noise for an agent but still short and informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no annotations and no output schema, the description covers the action, the detected patterns, the persistence target, and the return contents, which is most of what is needed. It stops short of routing guidance relative to the read-side siblings and of stating preconditions (e.g., needing previously recorded decisions).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, which is the baseline-4 case. The empty schema is fully covered, and there are no argument semantics the description could add.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb+resource ('Run behavior pattern detection on all recorded decisions and thoughts') and enumerates the four Chinese pattern names it detects, so the scope is concrete. It does not, however, differentiate itself from close siblings like pattern_get_pattern_summary, pattern_get_pattern_report, or memory_get_behavior_patterns, which an agent must distinguish from this one.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit when-to-use guidance and no mention of alternatives. An agent cannot tell from the text whether this should be run before pattern_get_pattern_summary/get_pattern_report, or whether it is safe to call repeatedly. Usage is only weakly implied by 'on all recorded decisions and thoughts'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.