Owl Group Trading — Indicator Code
Server Details
Verified cross-platform implementations of Owl Group Trading indicators as queryable code.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-06-18
- URL
TDQS
Scored across 2 tools
get_indicator_code retrieves implementation code for a specific indicator, while list_indicators provides the catalog of all available indicators. The roles are entirely complementary with no overlap.
Both tools follow a clear verb_noun pattern: list_indicators and get_indicator_code. The naming style is uniform and predictable.
Two tools is slightly below the typical range, but the server's scope is deliberately narrow: browse the catalog then fetch the code. Each tool earns its place without unnecessary surface area.
For a read-only indicator code library, list and get fully cover the user journey: discover available indicators and retrieve their verified source. No additional CRUD or search operations are needed for this domain.
Available Tools
2 toolsget_indicator_codeGet an indicator's implementationAInspect
Return the verified implementation of an Owl Group Trading indicator in a given platform. Args: slug (e.g. 'rl10', 'dragon', 'river-flood-plain') and platform (e.g. 'python', 'javascript'). Returns the commented source code, the verification proof (real Python-vs-JS parity), the summary, and the page URL. Call list_indicators first to see valid slugs and platforms.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Indicator slug, e.g. 'rl10' | |
| platform | No | Platform: 'python' or 'javascript' | python |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It accurately describes the return structure (commented source code, verification proof, summary, page URL). It implies a read-only operation and does not mention side effects, which is appropriate for a retrieval tool.
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 description is extremely concise at two sentences, with no wasted words. The first sentence front-loads purpose and returns, and the second provides actionable guidance, making it easy to parse.
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 simple retrieval tool with two parameters and no output schema, the description is complete. It covers what the tool does, how to use it, what to expect as output, and how to prepare (call list_indicators first).
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?
Input schema covers 100% of parameters with descriptions. The description adds value by providing concrete examples (e.g., 'rl10', 'python') and clarifies that slugs come from list_indicators, going beyond the basic schema.
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 clearly states the tool returns the verified implementation of an Owl Group Trading indicator, specifies key parameters and return values, and explicitly differentiates from the sibling tool list_indicators by instructing to call that first.
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?
The description provides explicit guidance to call list_indicators first to discover valid slugs and platforms, and gives examples of valid inputs. However, it does not explicitly state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_indicatorsList Owl Group Trading indicatorsAInspect
List every indicator in the Owl Group Trading code library: slug, name, one-line summary, available platforms, the linked glossary concept, the verification tolerance, and the page URL. Returns the authoritative catalog so the answer comes from real data rather than a guess. Takes no arguments.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries full burden. It explains the tool returns a list of all indicators with specified fields and takes no arguments. It does not describe side effects, but the operation is obviously read-only and non-destructive, which is clear from context.
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 description is a single sentence that combines the action, the resource, the output fields, and the rationale. It is front-loaded with the main purpose and contains no redundant information.
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?
Given no output schema, the description lists all expected return fields (slug, name, summary, platforms, glossary concept, tolerance, URL). It also clarifies the purpose (authoritative catalog), making the tool's behavior fully transparent for a listing operation with no parameters.
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?
There are no parameters (0 params, 100% schema coverage). The description explicitly states 'Takes no arguments,' which adds value beyond the empty schema by confirming the agent need not worry about inputs.
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 clearly states 'List every indicator in the Owl Group Trading code library' and enumerates the specific fields returned (slug, name, summary, platforms, etc.). It distinguishes from the sibling tool 'get_indicator_code' by focusing on listing all indicators rather than retrieving code for 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?
The description implies this tool is for obtaining an authoritative catalog of indicators, but it does not explicitly state when to use this vs. the sibling 'get_indicator_code'. It provides context ('answer comes from real data') but lacks direct comparison or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
- First observed
get_indicator_code - First observed
list_indicators
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