ACLM Lab Interpreter
Server Details
Interpret lab values against ACLM-optimized ranges. Returns deprescription signals.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 3.6/5 across 2 of 2 tools scored.
Each tool has a clearly distinct purpose: 'interpret_labs' handles a panel of lab values, while 'marker_reference' focuses on a single biomarker. No overlap or ambiguity.
Both tools use a consistent verb_noun pattern in snake_case ('interpret_labs', 'marker_reference'), making them predictable and easy to understand.
With only 2 tools, the server feels minimal for the domain of lab interpretation. While it covers core needs, additional tools (e.g., for trend analysis or managing patient data) might be expected.
The tools cover the basic operations of interpreting a lab panel and looking up individual markers, but lack support for tasks like updating reference ranges, managing patient history, or interpreting trends over time.
Available Tools
2 toolsinterpret_labsARead-onlyInspect
Interpret a panel of lab values against ACLM-optimized reference ranges. Returns risk classification per marker, lifestyle interventions, and medication deprescription signals.
| Name | Required | Description | Default |
|---|---|---|---|
| lab_values | Yes | Key-value pairs of biomarker names and values. Common keys: hba1c, fasting_glucose, fasting_insulin, ldl, hdl, triglycerides, apob, lp_a, hscrp, vitamin_d, b12, ferritin, tsh, free_t4, free_t3. | |
| health_goals | No | ||
| current_medications | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool returns risk classification, interventions, and deprescription signals, which adds behavioral context beyond the readOnlyHint annotation. However, it does not detail authentication needs or side effects, which are not critical given the read-only nature.
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 concise sentence that front-loads the core action. It could be slightly more structured for readability, but it is efficient and to the point.
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 the lack of output schema and the presence of nested objects, the description provides a fair overview of the return format. However, it fails to explain how health_goals and current_medications affect interpretation, making it incomplete for full autonomous use.
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 schema description covers only 33% of parameters (lab_values is described). The tool description does not elaborate on health_goals or current_medications, leaving their meaning and usage unclear. This is a significant gap.
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's purpose: interpreting lab values against ACLM-optimized reference ranges. It distinguishes from the sibling tool 'marker_reference' by specifying that it returns risk classification, lifestyle interventions, and deprescription signals, which is a more advanced analysis.
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 usage when lab values need interpretation, but it does not explicitly state when to use this tool versus the sibling 'marker_reference' or outline any prerequisites. Guidance on when not to use it is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
marker_referenceARead-onlyInspect
Look up the ACLM-optimized reference range and lifestyle intervention plan for a single biomarker (e.g., apob, lp_a, hscrp, hba1c, fasting_insulin, vitamin_d).
| Name | Required | Description | Default |
|---|---|---|---|
| marker | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. The description's 'look up' aligns with this, but adds no further behavioral details (e.g., auth requirements, rate limits). It does not contradict annotations.
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 concise sentence with the verb 'Look up' front-loaded. It is efficient and includes examples without unnecessary words.
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 lookup tool with one parameter, the description covers the core purpose and examples adequately. It lacks details on return format, but given the simplicity and no output schema, it is mostly complete.
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?
Schema has no description for the 'marker' parameter (0% coverage). The description lists example values, which adds helpful context, but does not formalize the expected format or constraints.
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 it looks up reference ranges and lifestyle plans for a single biomarker, with examples like apob, lp_a. This distinguishes it from the sibling interpret_labs which likely handles multiple markers.
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?
Usage context is implied by mentioning 'single biomarker' and giving examples, but there is no explicit guidance on when to use this vs the sibling tool interpret_labs, nor any when-not conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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