Analyze biomarker panels with an MD-led clinical engine. Guideline-cited. Synthetic data only.
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Average 4.3/5 across 3 of 3 tools scored.
Each tool has a clearly distinct purpose: analyzing biomarkers, retrieving methodology, and listing supported biomarkers. No overlap or ambiguity.
All tool names follow a consistent verb_noun snake_case pattern: analyze_biomarkers, get_methodology, list_supported_biomarkers.
Three tools is slightly minimal but appropriate for a focused research/education server covering analysis, reference, and methodology. Could benefit from an additional tool for detailed guidance.
The toolset covers the core domain fully: biomarker analysis, methodology explanation, and reference data listing. No obvious gaps.
analyze_biomarkersAnalyze biomarkers (synthetic)AAnalyze a SYNTHETIC biomarker panel with Phi Longevity's PRISM engine. Returns tiered, guideline-cited recommendations. For research/education with SYNTHETIC or de-identified data only. Do NOT submit protected health information (PHI). This endpoint is stateless and does not store inputs.
| Name | Required | Description | Default |
|---|---|---|---|
| age | No | Age in years of the synthetic persona (improves reference-range interpretation). | |
| biomarkers | Yes | Map of biomarker name -> numeric value, e.g. { "Hemoglobin A1c": 5.4 }. SYNTHETIC ONLY. | |
| biologicalSex | No | Biological sex of the synthetic persona (sex-specific reference ranges). | |
| conditionFocus | No | Optional condition track. Default general_wellness. | |
| include_partner_options | No | If true, include partner/product options. Default false. |
| Name | Required | Description |
|---|---|---|
| meta | No | Engine metadata for this analysis run. |
| issues | No | Flagged issues detected in the panel. |
| full_report | Yes | How the agent's owner can get a complete PRISM report. |
| recommendations | No | Tiered, guideline-cited recommendations from the PRISM engine. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (read-only, idempotent, non-destructive), the description adds that the endpoint is stateless and does not store inputs, providing valuable behavioral 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 three well-structured sentences, front-loading the purpose and immediately following with output and usage context, with no filler.
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 rich annotations and output schema, the description covers synthetic-only usage and statelessness. Minor gaps (e.g., unknown biomarker handling) are acceptable due to schema and annotations.
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 coverage is 100% with adequate parameter descriptions; the tool description does not add further semantic value beyond what is already in the input 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 analyzes a synthetic biomarker panel using PRISM engine and returns tiered recommendations, distinguishing it from siblings like full_prism_report.
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 specifies synthetic-only use and warns against submitting PHI, but does not explicitly guide when to use this tool versus alternatives like full_prism_report.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
full_prism_reportFull PRISM report (paid — $4.99 USDC via x402)APAID TOOL ($4.99 USDC on base via the x402 protocol). Everything analyze_biomarkers does, plus: multi-track compare/contrast analysis (up to 4 condition tracks), a panel-based Phi Score estimate with per-pillar breakdown, partner options, and a rendered report (markdown) to deliver to your owner. Call WITHOUT payment to receive x402 payment terms; pay; retry with the base64 payment payload in payment. For research/education with SYNTHETIC or de-identified data only. Do NOT submit protected health information (PHI). This endpoint is stateless and does not store inputs.
| Name | Required | Description | Default |
|---|---|---|---|
| age | No | Age in years of the synthetic persona. | |
| payment | No | Base64-encoded x402 payment payload. Omit on first call to receive payment terms. | |
| biomarkers | Yes | Map of biomarker name -> numeric value, e.g. { "Hemoglobin A1c": 5.4 }. SYNTHETIC ONLY. | |
| biologicalSex | No | Biological sex of the synthetic persona. | |
| compareTracks | No | Tracks to analyze for compare/contrast. Default: primary + general_wellness. | |
| conditionFocus | No | Primary condition track. Default general_wellness. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description fully explains the payment flow, statelessness, and data restrictions. Annotations (readOnlyHint, openWorldHint) are consistent and the description adds context about the two-call payment protocol. No contradiction.
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 dense paragraph. It front-loads the paid nature and lists features, but could be more structured (e.g., bullet points). No superfluous sentences.
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?
While the description covers purpose, payment, and limitations, it lacks details on the output format (e.g., structure of the markdown report, what the Phi score breakdown includes). No output schema exists, so the description should compensate more.
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?
All 6 parameters have descriptions in the schema (100% coverage). The description adds value by explaining the payment parameter's two-call behavioral pattern and defaults for compareTracks and conditionFocus, going beyond what the schema provides.
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 is a paid report generation tool that extends analyze_biomarkers with multi-track comparison, Phi score estimate, partner options, and a rendered markdown report. It distinguishes itself from siblings by being a superset.
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 explains the payment process (call without payment, then retry with payload) and limits usage to research/education with synthetic or de-identified data. It does not explicitly contrast with all siblings but implies when to use this over analyze_biomarkers.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_methodologyGet PRISM methodologyASummarize how the Phi Score works (5 clinical pillars + weights) and link to the full methodology.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| note | Yes | Decision-support disclaimer and synthetic-data rule. |
| source | Yes | Attribution. |
| phi_score | Yes | Plain-English summary of how the 0-100 Phi Score is computed. |
| agent_docs_url | Yes | Agent integration docs. |
| methodology_url | Yes | Full public methodology page. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint true, destructiveHint false, covering safety and idempotency. Description adds summarization and linking behavior but not additional traits beyond 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?
Single sentence with front-loaded action ('Summarize...'), no wasted words, highly efficient.
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?
Complete for a simple summary tool: no parameters, output schema exists (documenting return), annotations cover safety. Description adds value by specifying summary content and link.
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?
No parameters (0), schema coverage 100%. Description does not need to explain parameters; baseline score 4 applies.
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?
Description clearly states it summarizes the Phi Score methodology with 5 pillars and weights, plus links to full methodology. Distinct from siblings: analyze_biomarkers (biomarker analysis), full_prism_report (full report), list_supported_biomarkers (listing biomarkers).
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?
Implied usage: quick overview or entry point to methodology. Does not explicitly state when to avoid or alternatives, but sibling tool names provide context for differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_supported_biomarkersList supported biomarkersAList the biomarkers PRISM scores, with units and reference ranges, grouped by clinical pillar. Reference data only — no patient data.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| biomarkers | Yes | The 51-marker catalog with clinical reference ranges. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds valuable context: it returns reference data grouped by clinical pillar with units and ranges, and explicitly states no patient data is involved.
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?
Two concise sentences with no redundant information. The key facts are front-loaded and every word adds value.
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 parameters, rich annotations, and the presence of an output schema, the description is fully adequate. It explains what the tool returns without needing to detail return values.
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, and schema coverage is 100%. The description adds meaning about the output (biomarkers, PRISM scores, units, reference ranges, grouping), which is sufficient.
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 lists biomarkers (PRISM scores) with units and reference ranges, grouped by clinical pillar, and explicitly distinguishes it from patient data, which differentiates it from siblings like analyze_biomarkers and full_prism_report.
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 indicates it is for reference data only, implying usage when listing standard biomarkers is needed, but lacks explicit when-not-to-use or alternative tool guidance beyond the sibling list.
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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