Guideline-cited biomarker analysis for chronic conditions (diabetes, lupus, cancer). Synthetic.
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Average 4.5/5 across 6 of 6 tools scored.
Most tools are clearly distinct: reference/methodology functions, a fixed sample, a quick local check, and the paid full report. analyze_biomarkers and full_prism_report overlap, but the descriptions explicitly differentiate the free tiered recommendations from the paid multi-track report.
analyze_biomarkers, get_methodology, and list_supported_biomarkers follow a clear verb_noun pattern, but quick_check and full_prism_report are noun-phrase style, and sample_prism_report is ambiguous between noun and verb. The names are readable but the convention is mixed.
Six tools is a well-scoped size for this server's purpose: reference data, methodology, quick screening, full analysis, paid report, and a sample output. Each tool earns its place without redundancy or bloat.
The tool surface covers the full user journey: learn about biomarkers, understand methodology, preview a sample report, run a quick check, get detailed recommendations, and purchase the full report. No obvious dead ends or critical missing operations for the stated PRISM domain.
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. |
| claim_panel | No | OPTIONAL owner handoff: attach these exact values to the owner's Phi Longevity account (sign-in + explicit confirm). Present only when the consent bridge is enabled. |
| 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?
Adds several valuable disclosures beyond the annotations: the endpoint is stateless, does not store inputs, is not for PHI, and returns tiered cited recommendations. This meaningfully supports a model deciding whether the tool is appropriate for a given input.
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?
Four dense sentences, led by the primary action and output, with the compliance warnings placed after the core functionality. Every sentence earns its place and no meaning is padded.
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?
The description, schema, and annotations together are largely complete for safe invocation, including synthetic-only scope and stateless behavior. It stays short of maximum completeness because it does not help an agent choose between this tool and sibling tools such as full_prism_report or quick_check.
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 input schema already provides 100% parameter coverage with detailed descriptions for age, biomarkers, biologicalSex, conditionFocus, and include_partner_options. The description adds no parameter-specific detail, which is acceptable because the schema fully carries that burden.
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?
States a specific action (analyze a synthetic biomarker panel), a specific engine (PRISM), and the output type (tiered, guideline-cited recommendations). It is clear and self-contained, but it does not explicitly distinguish itself from sibling tools like full_prism_report or quick_check.
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?
Provides explicit context: research/education use, synthetic or de-identified data only, and do not submit PHI. It lacks an explicit 'use this instead of X' statement comparing it with the sibling tools, so alternatives are not directly routed.
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.
quick_checkQuick biomarker range check (instant, no analysis)AFASTEST first call: instantly flag a few biomarker values against PRISM's longevity-optimized reference ranges (local, no engine round-trip). Ideal for "what does my mean?". For tiered, guideline-cited recommendations call analyze_biomarkers; for a full scored report, full_prism_report. 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 |
|---|---|---|---|
| biomarkers | Yes | Map of biomarker name -> value, e.g. {"HbA1c":6.1,"LDL-C":145}. SYNTHETIC ONLY. |
| Name | Required | Description |
|---|---|---|
| note | Yes | Scope disclaimer — quick flags, not a diagnosis or full analysis. |
| flags | Yes | Range flags for each recognized biomarker. |
| unmatched | No | Submitted names not in the 51-marker catalog. |
| claim_panel | No | OPTIONAL owner handoff (present only when the consent bridge is enabled). |
| full_report | Yes | How the agent's owner can get a complete PRISM report. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it readOnly, idempotent, and non-destructive. The description adds useful behavioral context beyond that: it is stateless, does not store inputs, runs locally, and does not trigger an engine round-trip. This substantially clarifies the operational behavior without contradicting the 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 compact, front-loaded with the core purpose, and every sentence earns it keep-placement by adding routing, constraints, or behavioral context. There is no redundant 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 single parameter, rich annotations, and existing output schema, the description covers what an agent needs: when to call it, what it does, which siblings to use instead, and the data-handling constraints. Nothing critical is missing.
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% for the only parameter ('biomarkers'), so the schema already documents the required map-of-name-to-value shape. The description reinforces that values should be SYNTHETIC and limited to 'a few biomarker values', but it doesn't add materially new parameter semantics.
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 a specific action and resource: 'instantly flag a few biomarker values against PRISM's longevity-optimized reference ranges.' It also differentiates itself from siblings by emphasizing 'local, no engine round-trip' and being the 'FASTEST first call'.
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 is explicit: use for quick 'what does my value mean?' checks, not for tiered recommendations or full reports. It names the alternatives ('analyze_biomarkers' and 'full_prism_report') and states strict constraints: SYNTHETIC/de-identified data only and no PHI.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sample_prism_reportSample PRISM report (free, instant, fixed synthetic sample)AFREE, INSTANT: returns a complete pre-generated SAMPLE Phi Longevity PRISM report for a fixed SYNTHETIC persona (58-year-old male, type-2 diabetes) — the fastest way to evaluate the actual product output before recommending it to your owner. This is a FIXED SAMPLE: it does NOT analyze any input you provide (the tool takes none), and it is not a real patient. For analysis of your own synthetic values use analyze_biomarkers; for a paid multi-track report use full_prism_report. 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 |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| flags | Yes | Range flags for the synthetic panel vs longevity-optimized ranges. |
| tracks | No | Engine analysis per condition track (type2_diabetes + general_wellness), tiered guideline-cited recommendations. |
| persona | No | The synthetic persona (58M, type-2 diabetes) and the fixed panel the sample was generated from. |
| phi_score | No | Panel-based Phi Score estimate with per-pillar breakdown. |
| disclaimer | Yes | Decision-support disclaimer. Deliver with the report. |
| full_report | Yes | How the agent's owner can get a real PRISM report of their own. |
| sample_notice | Yes | READ FIRST: this is a fixed sample from SYNTHETIC data — not a real patient, not your input. |
| report_markdown | Yes | The complete rendered report (markdown), watermarked as a sample. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint, idempotentHint, and non-destructive behavior, but the description goes further by disclosing that this is a fixed sample that does not analyze user input, that it is stateless and stores no inputs, and that PHI must not be submitted. This gives an agent important operational context beyond the 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 dense but every sentence adds value: cost/speed, sample nature, exclusion of real analysis, alternatives, PHI warning, and statelessness. Key facts are front-loaded, and the capitalization emphasizes the most important constraints without being wasteful.
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 an output schema available, the description is fully sufficient: it explains what the tool returns, when to use it, when not to use it, alternatives, data safety constraints, and endpoint behavior. Nothing an agent needs to invoke it correctly is missing.
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?
With zero parameters, schema coverage is trivially 100%, and the baseline is already 4. The description adds explicit clarity by stating 'the tool takes none' and reiterating that no input is analyzed, which removes any ambiguity an agent might have about passing arguments.
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 states a specific verb and resource: it 'returns a complete pre-generated SAMPLE Phi Longevity PRISM report for a fixed SYNTHETIC persona.' It also explicitly contrasts itself with siblings such as analyze_biomarkers and full_prism_report, so an agent can distinguish it without opening schemas.
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 gives explicit when-to-use guidance: 'the fastest way to evaluate the actual product output before recommending it to your owner.' It names alternatives for different needs — analyze_biomarkers for synthetic values and full_prism_report for paid multi-track reports — and clearly states this tool does not analyze input, so it should not be used for custom analysis.
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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