Sally Skills
Server Details
Plug Sally AI into your agent. The clinical-grade health intelligence behind A1C Insights, Sally AI, now exposed as an MCP endpoint and REST API to your agent — 64+ biomarkers across Western clinical and TCM preventive frameworks. Authenticate, call the skills you need, get billed per request. Built for agents who care about health and evidence.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 1.5/5 across 6 of 6 tools scored.
The tools cover distinct health-related functions (lab analysis, chat, food logging, insights, sync, metabolic overview), but some overlap between health_insights and metabolic_overview could cause confusion. Descriptions are minimal, making differentiation harder.
Names are all snake_case, but the pattern is inconsistent: `analyze_lab_result` and `chat_with_sally` follow verb_noun, while the others (e.g., `food_journal`, `health_insights`) are noun_noun. This mixed convention reduces predictability.
With 6 tools, the server is well-scoped for a health assistant. Each tool has a clear role, and the count is neither too sparse nor excessive for the apparent domain.
The tool set covers core health tracking (lab results, food, metabolic overview) and interaction (chat, insights, sync). However, common areas like exercise or medication tracking are missing, leaving minor gaps.
Available Tools
7 toolsanalyze_lab_resultDInspect
Sally skill ($0.008/call)
| Name | Required | Description | Default |
|---|---|---|---|
| pdf_b64 | Yes | Base64-encoded PDF or image (≤10MB raw, ≤14MB base64). | |
| filename | No | Optional hint for mime detection (e.g. "panel.pdf"). Defaults to "document.pdf". | |
| llm_model | No | Override OpenRouter model id used for interpretation. Defaults to LAB_READING_MODEL on the OCR side. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits (e.g., read/write nature, side effects, data handling). The cost hint is insufficient for understanding behavior.
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 short but lacks substance. It is not concise in a helpful way; it is under-specified. Every sentence should earn its place; here the single sentence is essentially useless.
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 tool has 3 parameters, no output schema, and no annotations, the description is completely inadequate. It fails to explain what the tool does, what inputs are expected, or what the result is.
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 has 100% description coverage, so the baseline is 3. However, the tool description adds no meaning beyond the schema (e.g., no explanation of when parameters are needed or how they affect output). The description is nearly empty.
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 'Sally skill ($0.008/call)' does not specify a verb or resource; it is vague and uninformative. The tool name suggests lab result analysis, but the description fails to convey this.
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?
No guidance is provided on when to use this tool versus siblings like 'chat_with_sally' or 'health_insights'. There is no context for selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
chat_with_sallyDInspect
Sally skill ($0.003/call)
| Name | Required | Description | Default |
|---|---|---|---|
| health | No | If true, the agent personalises with the calling user's mem0, lab results, CGM, sleep, vitals. Defaults to false (knowledge-only). | |
| message | Yes | ||
| language | No | BCP-47 short code (e.g. 'en', 'id'). Omit for auto-detect from the message. | |
| knowledge | No | Sally's knowledge brain — 'medical' for evidence-based clinical sources, 'tcm' for Traditional Chinese Medicine. | tcm |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits (e.g., what happens with health data, knowledge bases, or output). The description is essentially missing.
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 short but under-specified rather than efficiently concise. It fails to convey essential information, making it ineffective.
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?
With 4 parameters, no output schema, and no annotations, the description is completely inadequate. It does not explain return values, behavior, or how to use the tool effectively.
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 description coverage is 75%, but the tool description adds no meaning beyond the schema. The schema already describes parameters well, so the description does not compensate or add value.
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 name 'chat_with_sally' suggests a conversational tool, but the description 'Sally skill ($0.003/call)' is vague and does not specify what the tool does or how it differs from siblings. No verb+resource is provided.
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?
No guidance is provided on when to use this tool vs alternatives. The description lacks any context about appropriate use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
food_journalDInspect
Sally skill ($0.004/call)
| Name | Required | Description | Default |
|---|---|---|---|
| mime | No | Optional mime override (e.g. "image/png"). Auto-detected from magic bytes if absent. | |
| image_b64 | Yes | Base64-encoded food image (≤10MB raw, ≤14MB base64). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description fails to disclose any behavioral traits (e.g., what happens after sending an image, whether it stores data, auth requirements). Completely opaque.
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?
Extremely short but lacks substance. Not concise; it's under-specified. Every sentence should earn its place, but this sentence adds no functional 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 2 parameters, no output schema, and no annotations, description must explain overall purpose. It fails entirely, leaving agents to guess the tool's role.
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 100% description coverage with clear parameter docs (image_b64 constraints, mime auto-detection). Description adds no value, but baseline is 3 due to high schema coverage.
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 is 'Sally skill ($0.004/call)' which only mentions cost, not the tool's function. Name 'food_journal' hints at food logging, but no verb or resource stated.
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?
No guidance on when to use this tool versus siblings like 'analyze_lab_result' or 'chat_with_sally'. Context must be inferred entirely from name and schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
health_insightsDInspect
Sally skill ($0.003/call)
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | Local date YYYY-MM-DD. Default: today in `timezone`. | |
| type | No | Which insight to generate. 'auto' resolves from current local hour: 05:00-11:59 morning, 12:00-17:59 afternoon, else evening (00:00-04:59 rolls back to evening). | auto |
| language | No | BCP-47 short code (e.g. 'en'). Default: 'en'. | |
| timezone | No | IANA tz (e.g. 'Asia/Jakarta'). Default: UTC. | UTC |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description lacks any behavioral details such as what the tool returns, side effects, or access requirements. The cost mention is irrelevant to behavior.
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?
Extremely short but under-specified. Not concise in a helpful way; essential information is missing.
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?
With no output schema, no annotations, and 4 parameters, the description is severely incomplete. Agent cannot infer return format, behavior, or prerequisites.
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% and parameter descriptions in schema are self-explanatory. However, description adds no additional meaning beyond 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?
Description 'Sally skill ($0.003/call)' does not state what the tool does; it is ambiguous and does not clarify that it generates health insights. The name implies health insights but description fails to confirm.
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?
No guidance on when to use this tool versus siblings like analyze_lab_result, food_journal, etc. No context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
health_syncDInspect
Sally skill ($0.001/call)
| Name | Required | Description | Default |
|---|---|---|---|
| date_to | No | UTC date YYYY-MM-DD. Default: today. | |
| include | No | Subset to return. Omit for the six daily-aggregate categories. `cgm_minute` (real-time, minute-base CGM samples) is opt-in only — it is NOT included in the default set because the table is large. | |
| max_days | No | Relative window size (days). Ignored if date_from is provided. Hard cap: 90. | |
| aggregate | No | When true, returns the same payload core-go sends to langchain for morning-insights + metabolic-overview. | |
| date_from | No | UTC date YYYY-MM-DD. Default: today - 7 days. | |
| cgm_minute_to | No | ISO datetime — end of the window. Default: now. | |
| cgm_minute_from | No | ISO datetime — start of the high-resolution CGM window. Default: now - 24h. | |
| cgm_minute_resolution | No | Sampling resolution for the cgm_minute series. `1m` returns raw rows (≤1440 = 1 day). Coarser buckets average value/roc inside each bucket — useful for longer windows. | 5m |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description is nearly empty. It does not disclose behavioral traits such as read-only nature, data source, or side effects.
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 only one line, but it is under-specified rather than genuinely concise. It lacks essential 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 8 parameters, no output schema, and sibling tools with overlapping functionality, this description is woefully incomplete. It does not explain expected results or use cases.
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%, so each parameter is already described in the schema. The description adds no additional meaning beyond the 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 'Sally skill ($0.001/call)' is vague and does not explain what the tool does. It fails to distinguish from sibling tools like health_insights or metabolic_overview.
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?
No guidance is provided on when to use this tool versus alternatives. The description gives no context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
metabolic_overviewDInspect
Sally skill ($0.005/call)
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | Target date YYYY-MM-DD (defaults to today UTC). All other CGM data is fetched from the DB. | |
| timezone | No | IANA timezone for postprandial timing context (e.g. "America/New_York"). Defaults to UTC. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden for behavioral traits. It discloses nothing about side effects, permissions, or what the tool does internally. The only behavioral hint is cost, which is insufficient.
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 short but underspecified. Conciseness should provide adequate information in few words; here it omits essential purpose, leading to under-specification rather than conciseness.
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?
No output schema exists, yet the description doesn't explain return values or tool behavior. Given the tool's apparent medical/fitness context, the description is completely inadequate for an agent to understand what calling this tool produces.
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% and the schema already clearly describes both parameters (date and timezone) with format, defaults, and purpose. The description adds no additional meaning beyond cost, but baseline 3 is appropriate as schema compensates.
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 'Sally skill ($0.005/call)' fails to state what the tool does. It does not indicate that this tool provides a metabolic overview, nor does it clarify the verb or resource. It is misleading as it only mentions a skill name and cost.
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?
No guidance is provided on when to use this tool versus sibling tools like analyze_lab_result or chat_with_sally. The description does not include context, prerequisites, or scenarios for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
supplement_gradingDInspect
Sally skill ($0.008/call)
| Name | Required | Description | Default |
|---|---|---|---|
| language | No | BCP-47 short code (e.g. 'en', 'id'). Omit for auto-detect from the stack text. | |
| use_labs | No | If true (default), the agent may read the calling user's lab results to surface biomarker-relevant gaps. Set false for a stack-only audit with no PHI. | |
| supplements | Yes | The supplement stack to audit — names + doses as free text or a list (e.g. "vitamin D 5000IU, magnesium glycinate 400mg, fish oil 1g"). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states a cost, offering no information about side effects, permissions, data access, or operational characteristics.
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 short but not effectively concise—it omits essential information. It lacks front-loaded purpose and does not earn its place with meaningful content.
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 tool's apparent complexity (grading supplements, optional PHI handling via use_labs) and no output schema, the description is entirely inadequate. It fails to explain return values, behavior, or expected outcomes.
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 description adds no meaning beyond the input schema. However, schema description coverage is 100%, and each parameter (language, use_labs, supplements) has a clear description. Baseline 3 applies because the schema already provides adequate parameter documentation.
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 is merely 'Sally skill ($0.008/call)', which fails to state a verb or resource. It provides no indication that the tool grades supplements or performs any specific action. It does not distinguish from siblings like analyze_lab_result or chat_with_sally.
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 guidance on when to use this tool versus alternatives. The description offers no context, prerequisites, or exclusions, leaving the agent without any decision support.
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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