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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Full call logging
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Tool access control
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Managed credentials
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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
6 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?
The description provides no behavioral information. It does not disclose whether the tool is read-only, what it modifies, or any side effects. Given no annotations, this is a critical gap.
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 brief but fails to convey the tool's purpose or behavior, making it inefficient rather than concise. Every sentence should earn its place; this one does not.
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 is almost entirely missing. For a tool that takes a base64 PDF and returns analysis, the description should explain the output, the OCR process, and any limitations. The current description provides no context, making it impossible for an AI to select or invoke this tool correctly.
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 three parameters have adequate descriptions in the input schema (100% coverage). The description adds no additional semantic value beyond what the schema provides, so a baseline score of 3 is appropriate.
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 only provides a pricing label and skill name ('Sally skill ($0.008/call)'), lacking any verb or resource indicating the tool's function. The purpose is implied only by the tool name, but the description fails to clarify what the tool does.
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 usage context is provided. There is no indication of when to use this tool versus siblings like chat_with_sally or food_journal, nor any guidance on prerequisites or alternatives.
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 present, and the description offers no behavioral details (e.g., that it is a chat, uses health data, or any side effects). The agent is left completely uninformed.
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 necessary content. Conciseness without substance is under-specification.
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 presence of 4 parameters and related sibling tools in the health domain, the description fails to explain the tool's function, input semantics, or output, making it severely incomplete.
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% (3 of 4 parameters described), so the schema already conveys parameter meanings. The description adds no additional clarification, earning a baseline score.
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 ($0.003/call)' does not state what the tool does. No verb or resource is mentioned, leaving the agent unable to discern the tool's purpose.
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 its siblings (analyze_lab_result, food_journal, etc.). The agent lacks any basis for selection.
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?
In the absence of annotations, the description carries full responsibility for behavioral transparency, yet it states nothing about side effects, data handling, permission requirements, or execution details like whether it stores data or performs analysis.
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?
While the description is short, it is severely under-specified, not concise. Conciseness requires efficient communication of essential information, which is entirely absent here.
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, no annotations, and the domain of food journaling which likely involves image analysis or logging, the description is critically incomplete. It fails to indicate return values, side effects, or operational context.
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 descriptions for both parameters ('image_b64' and 'mime'). The tool description adds no extra semantic value beyond the schema, but the schema itself is adequately descriptive for the parameters, meeting the baseline of 3.
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 ($0.004/call)' does not specify any action or resource. It lacks a verb describing what the tool does, making it impossible for an agent to distinguish its purpose from sibling tools 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?
No usage guidelines are provided. The description gives no indication of when to use this tool versus its siblings, such as 'analyze_lab_result' or 'health_insights', leaving the agent without decision-making criteria.
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?
With no annotations, the description carries the full burden of disclosing behavioral traits. It mentions nothing about side effects, permissions, rate limits, or output format, leaving the agent with no insight into the tool's behavior beyond its name.
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?
While brief, the description is under-specified rather than concise. It contains only a name and cost, failing to provide any functional context. Every sentence should add value; this one does not.
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 4 parameters and no output schema, the description should explain what insights are generated, but it provides zero contextual information. It is completely inadequate for helping an agent select or invoke the tool correctly.
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 with clear details for each parameter. The description adds no extra meaning beyond the schema, meeting the baseline for this dimension.
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 ($0.003/call)' does not state what the tool does. It only mentions a name and cost, lacking a verb or resource. The tool name 'health_insights' hints at its function, but the description fails to confirm or elaborate, making it nearly useless for distinguishing from siblings.
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 alternatives such as 'analyze_lab_result' or 'metabolic_overview'. The description provides no context for appropriate usage.
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 (FREE)
| 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 does not disclose any behavioral traits (e.g., read/write, side effects, auth needs). The tool's behavior is entirely 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?
The description is extremely short but lacks substance. It fails to communicate purpose, making it under-specified rather than concise.
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 and 8 parameters, the description provides no context on return values, behaviour, or usage. It is completely inadequate for an AI agent to select or invoke the tool correctly.
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 with detailed parameter descriptions (patterns, defaults, enums). The tool description adds no value beyond the schema, so baseline 3 is appropriate.
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 (FREE)' provides no verb or resource, and does not distinguish this tool from siblings like 'health_insights' or 'chat_with_sally'. It is essentially a tautology of the tool name.
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 vs alternatives. No context or when-not-to-use instructions are provided.
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?
With no annotations, the description should disclose behavioral traits, but it provides none. It fails to mention any side effects, prerequisites, or return 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 too short, but not due to efficiency; it omits essential information. It is under-specified.
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?
Despite only 2 parameters and no output schema, the description fails to convey the tool's purpose, making it completely inadequate for an agent to select or invoke correctly.
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 baseline is 3. The description adds no value beyond the schema, but the schema itself clearly documents the parameters.
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 'Sally skill ($0.005/call)', which is a tautology and lacks any indication of what the tool does. 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?
No guidance is provided on when to use this tool versus alternatives. The description gives no context for appropriate usage.
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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