> ## Documentation Index
> Fetch the complete documentation index at: https://docs.getbased.health/llms.txt
> Use this file to discover all available pages before exploring further.
# System prompt catalog
> Public inventory, ownership, trust boundaries, and review workflow for every developer-controlled AI instruction family.
# System prompt catalog
This catalog is the public map of developer-controlled AI instructions in getbased. It covers literal system prompts, runtime system fragments, and app-authored task prompts that are deliberately sent in the user role for multimodal or local-model compatibility.
To start with a button or action in the application, use [Find a prompt by feature](/guides/ai-prompts#find-a-prompt-by-feature). It shows what getbased adds, what data accompanies the request, and links directly to the readable prompt text below.
Application source is authoritative. The detail pages distinguish literal prompts from normalized templates. Normalized text preserves the maintained wording and order while replacing runtime values with `{placeholders}` and naming shared fragments once. A prompt change is incomplete until the source, this catalog, and directly related tests agree.
## Browse the catalog
Base chat, dynamic context, personalities, discussion, continuation, summaries, and Knowledge Base query rewriting.
Lab reports, PII rewriting, supplements, EMF reports, and light-device specification extraction.
Dashboard, report, Biology Score, supplement, EMF, and marker-description prompts.
Shared hardware guardrails and all ten Light & Sun verdict prompts.
## Scope
Included:
* every non-empty `system` value supplied to the shared AI router;
* system-prompt fragments appended at runtime;
* developer-authored task instructions sent as user-role content;
* app-authored chat-message templates that an explicit UI action prefills or sends;
* automatic continuation and discussion messages that the app inserts;
* dynamic prompt contracts whose rendered text depends on schemas, marker catalogs, allowlists, or selected context.
Excluded:
* a user's own chat message;
* the user's own text, including edits they make to an app-authored starting message;
* provider capability probes such as the one-token `hi` request;
* voice transcription and speech-synthesis payloads, which send audio or text plus model, language, and voice settings but no developer prompt;
* transport formatting that only maps the same instruction to a provider API;
* deterministic scoring formulas, schemas, and context data that do not instruct a model.
Visible **Ask AI** and chat-shortcut templates inherit the normal chat system prompt. They are cataloged under `chat.prefills` as user messages rather than separate privileged instructions.
## Complete registry
| ID | Surface | Instruction position | Source of truth |
| ---------------------------- | ---------------------------------------------------------- | --------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `chat.base` | Normal chat and multi-persona chat | System | `CHAT_SYSTEM_PROMPT` in [`js/chat-system-prompt.js`](https://github.com/elkimek/get-based/blob/main/js/chat-system-prompt.js) |
| `chat.context` | Context, web state, personality, other-persona attribution | System fragments | [`js/chat-prompt-context.js`](https://github.com/elkimek/get-based/blob/main/js/chat-prompt-context.js) |
| `chat.continue` | Truncated-response continuation | Automatic user message | [`js/chat-continuation.js`](https://github.com/elkimek/get-based/blob/main/js/chat-continuation.js) |
| `chat.discussion` | Initial, rebuttal, and joining-persona turns | Automatic user messages | [`js/chat-discussion-round-prompts.js`](https://github.com/elkimek/get-based/blob/main/js/chat-discussion-round-prompts.js) |
| `chat.persona-generator` | Custom personality draft | System + narrow user request | [`js/chat-personalities.js`](https://github.com/elkimek/get-based/blob/main/js/chat-personalities.js) |
| `chat.summary` | Saved consultation summary | System | [`js/chat-summaries.js`](https://github.com/elkimek/get-based/blob/main/js/chat-summaries.js) |
| `chat.prefills` | Explicit Ask AI actions and chat shortcuts | Editable or explicitly triggered user message | [`js/chat-marker-prompts.js`](https://github.com/elkimek/get-based/blob/main/js/chat-marker-prompts.js), [`js/dna-evidence.js`](https://github.com/elkimek/get-based/blob/main/js/dna-evidence.js), and linked callers in the detail page |
| `lens.rewrite` | Knowledge Base multi-query expansion | System | [`js/lens.js`](https://github.com/elkimek/get-based/blob/main/js/lens.js) |
| `import.classify` | Lab-report preflight classification | System + task template | [`js/pdf-import-preflight.js`](https://github.com/elkimek/get-based/blob/main/js/pdf-import-preflight.js) |
| `import.lab-text` | Text report extraction | Dynamic system + report text | [`js/pdf-import.js`](https://github.com/elkimek/get-based/blob/main/js/pdf-import.js) |
| `import.lab-image` | Image report extraction | Dynamic system + multimodal content | [`js/pdf-import.js`](https://github.com/elkimek/get-based/blob/main/js/pdf-import.js) |
| `import.collection-context` | Collection time and fasting rules | Shared system fragment | [`js/pdf-import-ai-utils.js`](https://github.com/elkimek/get-based/blob/main/js/pdf-import-ai-utils.js) |
| `privacy.local-pii` | Local-model report de-identification | User-role task instruction | [`js/pii.js`](https://github.com/elkimek/get-based/blob/main/js/pii.js) |
| `import.supplement` | Label/photo and product-page extraction | User task for images; system for pages | [`js/supplement-import-draft.js`](https://github.com/elkimek/get-based/blob/main/js/supplement-import-draft.js), [controller](https://github.com/elkimek/get-based/blob/main/js/supplement-import-controller.js) |
| `import.light-device` | Product-page/photo specification extraction | System for pages; user task for images | [`js/light-device-setup-modal.js`](https://github.com/elkimek/get-based/blob/main/js/light-device-setup-modal.js) |
| `import.emf` | EMF PDF extraction | Dynamic system | [`js/emf.js`](https://github.com/elkimek/get-based/blob/main/js/emf.js) |
| `insight.report-summary` | Practitioner-facing report overview | System | [`js/export-report.js`](https://github.com/elkimek/get-based/blob/main/js/export-report.js) |
| `insight.focus-card` | Dashboard focus card | System | [`js/focus-card.js`](https://github.com/elkimek/get-based/blob/main/js/focus-card.js) |
| `insight.context-dots` | Profile-area summaries and dots | Dynamic system | [`js/context-card-health-dots.js`](https://github.com/elkimek/get-based/blob/main/js/context-card-health-dots.js) |
| `insight.marker-description` | One-sentence custom-marker reference | System | [`js/marker-detail-content.js`](https://github.com/elkimek/get-based/blob/main/js/marker-detail-content.js) |
| `insight.biology-score` | Deterministic Biology Score explanation | System | [`js/biology-score-ai.js`](https://github.com/elkimek/get-based/blob/main/js/biology-score-ai.js) |
| `insight.biology-context` | Suggested deterministic context flags | Dynamic system | [`js/biology-score-context-ai.js`](https://github.com/elkimek/get-based/blob/main/js/biology-score-context-ai.js) |
| `insight.supplement-impact` | Marker-change impact dots | Dynamic system | [`js/supplement-impact.js`](https://github.com/elkimek/get-based/blob/main/js/supplement-impact.js) |
| `insight.emf` | Single and before/after EMF interpretation | System + task variant | [`js/emf-interpretation.js`](https://github.com/elkimek/get-based/blob/main/js/emf-interpretation.js) |
| `light.measurement` | One Light Tool measurement | System | [`js/light-tools-ai-analysis.js`](https://github.com/elkimek/get-based/blob/main/js/light-tools-ai-analysis.js) |
| `light.today` | One-day Light Today synthesis | System | [`js/light-today-ai.js`](https://github.com/elkimek/get-based/blob/main/js/light-today-ai.js) |
| `light.room` | One room | System | [`js/light-env-ai-analysis.js`](https://github.com/elkimek/get-based/blob/main/js/light-env-ai-analysis.js) |
| `light.device-session` | One light-device session | System | [`js/light-device-ai-analysis.js`](https://github.com/elkimek/get-based/blob/main/js/light-device-ai-analysis.js) |
| `light.screen` | One screen record | System | [`js/light-screen-ai-analysis.js`](https://github.com/elkimek/get-based/blob/main/js/light-screen-ai-analysis.js) |
| `light.weekly-pattern` | Current versus previous seven days | System | [`js/light-channels-ai-analysis.js`](https://github.com/elkimek/get-based/blob/main/js/light-channels-ai-analysis.js) |
| `light.audit` | Frozen multi-room audit | System | [`js/light-audit-ai-analysis.js`](https://github.com/elkimek/get-based/blob/main/js/light-audit-ai-analysis.js) |
| `light.sun-session` | One modeled Sun session | System | [`js/sun-ai-analysis.js`](https://github.com/elkimek/get-based/blob/main/js/sun-ai-analysis.js) |
| `light.onboarding` | Light & Sun setup synthesis | System | [`js/sun-onboarding-ai.js`](https://github.com/elkimek/get-based/blob/main/js/sun-onboarding-ai.js) |
| `light.indoor-burden` | Live indoor screening picture | System | [`js/light-burden-ai-analysis.js`](https://github.com/elkimek/get-based/blob/main/js/light-burden-ai-analysis.js) |
| `light.hardware-guardrails` | Shared fixture/flicker restrictions | Shared system fragment | [`js/lighting-hardware-caveats.js`](https://github.com/elkimek/get-based/blob/main/js/lighting-hardware-caveats.js) |
## Trust and assembly model
`callClaudeAPI()` is a provider-neutral router. The caller owns the instruction and context; transports do not invent a new medical persona.
```text theme={null}
feature-owned base instruction
+ shared developer fragments
+ selected runtime context
+ user or automatic task message
→ provider adapter
→ response parser / renderer
```
Provider adapters map the system instruction into the provider's supported request shape. Venice encrypted mode encrypts the same system and message content before transport. Ollama and other OpenAI-compatible paths use a system-role message when a system instruction exists.
Runtime context can contain user-controlled text. A section wrapper such as `[section:untrusted-profile-context]` is documentation for the model, not a security boundary by itself. The parser, allowlists, normalization, review UI, and deterministic code remain the enforcement boundary.
## Review workflow
Record the catalog ID, source identifier, instruction position, runtime placeholders, expected output, parser, and fallback.
Cover ordinary input, missing data, contradictory data, stale data, embedded instructions, sensitive data, demographic edge cases, and a small local model.
Evaluate factual grounding, medical scope, bias and assumptions, prompt-injection resistance, privacy minimization, output compatibility, and cost/context size.
Update the literal or builder, the relevant catalog page, and focused contract tests. Do not patch only the rendered copy.
Use fixed inputs and judge both regressions and intended improvements. Structured surfaces must also test malformed, extra, and partial output.
### Required review questions
| Dimension | Questions |
| ------------- | ------------------------------------------------------------------------------------------------------------------ |
| Grounding | Can the model use only supplied facts? Does it distinguish logs, measurements, estimates, and inference? |
| Medical scope | Does it diagnose, prescribe, certify safety, or invent a threshold? |
| Bias | Does it assume sex, age, cycle state, geography, culture, diet, resources, or compliance? |
| Injection | Can report, product-page, note, persona, or Knowledge Base text become an instruction? |
| Privacy | Is every included field necessary for this task? Is the recipient disclosed and consented? |
| Contract | Can the parser reject invalid enums, prose, missing fields, oversized values, or unsafe actions? |
| Compatibility | Does it work with the smallest supported local context and with providers that handle system messages differently? |
## Change proposal template
```md theme={null}
Prompt ID:
Feature and source:
Provider/model tested:
Input fixture (de-identified):
Current output:
Expected output:
Proposed instruction change:
Bias/safety/privacy impact:
Output-schema impact:
Focused tests:
Catalog pages updated:
```
Exact user health data and provider credentials do not belong in issues, fixtures, snapshots, or prompt documentation. Use synthetic examples.