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xano_xanoscript_docs

Read-onlyIdempotent

Retrieve XanoScript documentation for code generation. Use topics, file paths, or tiered summaries to get the exact reference you need.

Instructions

Get XanoScript programming language documentation for AI code generation. Call without parameters for overview (README). For context-limited models: use tier='survival' (~800 tokens) or tier='working' (~3500 tokens). Use 'topic' for specific documentation, or 'file_path' for context-aware docs based on the file you're editing. Use mode='quick_reference' for compact syntax reference (recommended for context efficiency). Use max_tokens to limit documentation size to fit your context budget. file_path mode defaults to 'quick_reference' to reduce context size; use mode='full' to get complete docs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoDocumentation topic to retrieve. Call without any parameters to get the README overview. Example: topic='syntax' for language syntax, topic='database' for database operations, topic='types' for type system. Available topics: survival (Minimal syntax survival kit for writing valid XanoScript (~3KB)), working (Complete working reference for common XanoScript tasks (~12KB)), readme (XanoScript overview, workspace structure, and quick reference), essentials (Common patterns, quick reference, and common mistakes to avoid), syntax (Expressions, operators, and filters for all XanoScript code), syntax/string-filters (String filters, regex, encoding, security filters, text functions), syntax/array-filters (Array filters, functional operations, and array functions), syntax/functions (Math filters/functions, object functions, bitwise operations), types (Data types, input blocks, and validation), tables (Database schema definitions with indexes and relationships), functions (Reusable function stacks with inputs and responses), apis (HTTP endpoint definitions with authentication and CRUD patterns), tasks (Scheduled and cron jobs), triggers (Event-driven handlers (table, realtime, workspace, agent, MCP)), database (All db), agents (AI agent configuration with LLM providers and tools), tools (AI tools for agents and MCP servers), mcp-servers (MCP server definitions exposing tools), unit-testing (Unit tests, mocks, and assertions within functions, APIs, and middleware), workflow-tests (End-to-end workflow tests with data source selection and tags), integrations (External service integrations index - see sub-topics for details), integrations/cloud-storage (AWS S3, Azure Blob, and GCP Storage operations), integrations/search (Elasticsearch, OpenSearch, and Algolia search operations), integrations/redis (Redis caching, rate limiting, and queue operations), integrations/external-apis (HTTP requests with api), integrations/utilities (Local storage, email, zip, and Lambda utilities), frontend (Static frontend development and deployment), addons (Reusable subqueries for fetching related data), debugging (Logging, inspecting, and debugging XanoScript execution), performance (Performance optimization best practices), realtime (Real-time channels and events for push updates), security (Security best practices for authentication and authorization), streaming (Streaming data from files, requests, and responses), middleware (Request/response interceptors for functions, queries, tasks, and tools), branch (Branch-level settings: middleware, history retention, visual styling), workspace (Workspace-level settings: environment variables, preferences, realtime)
file_pathNoFile path being edited. Returns all relevant docs automatically based on the file type and location. Uses applyTo pattern matching to select applicable topics. Example: 'api/users/create.xs' returns API, database, and syntax docs. 'function/format.xs' returns function and syntax docs.
modeNo'full' = complete documentation with explanations and examples. 'quick_reference' = compact reference with just syntax patterns and signatures. 'index' = compact topic listing with descriptions and byte sizes (~1KB). Use 'index' to discover available topics before loading them. Use 'quick_reference' to save context window space when you just need a reminder. Default: 'full' for topic mode, 'quick_reference' for file_path mode.
tierNoPre-packaged documentation tier for context-limited models. 'survival' (~3KB, ~800 tokens): minimum syntax to write valid XanoScript. 'working' (~12KB, ~3500 tokens): complete reference for common tasks. Overrides topic/file_path/mode when set. Use 'survival' for models with <16K context, 'working' for 16-64K context.
max_tokensNoMaximum estimated token budget for documentation. When used with file_path, loads topics in priority order until budget is reached. Helps prevent context overflow for small-window models. Estimate: 1KB of docs ≈ 250 tokens.
exclude_topicsNoList of topic names to exclude from file_path results. Use this to skip topics you've already loaded (e.g., exclude_topics: ['syntax', 'essentials']). Only applies when using file_path parameter.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
documentationNoThe documentation content (topic or README mode).
file_pathNoThe file path that was matched (file_path mode only).
modeNoThe documentation mode used.
tierNoThe pre-packaged tier used, if any.
versionNoThe XanoScript documentation version.
topicsNoList of matched topic names (file_path mode only).
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare the tool as read-only, non-destructive, and idempotent. The description adds value beyond annotations by detailing behavioral traits such as parameter precedence (tier overrides others), default modes per parameter, and token budget estimation. It also explains the open-world hint is false (limited topics). No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively long but every sentence adds value. It is front-loaded with the core purpose, then organized by parameter guidance. It avoids redundancy with schema. Could be slightly more concise, but given the complexity (6 parameters, multiple use cases), the length is justified.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (6 parameters, rich schema, output schema, annotations), the description covers all necessary aspects: parameter interactions, defaults, use cases for different context windows, and budget management. It leaves no ambiguity about how to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with detailed descriptions and enums. The description adds high-level guidance like using 'survival' for <16K context and the interaction between parameters, which is not in the schema. However, much of the parameter info is already in the schema, so the added value is moderate. A score of 4 reflects the helpful extra context without being essential.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves XanoScript programming language documentation for AI code generation. It is specific about the resource (XanoScript docs) and verb (get). While it doesn't explicitly distinguish from siblings, the siblings are for different domains (CLI, meta API, validate, version), so the purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides comprehensive guidance: call without parameters for overview, use tier for context-limited models, topic for specific docs, file_path for context-aware docs, mode for compact reference, and max_tokens for budget. It explains when to use each parameter and gives concrete examples. This is explicit and actionable.

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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