Builtin Skills

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Built-in Skills

For AI agents: a documentation index is available at the root level at /llms.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.

Available Skills

Skill	Description	Requirements
`datetime`	Date/time information	pytz
`math`	Mathematical calculations	(none)
`web_search`	Web search via Google API	API key
`wikipedia_search`	Wikipedia lookups	(none)
`weather_api`	Weather information	API key
`joke`	Tell jokes	(none)
`play_background_file`	Play audio files	(none)
`swml_transfer`	Transfer to SWML endpoint	(none)
`datasphere`	DataSphere document search	API credentials
`native_vector_search`	Local vector search	search extras
`mcp_gateway`	MCP server integration	MCP Gateway service
`google_maps`	Address validation & routing	Google Maps API key
`info_gatherer`	Structured question collection	(none)
`claude_skills`	Load SKILL.md files as tools	PyYAML
`api_ninjas_trivia`	Trivia questions from API Ninjas	API key
`ask_claude`	Anthropic Claude reasoning / sub-queries	`ANTHROPIC_API_KEY`
`custom_skills`	Register one-off SWAIG tools from config	(none)
`datasphere_serverless`	DataSphere search via DataMap (no server callback)	API credentials
`spider`	Web scraping & crawling	`cheerio` (TS) / `lxml` (Python)

datetime

Get current date and time information with timezone support. This is one of the most commonly used skills, callers often ask “what time is it?” or need scheduling help.

Functions:

get_current_time - Get current time in a timezone
get_current_date - Get today’s date

Requirements:pytz package (usually installed automatically)

Parameters:

This skill takes no configuration parameters. Timezone is specified per call via the timezone argument on get_current_time; UTC is the default when omitted.

Output format:

Time: “The current time in America/New_York is 2:30 PM”
Date: “Today’s date is November 25, 2024”

Common use cases:

“What time is it?” / “What time is it in Tokyo?”
“What’s today’s date?”
Scheduling and appointment contexts
Time zone conversions

Limitations:

Requires valid timezone names (e.g., “America/New_York”, not “EST”)
Doesn’t do time math or calculate durations
Doesn’t handle historical dates

Language	Adding datetime
Python	`self.add_skill("datetime")`
TypeScript	`await agent.addSkillByName('datetime')`

from signalwire import AgentBase

class TimeAgent(AgentBase):
    def __init__(self):
        super().__init__(name="time-agent")
        self.add_language("English", "en-US", "rime.spore")

        self.add_skill("datetime")

        self.prompt_add_section(
            "Role",
            "You help users with date and time information."
        )

math

Perform mathematical calculations safely. The skill uses a secure expression evaluator that supports common operations without executing arbitrary code.

Functions:

calculate - Evaluate mathematical expressions

Requirements: None

Parameters:

This skill takes no configuration parameters. The registered tool is always named calculate.

Supported operations:

Basic: +, -, *, /, ** (power), % (modulo)
Functions: sqrt, sin, cos, tan, log, abs, round
Constants: pi, e
Parentheses for grouping

Common use cases:

“What’s 15 percent of 230?”
“Calculate 45 times 67”
“What’s the square root of 256?”
Price calculations, tip calculations

Limitations:

Limited to supported functions (no arbitrary Python)
Large numbers may lose precision
Can’t solve equations or do symbolic math

from signalwire import AgentBase

class CalculatorAgent(AgentBase):
    def __init__(self):
        super().__init__(name="calculator")
        self.add_language("English", "en-US", "rime.spore")

        self.add_skill("math")

        self.prompt_add_section(
            "Role",
            "You are a calculator that helps with math."
        )

web_search

Search the web using Google Custom Search API. Results are filtered for quality and summarized for voice delivery.

Functions:

web_search - Search the web and return summarized results

Requirements:

Google Custom Search API key (from Google Cloud Console)
Search Engine ID (from Programmable Search Engine)

Setup:

Create a project in Google Cloud Console
Enable the Custom Search JSON API
Create an API key
Create a Programmable Search Engine at https://programmablesearchengine.google.com/
Get the Search Engine ID

Parameters:

Parameter	Type	Description	Default
`api_key`	string	Google API key (falls back to `GOOGLE_SEARCH_API_KEY`)	Required
`search_engine_id`	string	Search engine ID (falls back to `GOOGLE_SEARCH_ENGINE_ID`)	Required
`tool_name`	string	Custom function name (set per instance)	“web_search”
`num_results`	integer	Results to return	3
`delay`	number	Seconds between requests	0.5
`max_content_length`	integer	Max characters of scraped page content	32768
`oversample_factor`	number	Fetch extra results then re-rank	2.5
`min_quality_score`	number	Quality threshold (0-1)	0.3
`no_results_message`	string	Message returned when nothing matches	default
`safe_search`	string	`"off"`, `"medium"`, or `"high"`	”medium”

Multi-instance support: Yes - add multiple instances with unique tool_name values (e.g. search_news, search_docs).

from signalwire import AgentBase

class SearchAgent(AgentBase):
    def __init__(self):
        super().__init__(name="search-agent")
        self.add_language("English", "en-US", "rime.spore")

        self.add_skill("web_search", {
            "api_key": "YOUR_GOOGLE_API_KEY",
            "search_engine_id": "YOUR_SEARCH_ENGINE_ID",
            "num_results": 3
        })

        self.prompt_add_section(
            "Role",
            "You search the web to answer questions."
        )

wikipedia_search

Search Wikipedia for information. A free, no-API-key alternative to web search for factual queries.

Functions:

search_wikipedia - Search and retrieve Wikipedia article summaries

Requirements: None (uses public Wikipedia API)

Parameters:

Parameter	Type	Description	Default
`num_results`	integer	Max articles returned (1-5)	1
`no_results_message`	string	Message returned when nothing matches	default template

from signalwire import AgentBase

class WikiAgent(AgentBase):
    def __init__(self):
        super().__init__(name="wiki-agent")
        self.add_language("English", "en-US", "rime.spore")

        self.add_skill("wikipedia_search", {
            "num_results": 3  # Return up to three articles
        })

        self.prompt_add_section(
            "Role",
            "You look up information on Wikipedia to answer factual questions."
        )

weather_api

Get current weather information for locations worldwide. Commonly used for small talk, travel planning, and location-aware services.

Functions:

get_weather - Get current weather conditions for a location

Requirements: WeatherAPI.com API key (free tier available)

Setup:

Sign up at https://www.weatherapi.com/
Get your API key from the dashboard
Free tier allows 1 million calls/month

Parameters:

Parameter	Type	Description	Default
`api_key`	string	WeatherAPI.com API key (falls back to `WEATHER_API_KEY`)	Required
`tool_name`	string	Custom function name	”get_weather”
`units`	string	`"metric"`, `"imperial"`, `"standard"`, `"celsius"`, or `"fahrenheit"`	”fahrenheit”

from signalwire import AgentBase

class WeatherAgent(AgentBase):
    def __init__(self):
        super().__init__(name="weather-agent")
        self.add_language("English", "en-US", "rime.spore")

        self.add_skill("weather_api", {
            "api_key": "YOUR_WEATHER_API_KEY"
        })

        self.prompt_add_section(
            "Role",
            "You provide weather information for any location."
        )

joke

Tell jokes to lighten the mood or entertain callers. Uses a curated joke database for clean, family-friendly humor.

Functions:

tell_joke - Get a random joke

Requirements: None

Parameters:

Parameter	Type	Description	Default
`tool_name`	string	Custom function name	”tell_joke”

from signalwire import AgentBase

class FunAgent(AgentBase):
    def __init__(self):
        super().__init__(name="fun-agent")
        self.add_language("English", "en-US", "rime.spore")

        self.add_skill("joke")

        self.prompt_add_section(
            "Role",
            "You are a fun assistant that tells jokes when asked."
        )

play_background_file

Play audio files in the background during calls. Audio plays while conversation continues, useful for hold music, ambient sound, or audio cues.

Functions:

play_background_file - Start playing audio file
stop_background_file - Stop currently playing audio

Requirements: None (audio file must be accessible via URL)

Parameters:

This skill supports two configuration styles:

Catalog mode, preload named files via files, caller selects by key:

Parameter	Type	Description	Default
`tool_name`	string	Custom play function name	”play_background_file”
`files`	array	List of `{ key, description, url, wait? }` entries	Required

Free-form mode, caller supplies a URL at call time (gated by allowed_domains):

Parameter	Type	Description	Default
`default_file_url`	string	URL played when no argument is provided	Required
`allowed_domains`	array	Whitelisted domains for caller-supplied URLs	Required

Supported formats: MP3, WAV, OGG

from signalwire import AgentBase

class MusicAgent(AgentBase):
    def __init__(self):
        super().__init__(name="music-agent")
        self.add_language("English", "en-US", "rime.spore")

        self.add_skill("play_background_file", {
            "files": [\
                {\
                    "key": "hold_music",\
                    "description": "Looping hold music",\
                    "url": "https://example.com/hold-music.mp3",\
                }\
            ]
        })

swml_transfer

Transfer calls to another SWML endpoint.

Functions:

transfer_call (default name) - Transfer based on matched pattern

Requirements: None

Parameters:

Parameter	Type	Description	Default
`transfers`	object	Pattern → `{ url	address, message?, return_message?, post_process?, final?, from_addr? }`
`patterns`	array	Alternative shape: list of pattern entries	Required (or use `transfers`)
`allow_arbitrary`	boolean	Accept caller-supplied URL instead of matching a pattern	false
`tool_name`	string	Custom function name	”transfer_call”
`description`	string	Tool description	default
`parameter_name`	string	Argument name the LLM supplies	”transfer_type”
`parameter_description`	string	Argument description	default
`default_message`	string	Message when no pattern matches	default
`default_post_process`	boolean	Default for transferred calls returning to the agent	false
`required_fields`	object	Extra per-pattern required fields	`{}`

from signalwire import AgentBase

class TransferAgent(AgentBase):
    def __init__(self):
        super().__init__(name="transfer-agent")
        self.add_language("English", "en-US", "rime.spore")

        self.add_skill("swml_transfer", {
            "transfers": {
                "specialist": {
                    "url": "https://your-server.com/other-agent",
                    "message": "Transferring you to a specialist."
                }
            }
        })

datasphere

Search SignalWire DataSphere documents.

Functions:

search_knowledge (default name) - Search uploaded documents

Requirements: DataSphere API credentials

Parameters:

Parameter	Type	Description	Default
`space_name`	string	DataSphere space name	Required
`project_id`	string	Project ID (falls back to `SIGNALWIRE_PROJECT_ID`)	Required
`token`	string	API token (falls back to `SIGNALWIRE_TOKEN`)	Required
`document_id`	string	Document ID to search within	Required
`tool_name`	string	Custom function name	”search_knowledge”
`count`	integer	Results to return (1-10)	1
`distance`	number	Distance threshold (0-10)	3.0
`tags`	array	Filter by document tags	,
`language`	string	Language filter	,
`pos_to_expand`	array	POS tags to expand (`NOUN`, `VERB`, `ADJ`, `ADV`)	,
`max_synonyms`	integer	Synonym expansion limit (1-10)	,
`no_results_message`	string	Message when nothing matches	default

from signalwire import AgentBase

class KnowledgeAgent(AgentBase):
    def __init__(self):
        super().__init__(name="knowledge-agent")
        self.add_language("English", "en-US", "rime.spore")

        self.add_skill("datasphere", {
            "space_name": "your-space",
            "project_id": "YOUR_PROJECT_ID",
            "token": "YOUR_API_TOKEN",
            "document_id": "your-document-id"
        })

native_vector_search

Local vector search using .swsearch index files.

Functions:

Dynamic name (default search_knowledge) - Search a local vector index

Requirements: Search extras installed (pip install "signalwire-sdk[search]")

Parameters:

Parameter	Type	Description	Default
`tool_name`	string	Custom function name	”search_knowledge”
`index_file`	string	SQLite `.swsearch` path (SQLite backend)	,
`backend`	string	`"sqlite"` or `"pgvector"`	”sqlite”
`connection_string`	string	PostgreSQL URL (pgvector backend)	,
`collection_name`	string	Table/collection name (pgvector backend)	,
`build_index`	boolean	Rebuild index on startup	false
`source_dir`	string	Source directory when building	,
`remote_url`	string	Remote search-server URL (alternative to local index)	,
`index_name`	string	Named index on remote server	”default”
`count`	integer	Results to return (1-20)	5
`similarity_threshold`	number	Minimum score (0.0-1.0)	0.0
`tags`	array	Filter results by tag	`[]`
`global_tags`	array	Always-applied tag filter	`[]`
`file_types`	array	File extensions to index	`["md","txt","pdf","docx","html"]`
`exclude_patterns`	array	Glob patterns to skip	defaults
`no_results_message`	string	Message when nothing matches	default template
`response_prefix`	string	Prepended to result text	,
`response_postfix`	string	Appended to result text	,
`max_content_length`	integer	Max result chars	32768
`description`	string	Tool description override	,

from signalwire import AgentBase

class LocalSearchAgent(AgentBase):
    def __init__(self):
        super().__init__(name="local-search")
        self.add_language("English", "en-US", "rime.spore")

        self.add_skill("native_vector_search", {
            "index_file": "/path/to/knowledge.swsearch",
            "tool_name": "search_docs"
        })

mcp_gateway

Connect to MCP (Model Context Protocol) servers via the MCP Gateway service. This skill dynamically creates SWAIG functions from MCP tools, enabling your agent to use any MCP-compatible tool.

Functions: Dynamically created based on connected MCP services

Requirements:

MCP Gateway service running
Gateway URL and authentication credentials

Parameters:

Parameter	Type	Description	Default
`gateway_url`	string	MCP Gateway service URL	Required
`auth_user`	string	Basic auth username	None
`auth_password`	string	Basic auth password	None
`auth_token`	string	Bearer token (alternative auth)	None
`services`	array	Services and tools to enable	All
`session_timeout`	integer	Session timeout (seconds)	300
`tool_prefix`	string	Prefix for function names	”mcp_“
`retry_attempts`	integer	Connection retries	3
`request_timeout`	integer	Request timeout (seconds)	30
`verify_ssl`	boolean	Verify SSL certificates	true

How it works:

Skill connects to gateway and discovers available tools
Each MCP tool becomes a SWAIG function (e.g., mcp_todo_add_todo)
Sessions persist per call_id, enabling stateful tools
Session automatically closes when call ends

from signalwire import AgentBase

class MCPAgent(AgentBase):
    def __init__(self):
        super().__init__(name="mcp-agent")
        self.add_language("English", "en-US", "rime.spore")

        self.add_skill("mcp_gateway", {
            "gateway_url": "http://localhost:8080",
            "auth_user": "admin",
            "auth_password": "secure-password",
            "services": [\
                {"name": "todo", "tools": "*"},\
                {"name": "calculator", "tools": ["add", "multiply"]}\
            ]
        })

        self.prompt_add_section(
            "Role",
            "You help users manage tasks and perform calculations."
        )

google_maps

Validate addresses and compute driving routes using Google Maps. Supports geocoding, spoken number normalization (e.g., “seven one four” becomes “714”), and location-biased search.

Functions:

lookup_address - Validate and geocode a street address or business name
compute_route - Compute driving distance and estimated travel time between two points

Requirements: Google Maps API key with Geocoding and Routes APIs enabled

Parameters:

Parameter	Type	Description	Default
`api_key`	string	Google Maps API key (falls back to `GOOGLE_MAPS_API_KEY`)	Required
`lookup_tool_name`	string	Address lookup function name	”lookup_address”
`route_tool_name`	string	Route computation function name	”compute_route”
`geocode_tool_name`	string	Reverse-geocoding function name	”geocode_address”
`route_by_coords_tool_name`	string	Coord-based route function name	”compute_route_by_coords”
`default_mode`	string	`"driving"`, `"walking"`, `"bicycling"`, or `"transit"`	”driving”

from signalwire import AgentBase

class DeliveryAgent(AgentBase):
    def __init__(self):
        super().__init__(name="delivery-agent")
        self.add_language("English", "en-US", "rime.spore")

        self.add_skill("google_maps", {
            "api_key": "YOUR_GOOGLE_MAPS_API_KEY"
        })

        self.prompt_add_section(
            "Role",
            "You help customers verify delivery addresses and estimate delivery times."
        )

info_gatherer

Gather answers to a configurable list of questions. This is the skill version of the InfoGathererAgent prefab, designed to be embedded within larger agents.

Functions:

start_questions - Begin the question sequence
submit_answer - Submit an answer and get the next question

Requirements: None

Parameters:

Parameter	Type	Description	Default
`questions`	list	List of question dictionaries (`key_name`, `question_text`, `confirm`, `prompt_add`)	Required
`prefix`	string	Prefix for tool names and namespace (enables multi-instance)	None
`completion_message`	string	Message read after the last question	default template

Multi-instance support: Yes - use the prefix parameter to run multiple question sets on a single agent. With prefix="intake", tools become intake_start_questions and intake_submit_answer, and state is stored under skill:intake in global_data.

from signalwire import AgentBase

class MultiFormAgent(AgentBase):
    def __init__(self):
        super().__init__(name="multi-form")
        self.add_language("English", "en-US", "rime.spore")

        # First question set
        self.add_skill("info_gatherer", {
            "prefix": "contact",
            "questions": [\
                {"key_name": "name", "question_text": "What is your name?"},\
                {"key_name": "email", "question_text": "What is your email?", "confirm": True}\
            ]
        })

        # Second question set
        self.add_skill("info_gatherer", {
            "prefix": "feedback",
            "questions": [\
                {"key_name": "rating", "question_text": "How would you rate our service?"},\
                {"key_name": "comments", "question_text": "Any additional comments?"}\
            ]
        })

claude_skills

Load Claude Code-style SKILL.md files as agent tools. Each SKILL.md file in the configured directory becomes a SWAIG function, with YAML frontmatter parsed for metadata (name, description, parameters).

Functions: Dynamically created from SKILL.md files (prefixed with claude_ by default)

Requirements: PyYAML package

Parameters:

Parameter	Type	Description	Default
`skills_path`	string	Path to directory containing SKILL.md files	Required
`include`	array	Glob patterns of SKILL.md files to load	`["*"]`
`exclude`	array	Glob patterns to skip	`[]`
`tool_prefix`	string	Prefix for generated function names	”claude_“
`prompt_title`	string	Section title added to agent prompt	”Claude Skills”
`prompt_intro`	string	Prose introducing the loaded skills	default template
`skill_descriptions`	object	Override descriptions, keyed by skill name	`{}`
`response_prefix`	string	Prepended to each skill response	,
`response_postfix`	string	Appended to each skill response	,
`allow_shell_injection`	boolean	Permit shell metacharacters in arguments	false
`allow_script_execution`	boolean	Permit running scripts referenced by a skill	false
`ignore_invocation_control`	boolean	Bypass per-skill invocation gating	false
`shell_timeout`	integer	Shell command timeout (seconds)	30

from signalwire import AgentBase

class ClaudeSkillsAgent(AgentBase):
    def __init__(self):
        super().__init__(name="claude-skills-agent")
        self.add_language("English", "en-US", "rime.spore")

        self.add_skill("claude_skills", {
            "skills_path": "/path/to/skills/directory",
            "tool_prefix": "skill_"
        })

Skills Summary Table

Skill	Functions	API Required	Multi-Instance
`datetime`	2	No	No
`math`	1	No	No
`web_search`	1	Yes	Yes
`wikipedia_search`	1	No	No
`weather_api`	1	Yes	No
`joke`	1	No	No
`play_background_file`	2	No	No
`swml_transfer`	1	No	Yes
`datasphere`	1	Yes	Yes
`native_vector_search`	1	No	Yes
`mcp_gateway`	Dynamic	No*	Yes
`google_maps`	2	Yes	No
`info_gatherer`	2	No	Yes
`claude_skills`	Dynamic	No	Yes
`api_ninjas_trivia`	1	Yes	Yes
`ask_claude`	1	Yes	No
`custom_skills`	Dynamic	No	No
`datasphere_serverless`	1	Yes	Yes
`spider`	1	No	Yes

\* Requires MCP Gateway service, not external API

Builtin Skills ​

Built-in Skills ​

Available Skills ​

datetime ​

math ​

web_search ​

wikipedia_search ​

weather_api ​

joke ​

play_background_file ​

swml_transfer ​

datasphere ​

native_vector_search ​

mcp_gateway ​

google_maps ​

info_gatherer ​

claude_skills ​

Skills Summary Table ​

Builtin Skills

Built-in Skills

Available Skills

datetime

math

web_search

wikipedia_search

weather_api

joke

play_background_file

swml_transfer

datasphere

native_vector_search

mcp_gateway

google_maps

info_gatherer

claude_skills

Skills Summary Table