Analysis Skill

The analysis skill provides computational analysis via code execution. It writes and runs Python code in a sandboxed interpreter to answer questions that require computation, aggregation, or data traversal.

`create_skill(db_path?, config?)`

from haiku.rag.skills.analysis import create_skill

skill = create_skill(db_path=db_path, config=config)

Parameter	Default	Description
`db_path`	`None`	Path to LanceDB database. Falls back to `HAIKU_RAG_DB` env var, then config default.
`config`	`None`	`AppConfig` instance. If None, uses `get_config()`.

Tools

Tool	Purpose
`search(query, limit?)`	Hybrid search (vector + full-text) with context expansion
`list_documents()`	List all documents in the knowledge base
`execute_code(code)`	Execute Python code in a sandboxed interpreter with VFS access
`cite(chunk_ids)`	Register chunk IDs as citations for the current answer

State

The skill manages an AnalysisState under the "analysis" namespace:

class AnalysisState(BaseModel):
    document_filter: str | None = None
    executions: list[CodeExecutionEntry] = []
    citation_index: dict[str, Citation] = {}
    citations: list[list[str]] = []
    searches: dict[str, list[SearchResult]] = {}

document_filter — SQL WHERE clause applied to search and list_documents calls.
executions — Each execute_code call appends a CodeExecutionEntry with code, stdout, stderr, and success status.
citation_index / citations — Same per-turn citation tracking as the RAG skill.
searches — Search results from both the search tool and sandbox-internal searches.

Usage with RAG Skill

Combine both skills to give the agent full RAG + analysis capabilities:

from haiku.rag.skills.rag import create_skill as create_rag_skill
from haiku.rag.skills.analysis import create_skill as create_analysis_skill
from haiku.skills.agent import SkillToolset
from haiku.skills.prompts import build_system_prompt
from pydantic_ai import Agent

rag = create_rag_skill(db_path=db_path)
analysis = create_analysis_skill(db_path=db_path)
toolset = SkillToolset(skills=[rag, analysis])

agent = Agent(
    "openai:gpt-4o",
    instructions=build_system_prompt(toolset.skill_catalog),
    toolsets=[toolset],
)

See the Analysis Agent documentation for details on how the underlying sandbox works.