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Agentic Tools

Tools and infrastructure for reliable AI-assisted ontology, schema, and knowledge-base curation workflows. These components form the building blocks of an agent harness — the control plane that makes AI-assisted curation reproducible and reviewable.

For a guide on how these tools fit together, see Build your agentic harness.

Validators

linkml-reference-validator

Validates whether supporting text in structured records is actually present in cited references, helping enforce evidence-backed curation.

  • When to use: After an agent generates structured annotations with literature citations — catch hallucinated or misattributed evidence before review.
  • Install: pip install linkml-reference-validator
  • GitHub | Docs | PyPI

linkml-term-validator

Checks LinkML schemas and datasets for correct use of external ontologies and controlled terms, improving consistency for agent-generated outputs.

  • When to use: When agents generate data that references ontology terms — ensures terms exist and are used correctly.
  • Install: pip install linkml-term-validator
  • GitHub | Docs | PyPI

Provenance

ai-blame

Extracts provenance and audit trails from agent execution traces, enabling line-level attribution and post-hoc review for AI-assisted edits.

  • When to use: After AI-assisted editing sessions — understand which changes an agent made, when, and in what context.
  • Install: pip install ai-blame
  • GitHub | Docs | PyPI

Agent Skills

curation-skills

Reusable skill packs for ontology and biocuration tasks, designed to make agent behavior more consistent, transparent, and domain-aware.

  • When to use: When configuring agents for curation work — provide structured, domain-specific instructions instead of ad-hoc prompts.
  • GitHub | Skills Article

MCP Servers

noctua-mcp

MCP server wrapping GO-CAM editing capabilities, enabling agentic interaction with Noctua/Barista workflows through a standardized interface.

  • When to use: When agents need to create or edit GO-CAM models — provides structured access to the Noctua API.
  • Install: pip install noctua-mcp
  • GitHub | PyPI | noctua-py

oak-mcp

MCP server for ontology operations via the Ontology Access Kit (OAK), enabling agents to search, query, and traverse ontologies programmatically.

  • When to use: When agents need to look up ontology terms, traverse hierarchies, or perform ontology operations during curation tasks.
  • GitHub

System Instructions

CLAUDE.md / .goosehints

Configuration files checked into the root of your repository that provide system-level instructions to AI agents. These serve as prompt preset management — different repositories can have different instructions tailored to their domain and workflows.

Further Reading