Add agent harness documentation and agentic tools reference#70
Add agent harness documentation and agentic tools reference#70
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…ll.dev The aidocs site was behind on covering the agentic infrastructure ecosystem shown on mungall.dev. This update introduces the "agent harness" concept — the control plane around AI agents that handles validation, provenance, tool access, and human oversight — and documents the concrete tools that compose it (linkml validators, ai-blame, curation-skills, MCP servers). New pages: - how-tos/build-agentic-harness.md: practical guide to assembling a harness - reference/agentic-tools.md: reference for all agentic infrastructure tools Updated pages: - glossary.md: new terms (Agent Harness, ai-blame, Curation Skill, OAK, etc.) - faq.md: new Q&As on harness, validation, provenance, MCP servers - examples.md: added agentic infrastructure repos and ICBO tutorial - how-tos/integrate-ai-into-your-kb.md: validation, provenance, MCP tips - tutorials/ontology-editing-with-ai.md: links to 2025-2026 training materials - reference/client-apps.md: filled stub with comparison table - mkdocs.yml: added new pages to navigation https://claude.ai/code/session_01M6GBwgQiNEwBMCaigvtEvH
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Claude finished @cmungall's task —— View job PR Review: Add agent harness documentation and agentic tools referenceI've completed a comprehensive review of this documentation PR. The additions significantly enhance the project's value by providing comprehensive guidance on agent harness infrastructure. Review Tasks:
Overall Assessment: ExcellentThis PR significantly elevates the documentation quality and provides substantial practical value to the target audience. The concept of an "agent harness" as infrastructure rather than the agent itself is well-articulated and fills a crucial gap in AI curation guidance. StrengthsContent Quality:
Documentation Structure:
Technical Accuracy:
Areas for ImprovementMinor Issues:
Documentation Standards: The content excellently follows the repository's documentation standards:
Code Quality AssessmentNo security concerns identified - this is pure documentation with no executable code. Performance considerations: Documentation-only changes have no runtime performance impact. The MkDocs build should handle the additional content without issues. Test coverage: While this is documentation, the practical value can be validated by:
Best Practices AdherenceExcellent adherence to repository conventions:
Recommendation: Approve and MergeThis PR delivers significant value to the AI4Curators community with high-quality, practical documentation. The minor issues identified are suggestions for enhancement rather than blockers. The content is ready for production and will substantially help users understand and implement agent harnesses for reliable AI-assisted curation. |
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Pull request overview
Adds new documentation describing “agent harnesses” (control-plane infrastructure around AI agents) and a reference catalog of agentic tools used in AI-assisted curation workflows, plus related navigation and supporting docs updates.
Changes:
- Added a new how-to guide for assembling an agentic harness and a new “agentic tools” reference page.
- Expanded glossary/FAQ/examples/tutorials to include harness concepts, tool references, and training materials.
- Updated MkDocs navigation and upgraded the “Client apps” page into a usable reference.
Reviewed changes
Copilot reviewed 9 out of 9 changed files in this pull request and generated 1 comment.
Show a summary per file
| File | Description |
|---|---|
| mkdocs.yml | Adds the new how-to and reference pages to site navigation. |
| docs/how-tos/build-agentic-harness.md | New guide describing harness components and how they compose. |
| docs/reference/agentic-tools.md | New reference page cataloging validators, provenance tools, skills, and MCP servers. |
| docs/reference/client-apps.md | Replaces stub with a client comparison table and selection guidance. |
| docs/how-tos/integrate-ai-into-your-kb.md | Adds tips on validation, provenance, MCP servers, and harness framing. |
| docs/glossary.md | Adds new glossary entries for harness-related concepts and tools. |
| docs/faq.md | Adds an “Agent Harness and Infrastructure” FAQ section. |
| docs/examples.md | Adds “Agentic Infrastructure” examples (ai-blame, skills, MCP, tutorial). |
| docs/tutorials/ontology-editing-with-ai.md | Adds additional training materials and cross-links to harness guide. |
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| The infrastructure and control plane that wraps around an [AI agent](#ai-agent) to manage its execution. An agent harness handles context management, [tool](#tool) orchestration, validation, provenance, error recovery, and human-in-the-loop controls. It does not replace the agent — it governs how the agent operates. Think of it as the difference between writing a container and running Kubernetes. | ||
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| In a curation context, a harness typically includes: system instructions (e.g. [CLAUDE.md](#claude-code)), validators (e.g. [linkml-term-validator](#linkml-term-validator), [linkml-reference-validator](#linkml-reference-validator)), provenance tools (e.g. [ai-blame](#ai-blame)), [MCP](#model-context-protocol-mcp) servers for domain-specific tool access, and [GitHub Actions](#github-actions) for lifecycle automation. |
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The link text "CLAUDE.md" currently points to the glossary anchor for "Claude Code" (#claude-code), which is misleading for readers and makes it harder to find what CLAUDE.md is. Consider either changing the link text to "Claude Code" (if you meant the client) or linking CLAUDE.md to the relevant how-to (e.g., instruct-github-agent) or describing it as inline code without a link.
| In a curation context, a harness typically includes: system instructions (e.g. [CLAUDE.md](#claude-code)), validators (e.g. [linkml-term-validator](#linkml-term-validator), [linkml-reference-validator](#linkml-reference-validator)), provenance tools (e.g. [ai-blame](#ai-blame)), [MCP](#model-context-protocol-mcp) servers for domain-specific tool access, and [GitHub Actions](#github-actions) for lifecycle automation. | |
| In a curation context, a harness typically includes: system instructions (e.g. `CLAUDE.md`), validators (e.g. [linkml-term-validator](#linkml-term-validator), [linkml-reference-validator](#linkml-reference-validator)), provenance tools (e.g. [ai-blame](#ai-blame)), [MCP](#model-context-protocol-mcp) servers for domain-specific tool access, and [GitHub Actions](#github-actions) for lifecycle automation. |
Summary
This PR adds comprehensive documentation for building and understanding agent harnesses — the infrastructure that wraps AI agents to make them reliable, auditable, and production-ready for curation workflows. It includes a new how-to guide, reference documentation, glossary updates, and FAQ entries.
Key Changes
New how-to guide:
docs/how-tos/build-agentic-harness.md— explains what an agent harness is, why curators need one, and how to assemble one from existing tools (system instructions, MCP servers, validators, provenance tracking, GitHub Actions, and human-in-the-loop controls)New reference page:
docs/reference/agentic-tools.md— detailed documentation of available tools including validators (linkml-term-validator, linkml-reference-validator), provenance tools (ai-blame), agent skills (curation-skills), and MCP servers (noctua-mcp, oak-mcp)Glossary expansions: Added entries for:
FAQ additions: New section on "Agent Harness and Infrastructure" covering what a harness is, validation tools, provenance tracking, and available MCP servers
Enhanced how-tos: Added Tips 4-7 to
integrate-ai-into-your-kb.mdcovering validation, provenance tracking, MCP servers, and thinking in terms of harnessesUpdated examples page: Added "Agentic Infrastructure" section with examples of ai-blame, curation-skills, noctua-mcp, and ICBO 2025 AI tutorial
Improved client apps reference: Converted
docs/reference/client-apps.mdfrom stub to full reference with comparison table and guidance on choosing clientsTutorial updates: Added "Additional training materials" section to
ontology-editing-with-ai.mdwith links to workshops and recordingsNavigation updates: Added new how-to guide to mkdocs.yml navigation structure
Notable Details
The documentation emphasizes that an agent harness is not the agent itself, but the control plane around it — the infrastructure that ensures reliability, consistency, and auditability. The guide provides a concrete composition diagram showing how system instructions, tools, validators, provenance tracking, lifecycle automation, and human oversight work together.
https://claude.ai/code/session_01M6GBwgQiNEwBMCaigvtEvH