@stanford-oval
Creator · stanford-oval
Last updated · Sep 1, 2026
WikiChat
STRONG · 78Community indexed
WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus.
Creator · stanford-oval
Last updated · Sep 1, 2026
WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus.
Creator · stanford-oval
Last updated · Sep 1, 2026
WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus.
Creator · stanford-oval
Last updated · Sep 1, 2026
WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus.
Creator · stanford-oval
Last updated · Sep 1, 2026
WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus.
Review then install
Install targets
Codex install prompt
Install the "WikiChat" agent skill from https://github.com/stanford-oval/WikiChat. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"stanford-oval-wikichat","task":"Install WikiChat","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add stanford-oval/WikiChat
Maintenance
stable
7mo since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
1.6K
85/100 Quality · 86/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Financial research output is not financial advice; require human review before any live investment decision.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
1.6K GitHub stars
Repo activity
1.6K stars, 143 forks
Maintenance
7mo since push
License
Apache-2.0
Install
npx skills add stanford-oval/WikiChat
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add stanford-oval/WikiChatDo not use when
Alternative
75.1K Stars
npx skills add Egonex-AI/Understand-Anything
Alternative
43.6K Stars
npx skills add logseq/logseq
Alternative
69.9K Stars
npx skills add 666ghj/MiroFish
Alternative
112.2K Stars
npx skills add microsoft/generative-ai-for-beginners
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20WikiChat%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20WikiChat%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/stanford-oval-wikichat/install
Agent should check
Copy prompt
Task: Use WikiChat in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20WikiChat%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/stanford-oval-wikichat/install
Install command: npx skills add stanford-oval/WikiChat
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/stanford-oval-wikichat/install
LLM text format
/api/skills/stanford-oval-wikichat/install?format=text
Find alternatives
/api/skills/search?q=WikiChat&limit=3
Agent prompt
Use WikiChat for this task. Review https://www.openagentskill.com/api/skills/stanford-oval-wikichat/install, then install with: npx skills add stanford-oval/WikiChatRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/stanford-oval-wikichat
LLM text
/api/registry/manifest/stanford-oval-wikichat?format=text
Install alias
/api/registry/install/stanford-oval-wikichat
Recommend
/api/registry/recommend?task=Use%20WikiChat%20in%20an%20agent%20workflow&limit=3
Agent fit
RAG and knowledge
Use-case tags
Platforms
Python, RAG, Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
RAG and knowledge
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
PASS1.6K GitHub stars
Stars/forks activity
INFO1.6K stars, 143 forks; issue activity unavailable in current metadata
Recent maintenance
INFO7mo since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Manage repositories
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Workflow fit
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Alternative shortlist
Similar skills that may fit this task.
Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
A privacy-first, open-source platform for knowledge management and collaboration. Download link: http://github.com/logseq/logseq/releases. roadmap: https://logseq.io/p/NX4mc_ggEV
A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎，预测万物
21 Lessons, Get Started Building with Generative AI
WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus.
Imported by the skill-only GitHub discovery pipeline because it matches agent skill, automation, domain workflow, RAG, document-processing, data, finance, security, or developer-tool signals. Protocol-server projects are excluded from automated imports.
Frameworks & tools
Decision snapshot
1,600 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for WikiChat, ready for a manual X post.
WikiChat: WikiChat is an improved RAG. It stops the hallucination of large language models by retrievin... 1.6K stars https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=x
Listing + install path for WikiChat: https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=x Install: npx skills add stanford-oval/WikiChat
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Community indexed listing is attributed to stanford-oval but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/stanford-oval-wikichat/audit)
[](https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)stanford-oval✓
@stanford-oval
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Review then install
Understand Anything
Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
75.1K StarsLogseq
A privacy-first, open-source platform for knowledge management and collaboration. Download link: http://github.com/logseq/logseq/releases. roadmap: https://logseq.io/p/NX4mc_ggEV
43.6K StarsMiroFish
A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎，预测万物
69.9K StarsGenerative AI For Beginners
21 Lessons, Get Started Building with Generative AI
112.2K StarsReview then install
Install targets
Codex install prompt
Install the "WikiChat" agent skill from https://github.com/stanford-oval/WikiChat. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"stanford-oval-wikichat","task":"Install WikiChat","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add stanford-oval/WikiChat
Maintenance
stable
7mo since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
1.6K
85/100 Quality · 86/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Financial research output is not financial advice; require human review before any live investment decision.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
1.6K GitHub stars
Repo activity
1.6K stars, 143 forks
Maintenance
7mo since push
License
Apache-2.0
Install
npx skills add stanford-oval/WikiChat
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add stanford-oval/WikiChatDo not use when
Alternative
75.1K Stars
npx skills add Egonex-AI/Understand-Anything
Alternative
43.6K Stars
npx skills add logseq/logseq
Alternative
69.9K Stars
npx skills add 666ghj/MiroFish
Alternative
112.2K Stars
npx skills add microsoft/generative-ai-for-beginners
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20WikiChat%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20WikiChat%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/stanford-oval-wikichat/install
Agent should check
Copy prompt
Task: Use WikiChat in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20WikiChat%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/stanford-oval-wikichat/install
Install command: npx skills add stanford-oval/WikiChat
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/stanford-oval-wikichat/install
LLM text format
/api/skills/stanford-oval-wikichat/install?format=text
Find alternatives
/api/skills/search?q=WikiChat&limit=3
Agent prompt
Use WikiChat for this task. Review https://www.openagentskill.com/api/skills/stanford-oval-wikichat/install, then install with: npx skills add stanford-oval/WikiChatRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/stanford-oval-wikichat
LLM text
/api/registry/manifest/stanford-oval-wikichat?format=text
Install alias
/api/registry/install/stanford-oval-wikichat
Recommend
/api/registry/recommend?task=Use%20WikiChat%20in%20an%20agent%20workflow&limit=3
Agent fit
RAG and knowledge
Use-case tags
Platforms
Python, RAG, Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
RAG and knowledge
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
PASS1.6K GitHub stars
Stars/forks activity
INFO1.6K stars, 143 forks; issue activity unavailable in current metadata
Recent maintenance
INFO7mo since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Manage repositories
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Workflow fit
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Alternative shortlist
Similar skills that may fit this task.
Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
A privacy-first, open-source platform for knowledge management and collaboration. Download link: http://github.com/logseq/logseq/releases. roadmap: https://logseq.io/p/NX4mc_ggEV
A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎，预测万物
21 Lessons, Get Started Building with Generative AI
WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus.
Imported by the skill-only GitHub discovery pipeline because it matches agent skill, automation, domain workflow, RAG, document-processing, data, finance, security, or developer-tool signals. Protocol-server projects are excluded from automated imports.
Frameworks & tools
Decision snapshot
1,600 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for WikiChat, ready for a manual X post.
WikiChat: WikiChat is an improved RAG. It stops the hallucination of large language models by retrievin... 1.6K stars https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=x
Listing + install path for WikiChat: https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=x Install: npx skills add stanford-oval/WikiChat
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Community indexed listing is attributed to stanford-oval but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/stanford-oval-wikichat/audit)
[](https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)stanford-oval✓
@stanford-oval
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Review then install
Understand Anything
Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
75.1K StarsLogseq
A privacy-first, open-source platform for knowledge management and collaboration. Download link: http://github.com/logseq/logseq/releases. roadmap: https://logseq.io/p/NX4mc_ggEV
43.6K StarsMiroFish
A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎，预测万物
69.9K StarsGenerative AI For Beginners
21 Lessons, Get Started Building with Generative AI
112.2K StarsReview then install
Install targets
Codex install prompt
Install the "WikiChat" agent skill from https://github.com/stanford-oval/WikiChat. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"stanford-oval-wikichat","task":"Install WikiChat","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add stanford-oval/WikiChat
Maintenance
stable
7mo since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
1.6K
85/100 Quality · 86/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Financial research output is not financial advice; require human review before any live investment decision.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
1.6K GitHub stars
Repo activity
1.6K stars, 143 forks
Maintenance
7mo since push
License
Apache-2.0
Install
npx skills add stanford-oval/WikiChat
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add stanford-oval/WikiChatDo not use when
Alternative
75.1K Stars
npx skills add Egonex-AI/Understand-Anything
Alternative
43.6K Stars
npx skills add logseq/logseq
Alternative
69.9K Stars
npx skills add 666ghj/MiroFish
Alternative
112.2K Stars
npx skills add microsoft/generative-ai-for-beginners
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20WikiChat%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20WikiChat%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/stanford-oval-wikichat/install
Agent should check
Copy prompt
Task: Use WikiChat in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20WikiChat%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/stanford-oval-wikichat/install
Install command: npx skills add stanford-oval/WikiChat
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/stanford-oval-wikichat/install
LLM text format
/api/skills/stanford-oval-wikichat/install?format=text
Find alternatives
/api/skills/search?q=WikiChat&limit=3
Agent prompt
Use WikiChat for this task. Review https://www.openagentskill.com/api/skills/stanford-oval-wikichat/install, then install with: npx skills add stanford-oval/WikiChatRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/stanford-oval-wikichat
LLM text
/api/registry/manifest/stanford-oval-wikichat?format=text
Install alias
/api/registry/install/stanford-oval-wikichat
Recommend
/api/registry/recommend?task=Use%20WikiChat%20in%20an%20agent%20workflow&limit=3
Agent fit
RAG and knowledge
Use-case tags
Platforms
Python, RAG, Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
RAG and knowledge
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
PASS1.6K GitHub stars
Stars/forks activity
INFO1.6K stars, 143 forks; issue activity unavailable in current metadata
Recent maintenance
INFO7mo since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Manage repositories
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Workflow fit
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Alternative shortlist
Similar skills that may fit this task.
Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
A privacy-first, open-source platform for knowledge management and collaboration. Download link: http://github.com/logseq/logseq/releases. roadmap: https://logseq.io/p/NX4mc_ggEV
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21 Lessons, Get Started Building with Generative AI
WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus.
Imported by the skill-only GitHub discovery pipeline because it matches agent skill, automation, domain workflow, RAG, document-processing, data, finance, security, or developer-tool signals. Protocol-server projects are excluded from automated imports.
Frameworks & tools
Decision snapshot
1,600 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for WikiChat, ready for a manual X post.
WikiChat: WikiChat is an improved RAG. It stops the hallucination of large language models by retrievin... 1.6K stars https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=x
Listing + install path for WikiChat: https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=x Install: npx skills add stanford-oval/WikiChat
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Community indexed listing is attributed to stanford-oval but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/stanford-oval-wikichat/audit)
[](https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)stanford-oval✓
@stanford-oval
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Review then install
Understand Anything
Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
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112.2K StarsReview then install
Install targets
Codex install prompt
Install the "WikiChat" agent skill from https://github.com/stanford-oval/WikiChat. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"stanford-oval-wikichat","task":"Install WikiChat","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add stanford-oval/WikiChat
Maintenance
stable
7mo since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
1.6K
85/100 Quality · 86/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Financial research output is not financial advice; require human review before any live investment decision.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
1.6K GitHub stars
Repo activity
1.6K stars, 143 forks
Maintenance
7mo since push
License
Apache-2.0
Install
npx skills add stanford-oval/WikiChat
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add stanford-oval/WikiChatDo not use when
Alternative
75.1K Stars
npx skills add Egonex-AI/Understand-Anything
Alternative
43.6K Stars
npx skills add logseq/logseq
Alternative
69.9K Stars
npx skills add 666ghj/MiroFish
Alternative
112.2K Stars
npx skills add microsoft/generative-ai-for-beginners
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20WikiChat%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20WikiChat%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/stanford-oval-wikichat/install
Agent should check
Copy prompt
Task: Use WikiChat in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20WikiChat%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/stanford-oval-wikichat/install
Install command: npx skills add stanford-oval/WikiChat
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/stanford-oval-wikichat/install
LLM text format
/api/skills/stanford-oval-wikichat/install?format=text
Find alternatives
/api/skills/search?q=WikiChat&limit=3
Agent prompt
Use WikiChat for this task. Review https://www.openagentskill.com/api/skills/stanford-oval-wikichat/install, then install with: npx skills add stanford-oval/WikiChatRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/stanford-oval-wikichat
LLM text
/api/registry/manifest/stanford-oval-wikichat?format=text
Install alias
/api/registry/install/stanford-oval-wikichat
Recommend
/api/registry/recommend?task=Use%20WikiChat%20in%20an%20agent%20workflow&limit=3
Agent fit
RAG and knowledge
Use-case tags
Platforms
Python, RAG, Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
RAG and knowledge
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
PASS1.6K GitHub stars
Stars/forks activity
INFO1.6K stars, 143 forks; issue activity unavailable in current metadata
Recent maintenance
INFO7mo since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Manage repositories
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Workflow fit
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Alternative shortlist
Similar skills that may fit this task.
Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
A privacy-first, open-source platform for knowledge management and collaboration. Download link: http://github.com/logseq/logseq/releases. roadmap: https://logseq.io/p/NX4mc_ggEV
A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎，预测万物
21 Lessons, Get Started Building with Generative AI
WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus.
Imported by the skill-only GitHub discovery pipeline because it matches agent skill, automation, domain workflow, RAG, document-processing, data, finance, security, or developer-tool signals. Protocol-server projects are excluded from automated imports.
Frameworks & tools
Decision snapshot
1,600 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for WikiChat, ready for a manual X post.
WikiChat: WikiChat is an improved RAG. It stops the hallucination of large language models by retrievin... 1.6K stars https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=x
Listing + install path for WikiChat: https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=x Install: npx skills add stanford-oval/WikiChat
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Community indexed listing is attributed to stanford-oval but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/stanford-oval-wikichat/audit)
[](https://www.openagentskill.com/skills/stanford-oval-wikichat?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)stanford-oval✓
@stanford-oval
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Review then install
Understand Anything
Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
75.1K StarsLogseq
A privacy-first, open-source platform for knowledge management and collaboration. Download link: http://github.com/logseq/logseq/releases. roadmap: https://logseq.io/p/NX4mc_ggEV
43.6K StarsMiroFish
A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎，预测万物
69.9K StarsGenerative AI For Beginners
21 Lessons, Get Started Building with Generative AI
112.2K Starsstandard package or runtime install path
Permission surface
filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
standard package or runtime install path
Permission surface
filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
standard package or runtime install path
Permission surface
filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
standard package or runtime install path
Permission surface
filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness