knowledge-base
Skill86 starsChanged 4 months agoMITView on GitHub
Ingest URLs, documents, and transcripts into a searchable knowledge base. Query past research and curated documentation using full-text search. Trigger words: ingest, knowledge base, look up, search knowledge, what do we know about, research, index this, add to knowledge base.
- Sends data out
32 other projects use a version of this.
Adopted by
Most recently taken up by
- shetengteng/skillix-hubtheir own version, first seen Nov 8, 2026
- ITch8/customs-data-skillstheir own version, first seen Nov 8, 2026
- theopenco/llmgatewaytheir own version, first seen Nov 6, 2026
- digitalgym/aipathway-standardstheir own version, first seen Nov 4, 2026
- shinpr/rashomontheir own version, first seen Nov 1, 2026
- jjmrocha/coding-skillstheir own version, first seen Oct 13, 2026
Used with
Projects with it also use playwright, code-reviewer and 4 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
OpenAISkillplaywright
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GoogleSkillcode-reviewer
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engtySkillcodex
Use when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing
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ElasticSkillcreate-skill
Interactively create a new Claude Code skill and add it to the elastic-docs-skills catalog. Use when the user wants to generate a new skill, scaffold a slash command, or build automation for docs tasks.
Also in 3 projects that use this
CloudflareSkillsecurity-audit
Security guidance and vulnerability review for codebases, APIs, services, CLI tools, libraries, and daemons. Use for security questions, focused reviews, vulnerability research, security audits, or pen tests. Run the complete workflow only for explicit codebase audit or pen-test requests, full/comprehensive/end-to-end reviews, or requested report artifacts.
Also in 3 projects that use this
Microsoft AzureSkillverify
End-to-end app testing pipeline for browser-based web apps on cloud browsers via Azure Playwright Workspaces: verify the live app, author tests for working flows, heal failing tests, then re-run with video and produce one consolidated report. Three phases (app verification, test authoring, test healing) plus a scoped final sanity run; each phase emits a sub-report. Use when asked to "verify my app", "make sure my app works and has good test coverage", "do a full QA pass", "add tests where I'm missing coverage", "fix failing tests and add new ones", "smoke test before deploy", "QA my deployment", or any combined verify-and-test ask. Requires Azure CLI (`az login`) and a Playwright Workspace resource ID — bootstraps configs on first invocation. Browser-based web apps with Playwright only — not for unit/API tests, native mobile/desktop, load/perf, or full accessibility audits.
Also in 3 projects that use this
Other versions32 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 32
- rommapp/romm★ 14ksame name
- wonderwhy-er/DesktopCommanderMCP★ 10ksame name
- Lilac-Labs/gini-agent★ 1.9ksame name
- Open-Curiosity/gini-agent★ 1.9ksame name
- theopenco/llmgateway★ 1.7ksame name
- icey1287/SuperMew★ 884same name
- Karanjot786/TermUI★ 238same name
- svy04/ballast★ 73same name
- zeroclaw-labs/zeroclaw-skills★ 65same name
- shinpr/rashomon★ 20same name
22 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository23 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- autonomousSkill
- buildSkill
- instar-projectSkill
- secret-setupSkill
- setup-wizardSkill
- test-as-selfSkill
- agent-identitySkill
- agent-memorySkill
- agent-passportSkill
- agent-readinessSkill
- command-guardSkill
- credential-leak-detectorSkill
- instar-devSkill
- instar-feedbackSkill
- instar-identitySkill
- instar-schedulerSkill
- instar-sessionSkill
- instar-telegramSkill
- iterative-converging-auditSkill
- smart-web-fetchSkill
- spec-convergeSkill
- systematic-debuggingSkill
The file
We split this skill into the rules it gives an agent
2 rules. 0 are common, 2 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 24 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 65
When the agent wants to ingest content during a session:
- Distinctive: line 69
Call the ingest API or write the file manually:
“Common” is measured: kept by at least 6 in 10 of the 24 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
knowledge-base -- Searchable Knowledge Base for Instar Agents
Build a searchable knowledge base from external sources -- URLs, documents, transcripts, PDFs. Uses the existing MemoryIndex (FTS5) for search, so no new dependencies.
How It Works
The knowledge base is a set of markdown files in .instar/knowledge/ that MemoryIndex indexes alongside your other memory files. Each file has YAML frontmatter for metadata and is tracked in a catalog for browsing.
.instar/knowledge/
catalog.json # Registry of all ingested sources
articles/ # Ingested web articles
transcripts/ # Video/audio transcripts
docs/ # Curated reference documentationIngesting Content
Via CLI
# Ingest text content directly
instar knowledge ingest "Article content here..." --title "My Article" --tags "AI,agents"
# Ingest from a URL (fetch first, then ingest)
# Step 1: Fetch the content
python3 .claude/scripts/smart-fetch.py "https://example.com/article" --auto > /tmp/fetched.md
# Step 2: Ingest it
instar knowledge ingest "$(cat /tmp/fetched.md)" --title "Article Title" --url "https://example.com/article" --tags "topic1,topic2"Via API
curl -X POST http://localhost:${INSTAR_PORT:-4040}/knowledge/ingest \
-H "Content-Type: application/json" \
-d '{
"content": "The article content...",
"title": "Article Title",
"url": "https://example.com/article",
"type": "article",
"tags": ["AI", "infrastructure"],
"summary": "Brief description"
}'Via Agent Workflow
When the agent wants to ingest content during a session:
- Fetch the content (WebFetch, smart-fetch, transcript tools, or Read for local files)
- Clean it (strip navigation, ads, boilerplate)
- Call the ingest API or write the file manually:
# Write the markdown file with frontmatter
cat > .instar/knowledge/articles/2026-02-25-my-article.md << 'EOF'
---
title: "My Article"
source: "https://example.com/article"
ingested: "2026-02-25"
tags: ["AI", "infrastructure"]
---
# My Article
[Cleaned article content here]
EOF
# Sync the index to pick up the new file
instar memory syncSearching Knowledge
CLI
# Search within knowledge base only
instar knowledge search "notification batching"
# Search all memory (including knowledge)
instar memory search "notification batching"API
# Knowledge-scoped search
curl "http://localhost:${INSTAR_PORT:-4040}/memory/search?q=notification+batching&source=knowledge/&limit=5"
# Browse the catalog
curl "http://localhost:${INSTAR_PORT:-4040}/knowledge/catalog"
curl "http://localhost:${INSTAR_PORT:-4040}/knowledge/catalog?tag=AI"Managing Sources
List all sources
instar knowledge list
instar knowledge list --tag AIRemove a source
# Find the source ID from the list
instar knowledge list
# Remove it
instar knowledge remove kb_20260225123456_abc123
# Re-sync the index
instar memory syncVia API
# Remove
curl -X DELETE "http://localhost:${INSTAR_PORT:-4040}/knowledge/kb_20260225123456_abc123"MemoryIndex Configuration
To enable knowledge base indexing, add these sources to your .instar/config.json memory section:
{
"memory": {
"enabled": true,
"sources": [
{ "path": "AGENT.md", "type": "markdown", "evergreen": true },
{ "path": "USER.md", "type": "markdown", "evergreen": true },
{ "path": "knowledge/articles/", "type": "markdown", "evergreen": false },
{ "path": "knowledge/transcripts/", "type": "markdown", "evergreen": false },
{ "path": "knowledge/docs/", "type": "markdown", "evergreen": true }
]
}
}Source behavior:
articles/andtranscripts/useevergreen: false-- recent content ranks higher (30-day temporal decay)docs/usesevergreen: true-- reference documentation doesn't decay
Content Types
| Type | Directory | Temporal Decay | Best For |
article | articles/ | Yes (30-day) | Web articles, blog posts, news |
transcript | transcripts/ | Yes (30-day) | YouTube videos, podcasts, meetings |
doc | docs/ | No (evergreen) | API docs, manuals, reference material |
Tips
- Always sync after ingesting:
instar memory syncupdates the FTS5 index - Use tags consistently: Tags enable filtered browsing via
instar knowledge list --tag X - Include source URLs: Helps trace back to original content
- Clean before ingesting: Strip navigation, ads, cookie banners for better search results
- Use smart-fetch for URLs:
python3 .claude/scripts/smart-fetch.py URL --autogets clean markdown
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
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