lktieplktiep/cortex-hub/AGENTS.md

cortex-hub

AGENTS.md105 starsChanged 35 days agoMITView on GitHub

Current Phase: 6 (Polish, docs, testing, GA release) Start from what you know, not from a fixed ladder: Search once, read all ten. Measured on cortex-hub's own index (benchmarks/retrieval_bench.ts, n=15): the target file is in the top 10 for 15/15 queries but at rank 1 for only 8/15. So scan the whole result set, and never re-run a reworded version of the same query — recall@10 is already 1.000, so it returns the same set. Ask a different question or…

We split this AGENTS.md into the rules it gives an agent

2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.

≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.

Common
Distinctive
Very specific

Distinctive:
Use cortex tools as your primary workflow — they're faster, more focused, and save tokens compared to grep/find.
line 16
Very specific:
Bug protocol: search knowledge/memory first → fix → store non-obvious fixes via knowledge_store.
line 52

≈ “Common” is an estimate: at least 1 in 5 of the 36,368 AGENTS.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.

Files

AGENTS.md

Cortex Hub — Agent Guidelines

Current Phase: 6 (Polish, docs, testing, GA release)

Session Lifecycle

Start

cortex_session_start({ repo: "<repo URL>", mode: "development", agentId: "<your id>" }) — save the returned sessionId
cortex_knowledge_search + cortex_memory_search — recall what happened last session
cortex_task_pickup() — check for Conductor tasks assigned to you

During Work

Use cortex tools as your primary workflow — they're faster, more focused, and save tokens compared to grep/find.

What you need	Tool	Why it's better
Find code	`cortex_code_search`	AST-aware, returns focused results (~90% fewer tokens than grep)
Understand a symbol	`cortex_code_context`	Shows callers, callees, imports, process participation
Check blast radius	`cortex_code_impact`	Know what breaks before you edit
Pre-commit risk	`cortex_detect_changes`	Affected symbols + risk rating
Graph queries	`cortex_cypher`	Direct Cypher on the knowledge graph
Known solutions	`cortex_knowledge_search`	Search before debugging from scratch
Past decisions	`cortex_memory_search`	Recall what you or other agents learned
Save a fix	`cortex_knowledge_store`	Team-wide — so nobody debugs this twice
Save context	`cortex_memory_store`	Personal recall for future sessions
Other agents' changes	`cortex_changes`	Check before editing shared files
Tool effectiveness	`cortex_tool_stats`	Usage analytics and success rates

Start from what you know, not from a fixed ladder:

You already know	Start with
A symbol name	`cortex_code_context(name)` — exact graph lookup, plus callers/callees/imports in one call
Only the behaviour	`cortex_code_search(query, limit: 10)` — ranked hybrid search, one call
An exact literal (env var, config key, error string)	`rg` / `grep` — this is not a ranking problem
A relationship across files	`cortex_cypher`

Search once, read all ten. Measured on cortex-hub's own index (benchmarks/retrieval_bench.ts, n=15): the target file is in the top 10 for 15/15 queries but at rank 1 for only 8/15. So scan the whole result set, and never re-run a reworded version of the same query — recall@10 is already 1.000, so it returns the same set. Ask a different question or switch tool instead.

Knowledge and memory are for errors and decisions, not for locating code. Recall them once at session start, then when something breaks — not before every lookup.

cortex_code_impact before editing something exported or shared; cortex_changes before touching a file another agent may hold.

Bug protocol: search knowledge/memory first → fix → store non-obvious fixes via knowledge_store.

End

Verify: pnpm build && pnpm typecheck && pnpm lint
cortex_quality_report — report gate results
cortex_memory_store — persist session context (what was done, decisions, next steps)
cortex_session_end(sessionId, summary) — closes session + auto-saves summary as searchable memory

Project Context

Self-hosted MCP platform: code intelligence, persistent memory, shared knowledge, quality enforcement for AI agents.

Tech Stack

Monorepo: pnpm + Turborepo
MCP Gateway: Hono (Docker)
Dashboard: Hono API + Next.js 15
Backend: Qdrant, mem9, GitNexus (Docker Compose)
Infra: Cloudflare Tunnel, Watchtower

Code Conventions

camelCase vars/functions, PascalCase types/components
@cortex/* path aliases — never relative cross-package imports
Strict TypeScript — no any without comment
Conventional commits: feat:, fix:, docs:, chore:

Quality Gates

Step	Command
Build	`pnpm build` (full, never `--filter`)
Typecheck	`pnpm typecheck`
Lint	`pnpm lint`
Test (deploy only)	`pnpm test`

Endpoints

Service	URL
Dashboard	http://localhost:3000
API	http://localhost:4000
MCP	http://localhost:8318

Phase Roadmap

Phase 1: Server + Cloudflare Tunnel
Phase 2: Monorepo skeleton + shared packages
Phase 3: Docker stack (Qdrant, CLIProxy, Watchtower)
Phase 4: Hub MCP Server — apps/hub-mcp
Phase 5: Dashboard — apps/dashboard-web
[/] Phase 6: Polish, docs, testing, GA release

Key Documents

Document	Path
Code Conventions	`.cortex/code-conventions.md`
MCP Tool Reference	`docs/api/hub-mcp-reference.md`
Architecture Overview	`docs/architecture/overview.md`
Docker Stack	`infra/docker-compose.yml`

Compliance (Automated)

Tool usage is tracked and scored automatically:

Session Compliance Score — cortex_session_end grades your session (A/B/C/D) across 5 categories: Discovery, Safety, Learning, Contribution, Lifecycle
MCP Response Hints — every tool response includes context-aware hints about what to use next

These work on any MCP client — Claude Code, Antigravity, Cursor, Windsurf, Codex.

Download now (ZIP)

Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.
Of the AGENTS.md files we read, the 28,693 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.
In this repository2 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- .vscode/copilot-instructions.mdCopilot instructions

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

Reviews can't be read right now.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free