Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/5queezer/distill/claude-mdgit clone --depth 1 https://github.com/5queezer/distillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/5queezer/distill/claude-md)<a href="https://agentmods.dev/instructions/5queezer/distill/claude-md"><img src="https://agentmods.dev/badge/instructions/5queezer/distill/claude-md.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.02393 | $0.02393 |
| Opus 5 | $0.01196 | $0.01196 |
| Sonnet 5 | $0.00479 | $0.00479 |
| Haiku 4.5 | $0.00239 | $0.00239 |
Grade A, and why
distill CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Distill — Privacy-first Team Memory MCP Server
What this is
An MCP server that gives Claude Code access to a shared team knowledge base. Raw developer input is distilled into anonymous factual knowledge by an LLM before being stored.
Core principle
By default, the local LLM is the privacy component. Raw text → Ollama (local) → distilled fact → team DB. Three independent axes: BACKEND (storage), EMBEDDING_PROVIDER, DISTILLER_PROVIDER. Setting DISTILLER_PROVIDER=gemini sends raw text to Google instead of keeping it local.
Architecture (Uncle Bob / Clean Architecture)
Dependencies point inward. Business logic has no knowledge of frameworks, databases, or transport.
src/distill_mcp/
├── domain/ # Inner ring: pure business logic, no dependencies
│ ├── models.py # Memory, DistilledMemory, SearchResult (dataclasses/Pydantic)
│ ├── ports.py # Abstract interfaces (StoragePort, EmbeddingPort, DistillerPort)
│ └── services.py # Use cases: search, get, update, list_recent, forget (depends only on ports)
│
├── adapters/ # Outer ring: implementations of ports
│ ├── storage/
│ │ ├── sqlite_store.py # StoragePort → SQLite + FTS5 + LanceDB
│ │ └── postgres_store.py # StoragePort → asyncpg + pgvector + tsvector
│ ├── embeddings/
│ │ ├── ollama_embed.py # EmbeddingPort → local Ollama
│ │ ├── vertex_embed.py # EmbeddingPort → Vertex AI
│ │ └── gemini_embed.py # EmbeddingPort → Gemini API
│ └── distiller/
│ ├── ollama_distill.py # DistillerPort → local Ollama
│ └── gemini_distill.py # DistillerPort → Gemini API
│
├── server.py # FastMCP tool definitions — thin adapter calling services
├── ingest.py # Auto-observe: receives raw hook events, queues for worker
├── worker.py # Background worker: distills and stores queued events
├── config.py # pydantic-settings, env var loading
├── dedup.py # Cosine similarity > 0.95 check
├── private_store.py # Raw text → local JSONL (never synced)
├── cli.py # seed, export commands
└── __main__.py # Entry point: wires adapters, starts FastMCP
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 169 lines · 2,393 tokens per session scan A e8fc715cf683
distill CLAUDE.md is an instructions file published in the GitHub repository 5queezer/distill (1 stars, last pushed 4mo ago), licensed MIT. It adds 2,393 tokens to every session, about $0.0120 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other instructions, from other repositories
vespertide AGENTS.md
AGENTS.md instructions for dev-five-git/vespertide, covering vespertide knowledge base, structure, where to look, data flow and conventions.
aeon CLAUDE.md
Instructions for aeonfun/aeon, covering aeon, how aeon works, strategy, voice and soul file hierarchy (read in this order).
mcp-structured-memory CLAUDE.md
Claude Code instructions for nmeierpolys/mcp-structured-memory, a project described as: Structured Memory MCP Server.
inkwell-memory CLAUDE.md
Instructions for veronchenko/inkwell-memory, covering claude.md — inkwellmemory, layout, multi-tenant mode (inkwellmultitenant=1), conventions and testing.
RNR-Enhanced-Cognee AGENTS.md
AGENTS.md instructions for vincentspereira/RNR-Enhanced-Cognee, covering rnr enhanced cognee implementation for codex, critical requirements, 1. ascii-only output (no unicode encoding), 2. dynamic categories (no hardcoded categories) and 3. standard memory mcp interface.
memory-mcp-1file AGENTS.md
Instructions for pomazanbohdan/memory-mcp-1file, covering ⛔ l0 invariants (never violate under any circumstance), detection heuristic, 🔀 phase transition routing (⛔ blocking), gate-0: phase identification & loading and 🧾 proof-of-load requirement (critical).