Integration guidance for Honcho, an open-source memory library that stores conversation data and builds ongoing profiles of people and agents.

It helps add Honcho to Python or TypeScript projects, define participants and conversations, send messages for processing, and query stored user context.

It helps an agent retain useful context across conversations rather than treating every session as new.

integrate — Skill for Claude Code and Cursor by plastic-labs

Install

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.

Any agent

npx skills add plastic-labs/cursor-honcho --skill integrate

Clone the repo

git clone --depth 1 https://github.com/plastic-labs/cursor-honcho

Made for: Claude Code, Cursor.

Or install honcho-dev, the plugin that ships this one along with the rest of its 3 skills.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/plastic-labs/cursor-honcho/integrate/github.svg)](https://agentmods.dev/skills/plastic-labs/cursor-honcho/integrate)

Your own site

<a href="https://agentmods.dev/skills/plastic-labs/cursor-honcho/integrate"><img src="https://agentmods.dev/badge/skills/plastic-labs/cursor-honcho/integrate/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/plastic-labs/cursor-honcho/integrate"><img src="https://agentmods.dev/badge/skills/plastic-labs/cursor-honcho/integrate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 4,214 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

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 5.1	$0.00062	$0.04214
Opus 5.5	$0.00025	$0.01686
Sonnet 5.5	$0.00012	$0.00843
Haiku 4.5	$0.00006	$0.00421

Measured 2mo ago against content hash abfa83def04b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

integrate 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 2mo ago.

The scan reads SKILL.md. This mod also ships 3 executable files (references/bot-frameworks/nanobot/client.py, references/bot-frameworks/nanobot/honcho_tool.py, references/bot-frameworks/nanobot/session.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

plugins/honcho-dev/skills/integrate/SKILL.md · 541 lines

How it starts

The opening of the file, as written. The whole thing — 541 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Honcho Integration Guide

What is Honcho

Honcho is an open source memory library for building stateful agents. It works with any model, framework, or architecture. You send Honcho the messages from your conversations, and custom reasoning models process them in the background — extracting premises, drawing conclusions, and building rich representations of each participant over time. Your agent can then query those representations on-demand ("What does this user care about?", "How technical is this person?") and get grounded, reasoned answers.

The key mental model: Peers are any participant — human or AI. Both are represented the same way. Observation settings (observe_me, observe_others) control which peers Honcho reasons about. Typically you want Honcho to model your users (observe_me=True) but not your AI assistant (observe_me=False). Sessions scope conversations between peers. Messages are the raw data you feed in — Honcho reasons about them asynchronously and stores the results as the peer's representation. No messages means no reasoning means no memory.

Your agent accesses this memory through peer.chat(query) (ask a natural language question, get a reasoned answer), session.context() (get formatted conversation history + representations), or both.

Integration Workflow

Follow these phases in order:

Phase 1: Codebase Exploration

Before asking the user anything, explore the codebase to understand:

Language & Framework: Is this Python or TypeScript? What frameworks are used (FastAPI, Express, Next.js, etc.)?
Existing AI/LLM code: Search for existing LLM integrations (OpenAI, Anthropic, LangChain, etc.)
Entity structure: Identify users, agents, bots, or other entities that interact
Session/conversation handling: How does the app currently manage conversations?
Message flow: Where are messages sent/received? What's the request/response cycle?

Use Glob and Grep to find:

**/*.py or **/*.ts files with "openai", "anthropic", "llm", "chat", "message"
User/session models or types
API routes handling chat or conversation endpoints

Read the full file on GitHub · 541 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

2mo ago First seen · 541 lines · 62 tokens per session scan A abfa83def04b

Subscribe to this mod's changes

integrate is a skill published in the GitHub repository plastic-labs/cursor-honcho (7 stars, last pushed 22d ago), licensed MIT. It adds 62 tokens to every session and 4,214 once invoked, about $0.0002 per session on Opus 5.5. 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.

Memory and context

integrate next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
integrateplastic-labs/cursor-honcho	Skill	7	22d ago	MIT	A	62	Claude Code, Cursor
knowledge-ingestopenclaw/openclaw	Skill	394k	today	MIT	A	80	Claude Code, Codex
forgetasgeirtj/system_prompts_leaks	Skill	71k	yesterday	CC0-1.0	A	0	Claude Code, Codex
mem0-oss-to-platformmem0ai/mem0	Skill	69k	5d ago	Apache-2.0	A	217	Claude Code, Codex
Cortexdanielmiessler/LifeOS	Skill	20k	6d ago	MIT	A	184	Claude Code
memoryopensquilla/opensquilla	Skill	7.1k	5d ago	Apache-2.0	A	44	Claude Code, Codex
ha-data-storesshiwenwen/hope-agent	Skill	1.9k	yesterday	MIT	A	115	Claude Code, Codex