Borrowing it
Nothing to install: this file belongs to zhmxiaowo/opencode-simple. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zhmxiaowo/opencode-simple/main/.opencode/commands/instinct-import.mdgit clone --depth 1 https://github.com/zhmxiaowo/opencode-simpleWrote 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/commands/zhmxiaowo/opencode-simple/instinct-import)<a href="https://agentmods.dev/commands/zhmxiaowo/opencode-simple/instinct-import"><img src="https://agentmods.dev/badge/commands/zhmxiaowo/opencode-simple/instinct-import/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.
<a href="https://agentmods.dev/commands/zhmxiaowo/opencode-simple/instinct-import"><img src="https://agentmods.dev/badge/commands/zhmxiaowo/opencode-simple/instinct-import.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00011 | $0.00722 |
| Opus 5.5 | $0.00004 | $0.00289 |
| Sonnet 5.5 | $0.00002 | $0.00144 |
| Haiku 4.5 | $0.00001 | $0.00072 |
Grade A, and why
instinct-import scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
91% identical to instinct-import — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instinct Import Command
Implementation
Run the instinct CLI using the plugin root path:
python3 "${CLAUDE_PLUGIN_ROOT}/skills/continuous-learning-v2/scripts/instinct-cli.py" import <file-or-url> [--dry-run] [--force] [--min-confidence 0.7] [--scope project|global]
Or if CLAUDE_PLUGIN_ROOT is not set (manual installation):
python3 ~/.claude/skills/continuous-learning-v2/scripts/instinct-cli.py import <file-or-url>
Import instincts from local file paths or HTTP(S) URLs.
Usage
/instinct-import team-instincts.yaml
/instinct-import https://github.com/org/repo/instincts.yaml
/instinct-import team-instincts.yaml --dry-run
/instinct-import team-instincts.yaml --scope global --force
What to Do
- Fetch the instinct file (local path or URL)
- Parse and validate the format
- Check for duplicates with existing instincts
- Merge or add new instincts
- Save to inherited instincts directory:
- Project scope:
~/.claude/homunculus/projects/<project-id>/instincts/inherited/ - Global scope:
~/.claude/homunculus/instincts/inherited/
- Project scope:
Import Process
📥 Importing instincts from: team-instincts.yaml
================================================
Found 12 instincts to import.
Analyzing conflicts...
## New Instincts (8)
These will be added:
✓ use-zod-validation (confidence: 0.7)
✓ prefer-named-exports (confidence: 0.65)
✓ test-async-functions (confidence: 0.8)
...
## Duplicate Instincts (3)
Already have similar instincts:
⚠️ prefer-functional-style
Local: 0.8 confidence, 12 observations
Import: 0.7 confidence
→ Keep local (higher confidence)
⚠️ test-first-workflow
Local: 0.75 confidence
Import: 0.9 confidence
→ Update to import (higher confidence)
Import 8 new, update 1?
Merge Behavior
When importing an instinct with an existing ID:
- Higher-confidence import becomes an update candidate
- Equal/lower-confidence import is skipped
- User confirms unless
--forceis used
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.
- 1mo ago First seen · 113 lines · 11 tokens per session scan A 3f51688f3370
instinct-import is a command published in the GitHub repository zhmxiaowo/opencode-simple (2 stars, last pushed 7mo ago), licensed MIT. It adds 11 tokens to every session and 722 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to instinct-import, differing in 12 lines, and is treated as a copy.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
memory-store
Store an insight, decision, or pattern to memory.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
lians-recall
Recall current (non-stale) facts from Lians memory, optionally as-of a past date.