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 rules/canyonroad/agentsh/execgit clone --depth 1 https://github.com/canyonroad/agentshWhat 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 | $0.00377 | $0.00377 |
| Opus 5 | $0.00188 | $0.00188 |
| Sonnet 5 | $0.00075 | $0.00075 |
| Haiku 4.5 | $0.00038 | $0.00038 |
Grade A, and why
EXEC 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 2d 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.
What it actually says
agentsh Command Execution
When executing shell commands in this codebase, use agentsh to run commands within a sandboxed session.
Syntax for Single Command Execution
Basic Form
agentsh exec SESSION_ID -- COMMAND [ARGS...]
The -- separator is required between the session ID and the command.
Examples
agentsh exec my-session -- ls -la
agentsh exec my-session -- npm install
agentsh exec my-session -- go build ./...
With Environment Variable (Preferred for Agents)
When AGENTSH_SESSION_ID is set, all arguments after exec become the command:
export AGENTSH_SESSION_ID=my-session
agentsh exec -- ls -la
agentsh exec -- npm install
Auto-Create Session on First Exec
If the session doesn't exist, use --root to auto-create it:
agentsh exec my-session --root /path/to/workspace -- ls -la
Or set AGENTSH_SESSION_ROOT:
export AGENTSH_SESSION_ROOT=/path/to/workspace
agentsh exec my-session -- ls -la
Common Flags
| Flag | Description |
|---------------|------------------------------------------------|
| --timeout 30s | Command timeout (e.g., 30s, 5m) |
| --output json | JSON structured output instead of shell output |
| --stream | Stream output as it's produced |
| --pty | Interactive PTY mode |
Environment Variables
| Variable | Description |
|----------------------|------------------------------------------------|
| AGENTSH_SESSION_ID | Session ID to use (avoids passing as argument) |
| AGENTSH_SESSION_ROOT | Root directory for auto-creating sessions |
| AGENTSH_SERVER | Server URL (default: http://127.0.0.1:18080) |
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.
- 2d ago First seen · 56 lines · 377 tokens per session scan A b722341ea9f2
EXEC is a cursor rule published in the GitHub repository canyonroad/agentsh (378 stars, last pushed 26d ago), licensed Apache-2.0. It adds 377 tokens to every session, about $0.0019 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 2026-08-30.
Other cursor rules, from other repositories
agent-development
Python agents are typically in folders named agent-py/ or agent/ and use the sdk-python/ package.
pi-en
PI Cognitive AI. Trigger: $pi/coding/dev/code/architecture/API/refactor/debug/bug/error/exception/crash/timeout/performance/optimization/test/compile/git/release/verify/review/CR/product/requirements/ops/growth/design/team/support, or deep/2+ failures/looping/stuck/giving-up/retry/nevermind.
pi
你与用户是伙伴🤝战友🔥亲人❤️利益共同体🎯——目标一致:高质量解决问题。百务皆适,融贯古今中西的通才。.
git-author
Git author identity for commits so GitHub attributes contributions correctly.
tools
(none|read|write|network|exec) and risk (low|medium|high|critical). These drive the permission classifier — be honest.
langgraph
for ANY question about LangGraph, use the langgraph-docs-mcp server to help answer -.