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.
git clone --depth 1 https://github.com/netgrade-digital/shared-agentsWrote 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/rules/netgrade-digital/shared-agents/shared-agents-knowledge)<a href="https://agentmods.dev/rules/netgrade-digital/shared-agents/shared-agents-knowledge"><img src="https://agentmods.dev/badge/rules/netgrade-digital/shared-agents/shared-agents-knowledge/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/rules/netgrade-digital/shared-agents/shared-agents-knowledge"><img src="https://agentmods.dev/badge/rules/netgrade-digital/shared-agents/shared-agents-knowledge.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 | $0.00851 | $0.00851 |
| Opus 5.5 | $0.00340 | $0.00340 |
| Sonnet 5.5 | $0.00170 | $0.00170 |
| Haiku 4.5 | $0.00085 | $0.00085 |
Grade A, and why
shared-agents-knowledge 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 today.
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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Team Knowledge (shared-agents)
Repo: $SHARED_AGENTS_HOME (default ~/.shared-agents). Paths: $SHARED_AGENTS_HOME/docs/canonical-paths.md
Shell commands (canonical — do not duplicate here): run sa help
Without bashrc alias: "${SHARED_AGENTS_HOME:-$HOME/.shared-agents}/scripts/sa" help
Also: shared-agents · sharedagents · bare sa = same as sa help
Full guide for users/agents: skill sa-cli
Automatic sync (mandatory — never ask the user)
At the start of every agent session, before any other work:
- Run:
"${SHARED_AGENTS_HOME:-$HOME/.shared-agents}/scripts/sa" sync
(same asscripts/sync.sh pull— prefersa sync) - Do not ask permission. Do not mention sync unless it failed and blocks the task.
- If pull fails (offline): continue with local copy; retry sync before reading learnings.
- After
sa sync(non-quiet) or on request: runsa status --brief— if action needed, tell the user briefly (pending reviews, skill links, adapters).
Cursor also runs sessionStart hook — still run sync once at session start if unsure hook ran.
Before tasks
After sync, search $SHARED_AGENTS_HOME/team/learnings/approved/ and $SHARED_AGENTS_HOME/team/learnings/index.yaml for matching project/domain. Use skill shared-agents-knowledge.
After tasks (mandatory for non-trivial work)
After a non-trivial task (feature, bugfix, refactor, multi-file change, non-obvious fix):
- Always ask the user: „Soll ich ein Team-Learning in shared-agents anlegen?"
- Wait for explicit yes/no.
- If yes: skill
capture-learning— paths, format, publish workflow (see skill). Shell: skillsa-cliorsa help. - If no: stop — do not write anything.
- Tell user:
pending/is draft only; promotion toapproved/is humansa review(skillsa-cliorsa help).
Skip the question only for trivial work (typos, formatting, pure Q&A, no reusable insight).
No secrets. Agent never writes approved/.
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.
- today Changed · +2 lines · +147 tokens per session 2af89dae07a6
- 1mo ago First seen · 57 lines · 704 tokens per session scan A 3d8c473882de
shared-agents-knowledge is a cursor rule published in the GitHub repository netgrade-digital/shared-agents (5 stars, last pushed yesterday), licensed MIT. It adds 851 tokens to every session, about $0.0034 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.
Other cursor rules, from other repositories
swamr-obsidian-brain
Swamr Obsidian Brain — persistent knowledge base that agents read from and write to across phases. Prevents context loss by maintaining architecture decisions, task outputs, learned patterns, and project knowledge in an Obsidian vault. Every agent MUST read relevant notes before starting and write a summary note when…
cursor
Cursor rule "cursor" from nitingupta220/riperflow, covering riperflow σ and ω₁=🔍r→ℙ(ω₁)→research.
haive-memories
Hivelore shared memories & block sensors (auto-generated).
haive-mcp-required
Require Hivelore MCP (getbriefing / memrelevantto) before substantive repo edits.
use-profile
Always consult the user's personal profile via the mcp-me MCP server before answering.
sift-memory
Use the local sift CLI to search Claude Code, Codex, Cursor, and OpenCode chat history when prior AI coding-assistant context, session memory, implementation history, or project decisions would help.