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 skills/netgrade-digital/shared-agents/shared-agents-knowledgenpx skills add netgrade-digital/shared-agents --skill shared-agents-knowledgegit clone --depth 1 https://github.com/netgrade-digital/shared-agentsWhat 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 | $0.00054 | $0.00629 |
| Opus 5 | $0.00027 | $0.00315 |
| Sonnet 5 | $0.00011 | $0.00126 |
| Haiku 4.5 | $0.00005 | $0.00063 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shared Agents Knowledge
Path: $SHARED_AGENTS_HOME (default: ~/.shared-agents)
Automatic sync (always — no user action)
Every session, first step: run sync before anything else.
"${SHARED_AGENTS_HOME:-$HOME/.shared-agents}/scripts/sync.sh" pull
Pulls Core (~/.shared-agents) and Team (~/.shared-agents/team/) when configured.
- Do not ask the user to sync manually.
- Do not skip because "probably up to date".
- Offline/errors: continue with local files; note only if learnings may be stale.
IDE hooks also pull on session start (Cursor sessionStart, Claude SessionStart). Agent must still sync if hooks may not have run (subagents, headless).
Retrieve (before non-trivial tasks)
- Sync (pull) — always first.
- Read
team/learnings/index.yamlforproject,domain,tags,versions. - Grep
team/learnings/approved/for task keywords. - Prefer learnings whose
versionsmatch the project's stack (exact patch or same MAJOR.MINOR.PATCH line); treatexperimentalconfidence as hints. - Summarize briefly — do not dump the whole repo.
Capture (after non-trivial tasks — ask first)
Always ask after substantive tasks:
„Soll ich ein Team-Learning in shared-agents anlegen?"
| User says | Action |
|---|---|
| Yes / „ja" / „learning speichern" | Write to team pending/ (see below) |
| No | Do nothing |
Also capture when user explicitly asks anytime.
When writing:
- Activate skill
capture-learning. - Resolve path:
sa pending path YYYY-MM-DD-short-slug(see docs/canonical-paths.md — never workspace-relative; not in Core-Repo). - Never write directly to
approved/. - Remind user: teammate runs
sa review→approved/→ then all agents can use it.
For shell commands (install, review, pending push): skill sa-cli or run sa help.
Headless agents (OpenClaw)
Wrap commands with entrypoint (sync then exec):
"$SHARED_AGENTS_HOME/scripts/agent-entrypoint.sh" <your-agent-command>
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 · 71 lines · 54 tokens per session scan A 0abf27a1ace4
shared-agents-knowledge is a skill published in the GitHub repository netgrade-digital/shared-agents (4 stars, last pushed 2mo ago), licensed MIT. It adds 54 tokens to every session and 629 once invoked, about $0.0003 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.
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