Borrowing it
Nothing to install: this file belongs to egregore-labs/egregore. 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/egregore-labs/egregore/main/.claude/skills/archive/SKILL.mdgit clone --depth 1 https://github.com/egregore-labs/egregoreWrote 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/skills/egregore-labs/egregore/archive)<a href="https://agentmods.dev/skills/egregore-labs/egregore/archive"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/archive/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/skills/egregore-labs/egregore/archive"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/archive.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 466 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00041 | $0.05010 |
| Opus 5 | $0.00020 | $0.02505 |
| Sonnet 5 | $0.00008 | $0.01002 |
| Haiku 4.5 | $0.00004 | $0.00501 |
Grade A, and why
archive scanned grade A with 1 finding 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 10d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
**Neo4j-first.** All queries via `bash bin/graph.sh query "..."`. No MCP. No direct curl to Neo4j. How it starts
The opening of the file, as written. The whole thing — 587 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Capture effective prompt patterns and store them as reusable knowledge.
Sequences of human steering interventions that produced good AI reasoning — stored in the shared knowledge base as reusable patterns.
When to invoke
User says: "that prompt worked well", "save this prompting technique", "archive this steering pattern", "the way I phrased that got great results"
Not this: insight about the work itself → /reflect · private thought → /note
Topic: $ARGUMENTS
Auto-saves. No need to run /save after.
Two Modes
| Invocation | Mode | AskUserQuestion calls |
|---|---|---|
/archive |
Interactive — model reads session context, extracts prompt chains | 1-2 |
/archive [description] |
Quick — user provides the pattern directly | 0-1 |
Mode detection:
- No arguments → Interactive mode
- Any arguments → Quick mode
Mode detection
MODE=$(jq -r '.mode // "connected"' egregore.json 2>/dev/null)
Local mode (mode === "local"): Skip ALL bin/graph.sh calls — do NOT run them. Do NOT show any graph-related messaging ("Graph offline", "will sync", Neo4j, etc.).
Local-mode flow:
- Step 0: Get user via
git config user.name. Skip ALL context queries (Q1-Q4) — do not run them. - Step 1: Extract moves from session context only (no graph-aware suggestions).
- Step 3: Skip relation detection entirely — do not run quest/artifact queries.
- Step 4: Create pattern file — same as connected mode.
- Step 5: Skip entirely — no Neo4j Artifact creation.
- Step 6: Auto-save — same as connected mode.
- Step 7: TUI — use
✓ Saved · pushed(not "graphed"). Use/activity to see it.as footer.
Connected mode: Full behavior as specified below.
Execution rules
Neo4j-first. All queries via bash bin/graph.sh query "...". No MCP. No direct curl to Neo4j.
CRITICAL: Suppress raw output. Never show raw JSON to the user. All bin/graph.sh calls MUST capture output in a variable and only show formatted status lines.
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.
- 10d ago First seen · 587 lines · 41 tokens per session scan A feaddc0aa81e
archive is a skill published in the GitHub repository egregore-labs/egregore (282 stars, last pushed 6d ago), licensed MIT. It adds 41 tokens to every session and 5,010 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
learn
Diagnose and fix agent behavioral surfaces when the user corrects a mistake — connects to Claude native memory.
memorywhale
Query and write durable debugging memory recorded by MemoryWhale. Use when debugging a failure that may have happened before, when you need the exact error/flags/output from an earlier attempt, when the user asks "how did we fix this last time?", or once you've figured out why something failed / how a fix worked and…
init
Turn on Rekal memory in the current repository by running rekal init. Use when the user asks to initialize or set up Rekal here, or when a rekal command reported the repository is not initialized. Once per repository. Do not offer this merely because a repo lacks a .rekal/ store — most repos do not want one.
install
Install the Rekal binary on this machine. Use when rekal is not on PATH — a command reported command not found — or when the user asks to install Rekal. Once per machine, not per repository; to set up a repo that already has the binary, use the init skill instead.
atomic-wiki
Conversational wiki and capture-bucket routing. Fires when the user wants a place, space, or folder for notes, research, tickets, raw dumps, or knowledge capture — checks the block in /.claude/CLAUDE.md; if the cwd is under a registered realm, creates the folder as a bucket via atomic wiki bucket add rather than a…
remem
Use when the user asks Codex to recall prior project context, save durable decisions or bug fixes, inspect remem memory health, or activate remem automatic memory hooks from the Codex plugin.