Borrowing it
Nothing to install: this file belongs to dancing-bear-show/dancing-bear. 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/dancing-bear-show/dancing-bear/main/.claude/skills/familiarize/SKILL.mdgit clone --depth 1 https://github.com/dancing-bear-show/dancing-bearWrote 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/dancing-bear-show/dancing-bear/familiarize)<a href="https://agentmods.dev/skills/dancing-bear-show/dancing-bear/familiarize"><img src="https://agentmods.dev/badge/skills/dancing-bear-show/dancing-bear/familiarize/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/dancing-bear-show/dancing-bear/familiarize"><img src="https://agentmods.dev/badge/skills/dancing-bear-show/dancing-bear/familiarize.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 | $0.00051 | $0.00784 |
| Opus 5.5 | $0.00020 | $0.00314 |
| Sonnet 5.5 | $0.00010 | $0.00157 |
| Haiku 4.5 | $0.00005 | $0.00078 |
Grade A, and why
familiarize 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 yesterday.
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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Familiarization
Load context about dancing-bear at session start.
When to Use
- Session start — run before responding to first request
- Context refresh — when you need to re-orient
- Feature discovery — exploring what tools are available
Run Familiarize
./bin/llm familiar --stdout
This returns a YAML capsule covering:
- Skip paths and heavy files to avoid
- Key CLIs and agentic schema pointers
- Familiarization contract (read-only rules)
Deep Dive (On-Demand Only)
Load these only when the task requires deeper understanding:
| File | When to Load |
|---|---|
.llm/CONTEXT.md |
Architecture questions, system overview |
.llm/MIGRATION_STATE.md |
In-flight work, current status |
.llm/PATTERNS.md |
Implementing features, copy-paste templates |
.llm/FAMILIARIZE_CORE.md |
Familiarization contract details |
Note: ./bin/llm agentic --stdout inlines the first three of these. Use
--compact (2KB vs 38KB) unless you specifically want them preloaded.
Generate on demand (never preload):
./bin/llm domain-map --stdout # directory structure deep dive
There is no .llm/DOMAIN_MAP.md file — the domain map is generated by the command
above. Do not try to read it as a file.
Tool Discovery
For CLI capabilities, use agentic schemas (never --help):
./bin/<assistant> --agentic --agentic-format yaml --agentic-compact
Primary surfaces: mail-assistant, calendar-assistant, schedule-assistant, phone-assistant.
Load only the wrapper(s) relevant to the current task.
Visualization + orchestration surfaces (load when the task involves rendering or DAG orchestration):
./bin/charts— render time-series charts from JSON (render,grid,reshape)./bin/diagrams— Mermaid diagrams (from-yaml,render,validate,embed,telemetrycost/token pies)./bin/workflow— YAML DAG workflow engine (parse,compile,run,lint,list,status)
These three are standalone argparse CLIs rather than llm --app routes, but they
do support --agentic — as do all 19 apps. Discover them the same way as any
other surface; llm familiar --verbose surfaces them too.
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.
- yesterday First seen · 82 lines · 51 tokens per session scan A e7feeda8e050
familiarize is a skill published in the GitHub repository dancing-bear-show/dancing-bear (7 stars, last pushed yesterday), licensed MIT. It adds 51 tokens to every session and 784 once invoked, about $0.0002 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 2026-11-07.
familiarize compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| familiarizedancing-bear-show/dancing-bear | Skill | 7 | yesterday | MIT | A | 51 | Claude Code |
| gogolafkfreund/nixos_config | Skill | 32 | yesterday | GPL-3.0 | A | 125 | Claude Code, Codex |
| outlook-mcpmpalermiti/outlook-mcp | Skill | 41 | 2d ago | MIT | A | 96 | Claude Code, Codex |
| olkrlrghb/olkcli | Skill | 23 | 14d ago | MIT | A | 28 | Claude Code, Codex |
| mail-operationsdesirecore/market | Skill | 2 | today | MIT | A | 151 | Claude Code |
| corresyncnkiyohara/corresync | Skill | 2 | 2d ago | Apache-2.0 | A | 112 | Claude Code, Codex |
| c-calendardaxaur/openpaw | Skill | 178 | 5mo ago | MIT | A | 39 | Claude Code, Codex |