dancing-bear: Skill for Claude Code

.claude/skills/familiarize/SKILL.md

familiarize is a skill for Claude Code from dancing-bear-show/dancing-bear. It costs 51 tokens per session (784 once invoked), scanned A, original, MIT.

A repository-orientation tool for the dancing-bear personal-assistants codebase. It loads a compact summary of the project's structure, important files, commands, and working rules.

In plain words
What is it for?
Use it at the start of a session or when you need to rediscover the repository's tools, architecture, and coding conventions.
Why use it?
It reduces the time needed to understand an unfamiliar repository before making changes. It also points agents to deeper documentation only when a task needs it.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

This is dancing-bear-show/dancing-bear's own configuration. It tells Claude Code how to work on dancing-bear itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything dancing-bear configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is ./bin/llm familiar --stdout.

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/dancing-bear-show/dancing-bear/main/.claude/skills/familiarize/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/dancing-bear-show/dancing-bear

Made for: Claude Code.

Wrote 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.

agentmods badge for familiarize

README.md
[![agentmods](https://agentmods.dev/badge/skills/dancing-bear-show/dancing-bear/familiarize/github.svg)](https://agentmods.dev/skills/dancing-bear-show/dancing-bear/familiarize)
Your own site
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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.

agentmods 80×15 button for familiarize

Your own site · 80×15
<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>
Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 784 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured yesterday against content hash e7feeda8e050, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

.claude/skills/familiarize/SKILL.md · 82 lines

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, telemetry cost/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.

Read the full file on GitHub · 82 lines

Changes

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.

  1. yesterday First seen · 82 lines · 51 tokens per session scan A e7feeda8e050

Subscribe to this mod's changes

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.

Related

familiarize compared with skills from other repositories

familiarize next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
familiarizedancing-bear-show/dancing-bearSkill7yesterdayMITA51Claude Code
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outlook-mcpmpalermiti/outlook-mcpSkill412d agoMITA96Claude Code, Codex
olkrlrghb/olkcliSkill2314d agoMITA28Claude Code, Codex
mail-operationsdesirecore/marketSkill2todayMITA151Claude Code
corresyncnkiyohara/corresyncSkill22d agoApache-2.0A112Claude Code, Codex
c-calendardaxaur/openpawSkill1785mo agoMITA39Claude Code, Codex