history-explorer
History Explorer analyzes skill usage patterns from local decision logs by aggregating co-occurrence frequencies, meta-skill statistics, and router test fixtures into JSON output. Use this tool to identify which skill combinations were invoked together over a specified period, measure meta-skill adoption rates, or retrieve test fixture data for downstream LLM analysis, particularly when the meta-skill-creator needs to harvest usage patterns or when auditing personal skill usage trends.
git clone --depth 1 https://github.com/opensquilla/opensquilla /tmp/history-explorer && cp -r /tmp/history-explorer/src/opensquilla/skills/bundled/history-explorer ~/.claude/skills/history-explorerSKILL.md
# History Explorer
Lightweight read-only view over `~/.opensquilla/logs/decisions-*.jsonl`. Aggregates `DecisionEntry.skills_invoked` (SCHEMA_VERSION 10) into co-occurrence frequencies, joins with `SkillLoader.list_meta_specs()` for meta-skill usage stats, and surfaces the `tests/test_skills/router_fixtures/` corpus.
## Usage
```
uv run python {baseDir}/scripts/explore.py \
--log-dir ~/.opensquilla/logs \
--query "Co-occurring chains for PDF workflows" \
--window-days 30 \
--include co_occurrences,meta_usage,router_fixtures \
--top-k 10
```
## Output
JSON to stdout with keys `co_occurrences`, `meta_usage`, `router_fixtures`, and a `placeholder` string when the log is empty.
## Fallback
If no decision-log exists, return an empty result with a placeholder string explaining "no history; downstream should rely on user intent only".Submit audio or video for multilingual dubbing, poll status, and download dubbed audio. Use when the user asks for dubbing, 多语言配音, 视频翻译配音, 译制片, or wants a source clip dubbed into another language.
Generate a structured short-video shooting script from a topic. Emits a strict, machine-parseable shot list (3 shots by default) with image prompt + video prompt + voiceover + on-screen text per shot. Trigger when the user asks for a video script, 分镜, 短视频文案, AI视频, 短剧脚本, or wants visual prompts ready for image/video generation.
Use when the user asks to schedule recurring tasks, one-off reminders, timers, or cron-style jobs through the OpenSquilla cron tool.
Multi-round research with explicit methodology, evidence tracking, and citation-tagged synthesis. Trigger on 'deep dive', 'research report', 'literature review', 'investigate X across sources', 'multi-round investigation'. Distinct from the `summarize` skill, which is a single-pass condensation; this skill maintains a state file across iterations, tracks coverage, and produces a long-form report with per-claim citations. Three execution stages: plan (scope into sub-questions), iterate (record evidence per round), compile (synthesize report). The skill itself does not fetch the web — it tells the host agent which fetches to perform via OpenSquilla's existing web tools, and records what comes back.
Read, edit, or create Microsoft Word `.docx` files. Trigger this skill whenever the user mentions a Word document, .docx file, contract, report, brief, memo, or asks to extract text, modify an existing doc, generate one from a brief, or audit tracked changes. Three execution paths: text-and-structure extraction, in-place edit-by-run (preserves styles), and create-from-scratch with python-docx. Falls back to OOXML unzip-and-patch for layout work python-docx cannot reach.
Capture the current git diff (staged, working-tree, or staged file list) as text. Direct shell call for workflows that need repository diffs without an LLM agent loop.
GitHub operations via `gh` CLI: issues, PRs, CI runs, code review, API queries. Use when: (1) checking PR status or CI, (2) creating/commenting on issues, (3) listing/filtering PRs or issues, (4) viewing run logs. NOT for: complex web UI interactions requiring manual browser flows (use browser tooling when available), bulk operations across many repos (script with gh api), or when gh auth is not configured.
Render HTML (with CSS) to a PDF file. Trigger when the user wants to export a styled report, invoice, label, or any HTML/Jinja-rendered page to PDF. Uses WeasyPrint, which supports a meaningful subset of CSS Paged Media (page size, margins, headers/footers, page-break-before/after). Optional dependency — install via `pip install opensquilla[document-extras]` or `uv add weasyprint` because WeasyPrint pulls in native libraries (Pango, Cairo, fontconfig) that need OS-level packages.