paddleocr-doc-parsing
Use this skill to extract structured Markdown/JSON from PDFs and document images—tables with cell-level precision, formulas as…
Use when the user wants to analyze their communication style with AI from Claude Code logs — asks for a "prompt warrior" profile, an "AI profile", "wrapped", a psychological portrait of how they prompt, statistics of their sessions/messages, or personalized prompt-engineering
Claude Code
$ npx -y skills add timoncool/prompt-warrior --skill prompt-warrior --agent claude-code
Codex
$ npx skills add timoncool/prompt-warrior --skill prompt-warrior -a codex -y
Cursor
$ npx skills add timoncool/prompt-warrior --skill prompt-warrior -a cursor -y
Gemini CLI
$ npx skills add timoncool/prompt-warrior --skill prompt-warrior -a gemini-cli -y
GitHub Copilot
$ npx skills add timoncool/prompt-warrior --skill prompt-warrior -a github-copilot -y
OpenCode
$ npx skills add timoncool/prompt-warrior --skill prompt-warrior -a opencode -y
Windsurf
$ npx skills add timoncool/prompt-warrior --skill prompt-warrior -a windsurf -y
name: prompt-warrior description: Use when the user wants to analyze their communication style with AI from Claude Code logs — asks for a "prompt warrior" profile, an "AI profile", "wrapped", a psychological portrait of how they prompt, statistics of their sessions/messages, or personalized prompt-engineering recommendations based on their chat history. Works in any language (RU/EN lexicons built in).
Builds a gamified analytical portrait of the user's AI collaboration style from their local Claude Code JSONL logs: real metrics on a FIXED scale (comparable between people) plus fun statuses — a title, a level, achievements with rarity — and evidence-based prompt-engineering recommendations. It is NOT an RPG character sheet: no classes, no stat blocks; the analytics are the product, the statuses are the garnish.
**The scale is a contract.** All formulas and thresholds live in `scripts/analyze.py` (SCALE v1) and `references/scale.md`. NEVER adjust formulas, thresholds, rank mappings, or achievement conditions per user — comparability is the whole point. If a metric looks unflattering, it stays. Report numbers only from `profile.json`, never invent or soften them.
1. **Run the analyzer** (Python 3, stdlib only, read-only — it never modifies logs):
python scripts/analyze.py -o profile.json # all time, all projects python scripts/analyze.py --days 7 -o profile.json # last week python scripts/analyze.py --days 30 -o profile.json # last month python scripts/analyze.py --date-from 2026-06-01 --date-to 2026-06-30 -o profile.json python scripts/analyze.py --project <dir-name> -o profile.json # one project
THE RANGE IS THE USER'S CHOICE: if they named a period («за неделю», "this month", dates), pass it; if they didn't, default to all time and mention that a range is available. Never pick a range for the user silently. Default logs location: `~/.claude/projects`. Use `--projects-dir` to override. Try `python3` if `python` is missing. RUNNING IN A DIFFERENT HARNESS (OpenCode, Codex CLI, Gemini CLI, Copilot)? See `references/harnesses.md` — known log locations and formats, and how to plug a new source into SOURCES. If your paths differ, orient by analogy as described there.
2. **Read `profile.json`.**
needed; stop.
3. **Generate the local avatar (optional, offline)** — a deterministic monster from the user's title via the `robohash` package (assembles bundled PNG layers locally; zero network):
python scripts/avatar.py --from-profile profile.json -o avatar.png
If the package is missing, offer ONCE: «поставить `pip install robohash` для локальных аватаров-монстров?» — install on yes, skip on no. Without the avatar the card simply renders without an image — NEVER substitute placeholders, letters or icons in its place. The monster evolves when the title changes — mention it.
3а. **Write the Warrior's Chronicle** («Хроника воина») — 2-4 paragraphs (~100-180 words) that YOU, the model, author from profile.json: a characterization / mini-biography of the user in the grimoire-chronicle voice with light humor. Rules: facts strictly from the profile (no inventions), NO numbers (numbers live in the card sections — each number appears exactly once), neutral to metric values (do not shame, do not flatter), 1-2 <em> accents max, written in the card's language. This is the one place the model speaks freely — make it feel written, not generated.
4. **Build and SHOW the card** — output degrades gracefully, in this order: a. You do NOT write HTML/CSS/SVG. Write `content.json` — ONLY your authored parts, in the card language:
{"chronicle": ["<p1>", "<p2>", "<p3>"],
"strengths": ["..."],
"weaknesses": [{"w": "...", "a": "...", "ev": "...", "url": "https://..."}]}(chronicle = step 3а; strengths ≤3 and weakness→fix pairs ≤4 picked by the rules in `references/widget.md`). Then run the canonical renderer:
python scripts/render.py profile.json --content content.json --lang ru -o ai-profile.html
(`--lang en` for English — labels are symmetric, data fields are bilingual.) It fills the whole card: numbers exactly once, bars, gauges, icons, favicon, seal, achievements accordion, avatar if `avatar.png` exists. Tell the user the path. NEVER Read .svg asset files into context (widget.md, rule 2д). b. OPEN it for the user: if a preview panel/tool is available, open it there; otherwise open in the default browser (`start` on Windows, `open` on macOS, `xdg-open` on Linux). Do not make the user open the file by hand. c. If an inline widget tool is available, ALSO render an inline widget mirroring the same sections and numbers. d. If NONE of the above is available (headless/console-only environment), render the card as TEXT in the console following the text-fallback spec at the end of `references/widget.md` — same sections, same numbers, bars as unicode blocks.
5. **Explain the profile** in the user's conversation language (the widget carries both RU and EN labels from profile.json). If `profile.delta` is present and non-null, LEAD with what changed since the last visit — new achievements first (that is the share-worthy moment: «получена новая ачивка!»), then level/title changes, then the 2-3 most notable metric shifts with direction. Then the numbers: notable metrics, strengths and weaknesses; then the flavor: title, achievements. Always surface 1-2 non-obvious insights — the most extreme or most characteristic numbers in the profile, phrased as discoveries, not judgements. Numbers
Your AI agent's logs are hiding a character sheet. We found it. Prompt Warrior is an agent skill that reads your local session logs — Claude Code out of the box; Codex CLI, OpenCode, Gemini CLI and Copilot via documented log formats — and turns them into
Use this skill to extract structured Markdown/JSON from PDFs and document images—tables with cell-level precision, formulas as…
Estimates intracellular metabolic fluxes from steady-state carbon-13 isotope-tracing measurements using validated atom maps,…