Skip to main content

figure-qa

Use this skill to QA a scientific figure for journal compliance, alignment, palette correctness, and text legibility. Triggers on "QA this figure", "check this figure", "review my figure", "is this figure paper-ready", "validate figure", "check the text in this figure", or when invoked after a figures skill produces output (unless the caller passes no-qa). Dispatches on input type (SVG, raster PNG/JPG/TIFF, Python plot script, or composed-figure directory), runs the programmatic checks including OCR of expected strings and palette compliance against the project theme, adds a vision rubric pass, and returns a report with a machine-readable JSON verdict that drives the generate, QA, fix loop.

الانتقال إلى التثبيت

معلومات المصدر

المستودع
neuromechanist/research-skills
آخر نشاط في المصدر
٢١ سبتمبر ٢٠٢٦ في ٠١:٢٧
لغة SKILL.md المكتشفة
الإنجليزية
النجوم
٤٦
التفرعات
٨

خيارات التثبيت

يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.

مراجعة ملفات المصدر

اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.

مستكشف الملفات
3 ملفات

عرض SKILL.md

SKILL.md
تعليمات المصدر · معاينة للقراءة فقط
name
figure-qa
description
Use this skill to QA a scientific figure for journal compliance, alignment, palette correctness, and text legibility. Triggers on "QA this figure", "check this figure", "review my figure", "is this figure paper-ready", "validate figure", "check the text in this figure", or when invoked after a figures skill produces output (unless the caller passes no-qa). Dispatches on input type (SVG, raster PNG/JPG/TIFF, Python plot script, or composed-figure directory), runs the programmatic checks including OCR of expected strings and palette compliance against the project theme, adds a vision rubric pass, and returns a report with a machine-readable JSON verdict that drives the generate, QA, fix loop.
version
0.2.0
# Figure QA Routes a scientific figure to an independent, fresh-context QA reviewer that detects the input type, runs the deterministic checks (fonts, palette, geometry, alpha, resolution, rendered text) with the helper scripts, and adds a vision-language model (VLM) rubric judgment for the aesthetic dimensions. This skill is a thin dispatcher: the detection logic, exit-code contract, VLM rubric, report shape, and the iterate loop all live in `references/`, and the deterministic engine lives in the figures plugin's `agents/figure-qa-scripts/`. ## When to use Activate when a figure needs a journal-submission QA pass, or after a figures skill (`figures:scientific-figure`, `figures:svg-figure`, `figures:svg-primitives`, `figures:transparent-icons`, `figures:ai-full-figure`, `figures:plot-styling`) produces output, unless the caller passes `no-qa`. ## What to pass to the reviewer Every dispatch carries the same briefing, so the right checks run: - the figure path and, when known, the input type - the target journal (`nature`, `science`, `cell`, `pnas`, `poster`, `slide`, or `generic`) - the theme path (`figures/theme.json`) so palette compliance is judged against the project bible rather than a fixed allow-list - every verbatim string the figure was asked to render (titles, panel letters, labels); without this list the raster text check is silently off - the physical width in millimetres for raster inputs, so text height converts to points ## Why a fresh-context reviewer A QA pass is more trustworthy from a reviewer that did not just author the figure. Run it in a separate context and pass only the briefing above. On tools without subagents, run the procedure inline. For several candidates, issue one dispatch per candidate in a single message so they run in parallel on the Sonnet tier. ## Dispatch In every branch the reviewer follows `references/figure-qa-procedure.md` (strict separation: scripts own ground-truth measurements, the VLM owns aesthetic judgment). - **Claude Code:** `Agent(subagent_type: "figures:figure-qa", ...)` with the briefing above. Honor a `no-qa` opt-out by returning immediately. - **Codex CLI:** plugin installation exposes this skill, not a Codex subagent. To use a fresh-context Codex reviewer, first copy `${CLAUDE_PLUGIN_ROOT}/agents/templates/figure-qa.toml` (the plugin's `agents/templates/` directory) to `~/.codex/agents/` or `.codex/agents/`, then invoke that configured agent if the current Codex surface supports `/agent`. If no Codex subagent is configured or available, use the fallback branch. - **Copilot CLI:** plugin installation exposes this skill and, through `.github/plugin/plugin.json`, the `.agent.md` reviewer in `agents/templates/`. Invoke that configured agent when the current Copilot surface supports custom agents. If running outside a plugin install, copy `agents/templates/figure-qa.agent.md` to `.github/agents/` or `~/.copilot/agents/`. If no custom agent is available, use the fallback branch. - **Fallback** (no subagent support, or an interactive in-thread check): first locate the procedure (`$CLAUDE_PLUGIN_ROOT/skills/figure-qa/references`, else `find . -type d -path '*/skills/figure-qa/references' | head -1`); if it cannot be found, stop and tell the user to install the figures plugin rather than guessing checks. Then follow `references/figure-qa-procedure.md` directly. ## The report and the loop The report keeps its markdown sections and ends with one fenced JSON block: `status` (`ship`, `revise`, `block`), `findings[]` each with `check`, `severity`, `message`, `action` (`regenerate`, `edit`, `overlay`, `rescale`, `recolor`, `none`) and a `hint`, plus `measurements` and the five VLM scores. Generation skills branch on that block. `references/iterate-loop.md` defines the generate, QA, fix, regenerate loop (N candidates in parallel, one targeted change per iteration, stop at `ship` or after three iterations) that `figures:ai-full-figure` follows. ## The brain (do not duplicate into dispatch or agent shells) - `references/figure-qa-procedure.md`: no-qa opt-out, script location, type detection, per-branch checks including the raster text check and theme palette compliance, exit-code contract, VLM rubric, the exact report shape, and the finding-to-action table. - `references/iterate-loop.md`: the candidate, QA, fix loop with its worker briefing and stopping conditions. - `agents/figure-qa-scripts/check_{svg,raster,plot_script}.py` (in the figures plugin): the deterministic engine, kept in place so other skills can call it directly. `check_raster.py --json --expect-text "..." --palette figures/theme.json --width-mm 89 --journal nature` is the text and palette check; `check_svg.py --json --palette figures/theme.json` covers SVG geometry, fonts, and palette.
عرض على GitHub