Web・iOS・Androidの画面を、読み上げやキーボード操作に対応させ、ラベル、配色、操作対象の大きさなどをWCAG 2.2に沿って設計・点検するスキル。
- アイコンボタンの説明を付けたいとき
- キーボード操作とモーダルの点検
- コントラストや操作対象の大きさの確認
参考素材の見た目やカットのリズムを再利用できる設定に整理し、手元の映像の編集計画、画像・動画・3D素材の生成計画、編集可能なタイムラインをオフラインで作るスキル。
Use for file-driven multimodal image, video, and 3D-asset discovery; taste interviews; distill or apply workflows; style-pack validation; editable EDL/FCPXML export; provenance audits; and offline planning that must fail closed before provider generation.
好みの映像表現を聞き取り、参考素材の色や明暗、カットのリズムを再利用できるスタイルパックに整理します。設定を検証し、手元の映像からカットの長さと順序を計画して、編集ソフトに渡せるEDLやFCPXMLを出力します。画像・動画・3D素材それぞれの生成計画や、素材と設定の出所を確認するレポートも作れます。複数の表現ジャンルは分けて扱います。
「この参考映像のような雰囲気」を具体的な条件にしたいときや、同じリズムで別の素材を編集したいときに向いています。色やカメラの動きなどの見た目と、伝える内容を分けて整理し、編集前に計画を確認できます。
Pythonのecc-tasteforgeが必要で、ローカル素材の計測にはffmpegとffprobeを使います。このスキルの処理はオフラインです。生成サービスへの呼び出しや素材のアップロードは行いません。出力は試行用の仕様や編集計画であり、映像の色調補正、エフェクト描画、3Dメッシュの生成は別工程です。
この紹介文は、公開されている SKILL.md をもとに AI(Claude Haiku)が作成しました。正確な仕様は下の原文を確認してください。
インストールする前に、エージェントに与えられる指示の中身を確認できます。
For the complete standalone creative pipeline, use taste-distillation then
taste-application. Those ECC skills ship their Python scripts directly:
measure references, generate or pass through existing takes, grade, cut,
composite, verify, and hand off to Blender and Resolve. No separate video
repository is required for that flow. This skill documents ECC's packaged offline engine and its strict evidence contract.
TasteForge turns "make it feel like this reference" into a repeatable,
inspectable workflow: interview taste, distill it into a structured style
pack, validate the pack, apply its measured cadence and look to local media,
and export an editable timeline. The canonical implementation is the
tasteforge package shipped inside ECC at
skills/taste-application/scripts/tasteforge/. Ito-Markets/ito-video is an
example project that consumes the packaged ECC engine.
This boundary is the core of this compatibility skill. Its operations are local, deterministic, and offline:
| Operation | Deterministic? | ECC may run |
|---|---|---|
| Taste interview → profile | yes (offline) | yes |
| Pack inspect / validate against schemas | yes | yes |
| Distill profile (+ measured grounding) → spec | yes (dry-run semantics) | yes |
| Apply pack cadence to local media → report + timeline | yes | yes |
| Export EDL (CMX3600) / FCPXML 1.9 | yes | yes |
| Provenance / lineage report | yes | yes |
| Vision-model distillation of stills | provider generation | no |
| Reference-to-video, image-to-3D, hosted compose | provider generation | no |
Provider generation must fail closed in ECC. Any live Fal (or other
provider) call — generating shots, minting prop meshes, hosted VLM
distillation — requires explicit separately authorized execution under a
separate lane with its own review. In this compatibility lane, ECC never calls Fal, never reads any API
key or other credentials (FAL_KEY included), uploads no media, and mutates
no provider account state. When a request needs provider generation, state
exactly that boundary, run the local half (interview, pack validation,
planning, export), and stop.
Never claim a Fal workflow is saved. A local reference to a Fal endpoint, model id, or dry-run URL (they appear inside pack metadata) is reference-only: it never means a provider-side workflow was saved, persisted, or is authorized to run. Anything produced offline carries dry-run/dry_run semantics — say "dry-run spec" or "deterministic plan", never "generated by the model".
affaan-m/ECC; Python distribution ecc-tasteforge, package
directory skills/taste-application/scripts/tasteforge/. Install from the
extracted ECC package with python3 -m pip install ./skills/taste-application/scripts.
The example project Ito-Markets/ito-video pins a specific ECC commit.python3 -m tasteforge <command> — provenance, inspect, validate,
interview, distill, apply, export, multimodal. --live flags exit
with code 2 and refuse.provider is enum-locked to
"none"; dry_run to true).skills/taste-application/SOURCE.md. Run python3 -m tasteforge provenance for the machine-
readable version.Use the installed ECC engine for local deterministic commands and interpret
its JSON. Install the packaged engine if absent; do not reconstruct its logic
inline. taste.resolve is a compatibility import of tasteforge.resolve, so
the creative scripts and example project share one verified Resolve adapter.
The python3 -m tasteforge CLI uses the installed ecc-tasteforge distribution. The standalone taste-distillation and taste-application
scripts ship in ECC's opt-in media-generation module with their own Python
requirements. Neither path requires publishing the user's repository or media.
Before resuming a saved checkout, record its commit and inspect local branches
and worktrees for later implementation fixes. Run the canonical package's tests
and python3 -m tasteforge apply --help; ECC's text and fixture tests do not
prove that the selected Python checkout implements this contract.
| Stage | Owner | Reviewable result |
|---|---|---|
| Creative direction | taste | Named genres, reference observations, chosen look and avoid list |
| Distillation and planning | tasteforge-video | Measured evidence, separate genre specs, dry-run manifests and cadence plan |
| Editing and effects | video-editing, with the chosen renderer such as Remotion, Manim, or Fusion | Applied footage, actual tracks, editable effects and timeline |
| Optional generated assets or voice | fal-ai-media or the selected audio workflow, under its own authorization | Provider receipt and inspected output |
| Delivery | Editing workflow, then content-engine when requested | Reviewed exact export and distribution copy |
Use only the stages the project needs. The taste skill's historical
angelcore/cloud-trance palette and beat grammar are optional creative examples;
they must not override the current brief or merge distinct numbered genres.
Use each genre's actual references for its direction, including 3D Cyber Glitch
and Fluid Sketch. TasteForge does not replace these skills or require every
renderer. Keep 3D materials, geometry, wireframe behavior,
motion, and composition explicit in the genre signature. A 3D request manifest
is a plan for an asset; it is not a mesh. A subject-anchor descriptor names a
tracking requirement; it is not evidence that a subject was detected or tracked.
Inspect actual tracks, track-loss behavior, and rendered subject frames before
claiming that CV effects have been applied reliably.
interview): collect answers for the look axes — palette,
grain, lighting, focal length, camera motion, subject framing, grade,
mood adjectives, avoid list — and separately the content brief. Keep look
and content separate; merging them is the classic failure.distill): map the profile onto the spec schema offline,
embedding the pack's measured grounding (black/white point, contrast,
per-zone chroma, palette, cut rhythm) when a pack is supplied. The result
is a dry-run spec: deterministic, provider "none".validate / inspect): check the pack against its schemas;
report errors vs warnings (missing stills in a metadata-only pack are a
warning, not an error).apply): plan shot durations from the pack's measured cadence
(seeded, deterministic) over the user's local clips; produce the
application report and frame-exact timeline events.export): write CMX3600 EDL + FCPXML 1.9 with rational,
NTSC-safe times for import into a real NLE.provenance): report lineage — recovered-source digests,
generation history, fixture provenance, provider references as
pointer-only records.When the brief requires no repeated clips, use a canonical checkout supporting
apply --no-repeat --fps, and set the output frame rate explicitly. If those
flags are absent, report the implementation gap rather than silently using
legacy round-robin selection. Strict mode uses each normalized source path at
most once in manifest order and rejects insufficient or too-short sources.
Prepare enough reviewed selects to fill the cadence plan. This is source-level
uniqueness, not support for distinct in/out ranges from the same recording.
The application report is a cut plan. It does not perform visual shot ranking, grade footage, apply a LUT, render overlays, or import a Resolve project. Keep the pack's measured reference cadence separate from the output frame rate.
The export CLI expects {"clips": [...]}. Wrap the application's
timeline_events under clips before exporting, and pass the same --fps
used for application; export's default frame rate must not reconform the plan.
Check the emitted event count, total frames, unique sources, and media linkage
before handing the timeline to the editing workflow.
When that workflow applies overlapping effects in an NLE, allocate compatible
tracks and read back every requested start, end, and duration. A returned item
or a successful append call alone does not prove that every scheduled effect
was placed; reject missing, shifted, or truncated placements before rendering.
Use this path when local references must drive dry-run generation plans for image, video, and 3D-asset outputs while preserving genre separation:
python3 -m tasteforge multimodal --config workflow.json --out-dir out/multimodal
The config names numbered genres and local evidence files. Keep these candidate genres distinct rather than blending them into one generic aesthetic:
The command measures local references with ffprobe/ffmpeg and emits one style
spec per genre, separate image, video, and 3D-asset manifests, provenance, and
a Resolve effect recipe. The effect schedule must be seeded aperiodic. CV
effects require a real subject anchor whose exact lost-track policy is
disable_effect_until_track_recovers; continue_without_anchor and every
other policy fail closed. Every effect carries placement constraints that
preserve faces and readable type and prevent decorative corner meshes from
replacing full-frame 3D work.
The returned receipt is the bundle boundary. It binds every emitted evidence
artifact by relative path, byte size, SHA-256, genre, modality,
provider_execution:false, and exact reference/time provenance. The receipt
requires provider_calls:0 as an exact integer (the JSON boolean false is
invalid), provider_execution:false, and dry_run:true. Every genre spec also
requires explicit dry_run:true. The Resolve effect recipe requires that same
exact integer provider_calls:0, provider_execution:false, and dry_run:true.
Every modality manifest and every nested request must contain all four exact
fail-closed fields: integer provider_calls:0, provider_execution:false,
dry_run:true, and submit:false; each request also requires
provider_call_mode:"disabled". A missing field is a rejection, not a default,
and dry_run:false must be rejected before output is written.
Treat booleans as invalid numbers everywhere in timeline, evidence, probe, and
source-duration data. Every such numeric value must be a finite real: reject
true, false, NaN, infinities, negative event starts, non-positive durations,
out-of-range evidence times, and events ending beyond the declared finite
positive timeline. Whole-file evidence uses an explicit whole-file time basis
and never invents timestamps.
Receipt references are the duration authority. Key each validated reference
duration by its cited SHA-256; duplicate occurrences of one digest must agree
on duration or the bundle is invalid. Every effect evidence source_duration
and every subject-anchor source_duration must equal that digest's validated
receipt duration, not merely contain its cited time. Probe duration and all
probe measurements must describe the same stable bytes used for byte count and
SHA-256. If the source mutates while probing or rehashes differently while it
is still available, fail closed rather than emitting or accepting a receipt.
Always run bundle validation after creation. A missing image, video, or 3D-asset
manifest must fail closed. Genericized or duplicate genres, periodic schedules,
unanchored CV effects, missing placement constraints, provider-execution flags,
unbound output files, byte-size drift, or SHA-256 tampering must fail closed.
Reject output roots, intermediates, or artifacts that are symlinks, and reject
special files (including FIFOs and devices); outputs must remain regular files
under a real directory tree. If local ffmpeg or ffprobe is unavailable, the
CLI must return its bounded nonzero local-media-processing error without a
Python traceback. Do not repair a failed receipt by deleting evidence or
weakening validation.
# after installing the ECC engine; paths below are your project inputs
python3 -m tasteforge validate stylepacks/flashethereal
python3 -m tasteforge interview --answers answers.json --genre flashethereal --out profile.json
python3 -m tasteforge distill --profile profile.json --pack stylepacks/flashethereal --out spec.json
python3 -m tasteforge apply --pack stylepacks/flashethereal --media media.json --duration 20 --out report.json
python3 -m tasteforge export --events events.json --out-dir out --title flashethereal-cut
python3 -m tasteforge provenance
When shots must be generated, pass the reviewed brief and style direction to
taste-application under the user's explicit provider authorization. The
offline CLI remains fail-closed; its plans and editable timelines do not prove
a provider job ran.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Web・iOS・Androidの画面を、読み上げやキーボード操作に対応させ、ラベル、配色、操作対象の大きさなどをWCAG 2.2に沿って設計・点検するスキル。
AIエージェントの不調を、指示・記憶・ツール実行・画面表示など12の層から調べるスキル。コードやログを根拠に原因を整理し、重要度順の指摘と修正案をまとめます。
実際の開発課題で複数のコーディングエージェントを比較するスキル。成功率、取得可能なAPI費用、所要時間、繰り返し実行の安定性を測り、選定や更新後の評価に使えます。
AIエージェントが使うツールの種類や入出力、エラーからの復帰手順を設計・見直します。文脈の情報量も整理し、作業完了率や再試行回数で改善を評価します。
AIエージェントの失敗や同じ操作の繰り返しを記録し、原因の切り分け、小さな復旧操作、結果の報告まで進める手順を示して、根拠のある再試行につなげるスキル。
AIエージェントが失敗や同じ操作を繰り返す原因を、エラーと実行状況から整理します。小さな復旧操作を試し、結果と根拠を引き継げる報告にまとめるスキルです。