kiku-jw

Audit and improve a public GitHub repository's discoverability and any linked canonical site without confusing repository presentation with website SEO. Use for repository SEO, GitHub discoverability, topics/homepage/README optimization, GitHub Pages SEO, AEO, or agent-friendly public documentation.

Create, edit, analyze, or format spreadsheets (`.xlsx`, `.csv`, `.tsv`) with `openpyxl` and `pandas`, especially when formulas, references, and formatting must survive the change. Use when spreadsheet integrity matters more than ad hoc CSV hacking.

Analyze and reshape spreadsheet, CSV, or TSV data with `pandas` and stable output files. Use when the job is aggregation, filtering, joins, metrics, or tabular transformations rather than workbook-style editing.

Create or edit `.xlsx` workbooks while preserving formulas, references, formatting, and layout. Use when workbook integrity matters more than raw data analysis.

Produce a fast plain-text transcript with the bundled CLI using the light transcription model. Use when speaker diarization is not needed.

Produce a speaker-aware transcript with diarization and optional known-speaker hints using the bundled CLI. Use when the user explicitly needs speaker labels.

Transcribe audio files to text with optional diarization and known-speaker hints using the bundled CLI. Use when the user wants text from audio or video, especially when speaker labeling or repeatable output matters.

Create short narrated videos from text scripts, simple timelines, or still images using Python and ffmpeg, with optional edge-tts voiceover. Use when the user asks for an MP4 render, narration generation, or a simple explainer video build.

Create, edit, analyze, or format spreadsheets (`.xlsx`, `.csv`, `.tsv`) with `openpyxl` and `pandas`, especially when formulas, references, and formatting must survive the change. Use when spreadsheet integrity matters more than ad hoc CSV hacking.

Analyze and reshape spreadsheet, CSV, or TSV data with `pandas` and stable output files. Use when the job is aggregation, filtering, joins, metrics, or tabular transformations rather than workbook-style editing.

Create or edit `.xlsx` workbooks while preserving formulas, references, formatting, and layout. Use when workbook integrity matters more than raw data analysis.

Create short narrated videos from text scripts, simple timelines, or still images using Python and ffmpeg, with optional edge-tts voiceover. Use when the user asks for an MP4 render, narration generation, or a simple explainer video build.

Render and validate an MP4 from an existing `video-builder` spec JSON using the bundled Python pipeline. Use when a spec already exists and the job is actual rendering, not story or spec design.

Build a minimal JSON render spec for the local video pipeline from script lines, still images, or narration assets. Use when the spec artifact must exist before any MP4 render can run.

Transcribe audio files to text with optional diarization and known-speaker hints using the bundled CLI. Use when the user wants text from audio or video, especially when speaker labeling or repeatable output matters.

Produce a fast plain-text transcript with the bundled CLI using the light transcription model. Use when speaker diarization is not needed.

Produce a speaker-aware transcript with diarization and optional known-speaker hints using the bundled CLI. Use when the user explicitly needs speaker labels.

Build an implementation-ready spec bundle when a plain PRD is no longer enough: minimum useful contracts, schema, test plan, blueprint, gates, ADRs, boundaries, and GitHub-ready task breakdown. Use when ambiguity or architecture risk would otherwise slow execution.

Turn a completed coding session, git diff, notes, or transcript into a development diary draft or end-of-session writeup without rewriting the story by hand. Use near the end of meaningful work when the user wants a durable wrap-up.

Remove obvious AI-writing tics from drafts so the text sounds credible, calm, and human. Trigger on requests like make this sound less AI, detox this draft, or clean up public-facing copy before publishing.

Keep substantial work coherent across long sessions or compaction with one short factual `CONTINUITY.md` covering sources of truth, goal, constraints, decisions, evidence, and done/now/next state. Use when session drift would otherwise become a real risk.

Shape product work with the minimum useful framework after an idea clears basic validation. Use for assumptions, experiments, opportunity-solution trees, strategy, value proposition, or pre-mortems when the next product decision is still fuzzy.

Validate a raw product idea before PRD or implementation: buyer, pain, workaround, promised outcome, smallest wedge, distribution path, proof sought, kill criteria, and the next honest lane. Use when an idea still needs market or wedge truth.

Decide how much process a task deserves before coding: tiny vs substantial, chat vs GitHub, checklist vs execution brief, architecture lane vs full bundle, operator review vs council, and private diary vs public draft. Use when the shape of the work is the blocker.

Create a self-contained HTML explainer for systems, workflows, diagrams, timelines, comparisons, or data-heavy summaries when plain terminal text would be painful to read. Use when the output naturally wants a visual artifact instead of chat prose.