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README.md

@@ -23,7 +23,8 @@ Test prompts for [Tech-Graphics-Benchmark](https://github.com/danielrosehill/Tec
 | `style` | The visual style asked for |
 | `prompt` | Exact text sent to the model |
 | `input_image` | Path under `inputs/` for image-to-image, else `null` |
-| `expected_text` | Every string that must appear, spelled exactly. Pass/fail ground truth |
+| `expected_text` | Every string that must appear, spelled exactly. Pass/fail ground truth. Empty for descriptive prompts, where any garbled or invented text fails |
 | `structure_checks` | Arrow, layout and content instructions the grader checks |
+| `notes` | Optional: sources for figures in the prompt, grading caveats |
 
 `inputs/whiteboard-mcp-01.jpg` is from [Sample-Whiteboards](https://github.com/danielrosehill/Sample-Whiteboards) (`whiteboards/030426.jpg`, photographed 2026-04-03).

prompts.jsonl

@@ -2,3 +2,5 @@
 {"id": "tgb-t2i-02", "modality": "text-to-image", "style": "manga, bold ink with flat colour", "prompt": "Create a manga-style technical diagram, bold ink lines with flat bright colours, showing a speech-to-text pipeline. Four boxes in a single left-to-right row, connected by arrows pointing right: \"Audio In\" -> \"Voice Activity Detection\" -> \"Transcription\" -> \"Text Out\". Below the row, a separate box labelled \"Custom Vocabulary\" with one arrow pointing up into \"Transcription\" only. A small speech bubble coming out of \"Text Out\" says exactly: \"Kubernetes, not Cooper Nettys!\". No other text.", "input_image": null, "expected_text": ["Audio In", "Voice Activity Detection", "Transcription", "Text Out", "Custom Vocabulary", "Kubernetes, not Cooper Nettys!"], "structure_checks": ["four boxes in one row, left to right, in the stated order", "three right-pointing arrows between them", "Custom Vocabulary sits below the row", "exactly one arrow from Custom Vocabulary, pointing into Transcription", "speech bubble comes from Text Out", "no extra text"]}
 {"id": "tgb-i2i-01", "modality": "image-to-image", "style": "keep handwriting, add colour", "prompt": "Turn this whiteboard photo into a clean, colourful diagram. Remove the whiteboard frame, glare and background, and correct the perspective to a straight-on view on a white background. Keep my handwriting style but make it neater and easy to read. Keep every label, box and arrow exactly where it is and pointing the same way. Fix obvious misspellings of technical names (\"Proxmox\", \"Replicate\", \"Remote\") but do not add, remove or reword any label. Add colour: give each group of related boxes its own soft colour and make the arrows a contrasting colour.", "input_image": "inputs/whiteboard-mcp-01.jpg", "expected_text": ["WAN", "Telegram", "CF / Tailscale", "OpenClaw", "Docker", "VM", "META MCP", "META MCP 2", "Desktop Client", "No proxy possible", "LAN use", "LAN MCPs", "NAS", "HA", "SBCs", "Proxmox", "SSE Remote MCPs", "Replicate", "Google"], "structure_checks": ["Desktop Client -> META MCP 2", "Desktop Client -> VM", "WAN -> OpenClaw (labelled CF / Tailscale)", "META MCP -> LAN MCPs", "META MCP -> SSE Remote MCPs", "LAN MCPs -> NAS, HA, SBCs, Proxmox", "SSE Remote MCPs -> Replicate, Google", "upward arrow labelled LAN use", "handwriting character kept", "no labels added or dropped"]}
 {"id": "tgb-i2i-02", "modality": "image-to-image", "style": "anime, clean sans-serif labels", "prompt": "Redraw this whiteboard sketch as a vibrant anime-style infographic. Replace all of my handwritten labels with a clean sans-serif font, spelled correctly. Keep the same layout: every label, box and arrow stays in the same relative position and every arrow points the same way. Draw the two little faces as small cute anime characters, keeping their labels (\"Desktop Client\" and \"Telegram\"). Do not add, remove or reword any label.", "input_image": "inputs/whiteboard-mcp-01.jpg", "expected_text": ["WAN", "Telegram", "CF / Tailscale", "OpenClaw", "Docker", "VM", "META MCP", "META MCP 2", "Desktop Client", "No proxy possible", "LAN use", "LAN MCPs", "NAS", "HA", "SBCs", "Proxmox", "SSE Remote MCPs", "Replicate", "Google"], "structure_checks": ["Desktop Client -> META MCP 2", "Desktop Client -> VM", "WAN -> OpenClaw (labelled CF / Tailscale)", "META MCP -> LAN MCPs", "META MCP -> SSE Remote MCPs", "LAN MCPs -> NAS, HA, SBCs, Proxmox", "SSE Remote MCPs -> Replicate, Google", "upward arrow labelled LAN use", "all labels in sans-serif type", "no labels added or dropped"]}
+{"id": "tgb-t2i-03", "modality": "text-to-image", "style": "crayon, hand-drawn banner", "prompt": "Create a wide banner image (roughly 3:1) drawn in crayon on textured paper, like a bright, playful hand-drawn explainer. At the top left, a box labelled \"Boxty v1.0\" with a small subtitle \"tech vocabulary\", and next to it, in handwriting: \"WER 1.35%\". At the top right, a box labelled \"Jachnun v1.0\" with a small subtitle \"code-switching\", and next to it, in handwriting: \"WER 5.85%\". Between them, a third box containing a jumble of words: \"teudat zehut\", \"arnona\", \"makolet\", \"GitHub Gist\", \"Kubernetes\". From that middle box, one bold arrow points straight down to a larger box at the bottom labelled \"Sabich v2.2\", with handwritten next to it: \"Code-switching WER 4.91%\" and \"Tech WER 2.76%\". In the margin beside the arrow, a scribbled note with a little doodle arrow pointing at Sabich: \"accuracy preserved!\". No other text.", "input_image": null, "expected_text": ["Boxty v1.0", "tech vocabulary", "WER 1.35%", "Jachnun v1.0", "code-switching", "WER 5.85%", "teudat zehut", "arnona", "makolet", "GitHub Gist", "Kubernetes", "Sabich v2.2", "Code-switching WER 4.91%", "Tech WER 2.76%", "accuracy preserved!"], "structure_checks": ["wide banner aspect ratio", "Boxty top left, Jachnun top right, word box between them", "each WER sits next to the right model", "exactly one arrow, from the word box down to Sabich v2.2", "margin note beside the arrow, pointing at Sabich", "crayon texture throughout", "no extra text"], "notes": "WER figures: Boxty v1.0 tech WER from its model card (hf.co/Hebrish/Parakeet-TDT-0.6B-v2-Tech-And-Accent, test revision f956dbb184c2); Jachnun v1.0 and Sabich v2.2 from the Sabich model card, English-Hebrew Code-Switching ASR Benchmark test set v2 (revision 48ec85a), checked 2026-10-28. Boxty's figure is on a different test set, so it is a label to reproduce, not a like-for-like comparison."}
+{"id": "tgb-t2i-04", "modality": "text-to-image", "style": "cover art, free style", "prompt": "Cover art for a blog post about fine-tuning a speech recognition model on one person's voice so it understands both tech jargon and Hebrew words dropped into English sentences. Two earlier specialist models (a tech-vocabulary model and a code-switching model) feed into one combined model that does both without getting worse at either. Show the idea visually: sound waves from a speaker turning into accurate text, two streams merging into one, a sense of things clicking into place. Warm, colourful and characterful, with a nod to Israeli street food (the models are named after foods: the combined one is Sabich, a stuffed pita). Leave clear space at the top for a title. Do not try to write a title or any sentences.", "input_image": null, "expected_text": [], "structure_checks": ["two streams visibly merge into one", "speech turning into text is legible as an idea", "clear space left at the top", "any text that appears is real, correctly spelled words; no pseudo-text or garbled glyphs"], "notes": "Descriptive prompt with no exact strings. text_exact passes only if the image contains no garbled or invented text."}