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Commits
| Author | SHA1 | Message | Date | |
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 aleleba
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8094183940
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Phase 6.3.17: fix a harness fidelity bug and add a vibrancy metric
The first baseline measured production with only 2290 of the 16392 characters of the server's instructions block - 14%. The missing 86% is exactly the API grounding: Core Shape Properties and Methods, Layout Systems, Text Elements, and The penpot and penpotUtils Objects, which is where insertChild, resize(), the layouts and penpotUtils are documented. That was worth catching, because the discrepancy had a visible signature: the measurement said production creates nothing, while the user's real Claude Code session produced grey boxes, i.e. shapes greater than zero. When a harness and reality disagree, the harness is the first suspect. In phase 5 a low max_tokens manufactured an apparent regression the same way. The gate now injects the full document, minus the trailing "You have hereby read the Penpot High-Level Overview" line, which is framing of the tool response rather than part of the instructions block and would otherwise tell the model it had already read something. The finding survives the fix. Across the five prompts measured cleanly under the corrected condition, shapeCount is still zero on every one. So the API invention is not an artefact of withholding documentation from the model - it happens with the documentation present. Also adds the vibrancy requirement the user raised as first-class scope: given an ambiguous brief the model must choose and justify a palette rather than ask or fall back to defaults. Neither distinctFillColors nor placeholderGreys distinguishes a vibrant palette from a muted but technically non-grey one, so four metrics are added: chromaticFills, meanChromaticSaturation, paletteStructured (a dominant brand hue, an accent at least 30 degrees away, and neutrals), and finalMessageListsHex, because a palette chosen in silence cannot be adjusted by the user. The saturation floor of 45 is derived, not asserted: measured over the 325 non-neutral fills of this phase's hand-authored corpus, median HSL saturation is 75, p25 is 48 and p10 is 35. A floor of 45 sits just under the first quartile and is cleared by 79% of those fills, so it is a floor the target behaviour already clears rather than an aspiration. The lightness band of 15 to 85 excludes near-blacks and near-whites, which can compute as highly saturated while reading as neutral. Gate prompt 6 becomes the user's literal failing sentence, and two ambiguous-brief prompts are added. One of them had to be re-domained after the disjointness check found it shared a 6-gram with a seed - the check fails on a single shared shingle, which is what makes it useful. Results so far are partial: prompts 1-5 measured cleanly, 6 has a timed-out audit and 7-10 hit the MCP outage, so those get re-measured. Both runs are kept, the 14% one renamed to record what it was. |
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aleleba
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5f0ddd962c
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Phase 6.3.17: measure the gate 5 baseline against production
Ran the full agent loop against vllm-qwen36 on port 8000 (read-only HTTP)
with the Penpot plugin live, before asking for any downtime. Without this
file "it improved" would be a claim rather than a measurement.
Result over the 8 graded prompts: mean score 14.9, zero prompts at or above
60, veto violated on 2 of 8, 66% of execute_code calls raised, and 7 of 8
prompts burned all 14 turns without producing a final message.
The plan predicted production would score near zero on distinct colours and
style richness while producing a high shape count - grey boxes. The shape
count is also zero. On a fresh page it creates nothing at all, so the
failure sits upstream of the grey boxes: the model invents a Figma-shaped
API wholesale and every call throws. From the captured turns:
penpot.currentPage() is a property, not a function
penpot.createRectangle(page, 200, 56) takes no arguments
penpot.createText(page, ...) takes one, the text
penpot.getPageById(...) lives on penpotUtils
fills = [{type:'solid', color:{r,g,b,a}}] is {fillColor, fillOpacity}
shadows = [{type:'drop', x, y, blur, ...}] is {style, offsetX, offsetY}
It then spends the remaining turns querying penpot_api_info without
recovering. So the reported symptom understated it.
Two robustness fixes the run itself forced, both after losing a completed
run to them:
- A ConnectionError does not just drop the request, it can drop the MCP
session, so retrying the same tools/call against a dead session fails
identically every time - which is exactly what the first attempt showed,
four retries and four identical ConnectionErrors. The client now redoes
the handshake before retrying, and that recovered two drops in this run.
- Results are written after every prompt. The first attempt died on prompt
4 and lost the three already measured, which is the expensive data
precisely because it requires production to be up.
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