This release adds 2 notable features for engineering teams evaluating rollout.
✓ No known CVEs patched in this version
Summary
AI summaryAdds a Higgsfield creative handbook and a multi-model evaluation matrix runner.
Changes in this release
| Type | Severity | Summary | CVE |
|---|---|---|---|
| Feature | Low |
Adds Higgsfield knowledge pack markdown file for prompt guidance. Adds Higgsfield knowledge pack markdown file for prompt guidance. Source: llm_adapter@2026-05-26 Confidence: high |
— |
| Feature | Low |
Adds `npm run matrix` command to generate multi-model evaluation HTML report. Adds `npm run matrix` command to generate multi-model evaluation HTML report. Source: llm_adapter@2026-05-26 Confidence: high |
— |
| Feature | Low |
Adds `--json-out <path>` flag to `evals/run.mjs` for machine‑readable output. Adds `--json-out <path>` flag to `evals/run.mjs` for machine‑readable output. Source: llm_adapter@2026-05-26 Confidence: high |
— |
| Feature | Low |
Provides hover details for failing checks in the generated matrix HTML report. Provides hover details for failing checks in the generated matrix HTML report. Source: granite4.1:30b@2026-05-26-audit Confidence: low |
— |
| Performance | Low |
Implements model‑class‑gated fixtures in matrix evaluation (small, mid‑tier, reasoning). Implements model‑class‑gated fixtures in matrix evaluation (small, mid‑tier, reasoning). Source: granite4.1:30b@2026-05-26-audit Confidence: low |
— |
Full changelog
Summary
Patch release. Two additive ships, no engine code changes:
packs/higgsfield-creative-handbook.md— knowledge pack for Higgsfield-targeted prompts (Soul ID workflow, camera moves, model-selection rules, Marketing Studio modes, prompt structure). Pairs with thehiggsfieldplatform entries from 1.6.1.npm run matrix— multi-model eval matrix runner that produces a side-by-side HTML showing engine performance across model classes.
Higgsfield knowledge pack
9 H2-chunked sections covering:
- Model selection guide — which of the 13 Higgsfield-routed models for which use case (Soul 2.0 for portraits, Sora 2 for photoreal video, Cinema Studio for filmic shots, Kling 3.0 for motion fidelity, etc.)
- Prompt structure pattern — long-form natural-language prose with the canonical structure ([shot type] [subject + action] [setting] [lighting] [textures] [palette + mood] [style cues])
- Camera moves — explicit vocabulary table (push-in, pull-out, crane, orbit, tilt, pan, handheld, etc.) for video models
- Soul ID workflow — 3-step training process for face-faithful character reuse across generations
- Multi-reference editing — when to route to
edit?model=multiinstead of text-to-image - Marketing Studio workflows — brand kit, avatars, products, hooks, virality predictor
- Mode presets — UGC Factory, TV Spot, Wild Card, Pinterest Pin, etc.
- Common pitfalls — don't translate Midjourney flags verbatim, don't redescribe Soul ID characters in prose, keep < 150 words
- Output specs — 4K images, 15s video, credit costs
Context Curator pulls relevant chunks via semantic retrieval when prompts target Higgsfield. No explicit loading needed for users who npm install clarifyprompt-mcp — the pack ships in the npm tarball and is discovered at runtime.
npm run matrix — multi-model eval matrix
npm run matrix -- --models llama3.2:3b,qwen2.5-coder:7b-instruct-q4_K_M,qwen2.5:14b-instruct-q4_K_M
Runs the eval harness sequentially against each model, writes per-model JSON, stitches into one side-by-side HTML at evals/matrix.html.
What it lights up:
- The 3 model-class-gated fixtures (
shape-small-local-model/shape-mid-tier-model/shape-reasoning-model) that single-model runs skip — each lights up on its target model class. - Cross-model deltas at a glance — e.g.
analyzer-creative-mediafails on qwen-coder-7b but passes on gpt-4o-mini. - Hover any cell for failing-check details.
Implementation note: evals/run.mjs gained a --json-out <path> flag (matrix.mjs uses it; also useful for CI tooling that wants machine-readable run data).
Where it lives: evals/matrix.mjs is NOT in the npm tarball — it's a maintainer/contributor tool you run from a cloned repo, not a runtime artifact.
Compatibility
- No MCP tool surface changes — still 23 tools.
- No env-var changes.
- No platform count changes — still 60+ platforms.
- Tarball grows ~10 KB for the knowledge pack file (103 files / ~162 KB packed total).
Full diff: https://github.com/LumabyteCo/clarifyprompt-mcp/compare/v1.6.1...v1.6.2
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About LumabyteCo/clarifyprompt-mcp
MCP server for AI prompt optimization — transforms vague prompts into platform-optimized prompts for 58+ AI platforms across 7 categories (image, video, voice, music, code, chat, document).
Related context
Beta — feedback welcome: [email protected]