# Archaeological Drawing > 将器物照片、器物描述或已有草图转成符合考古报告规范的文物绘图工作流、生成提示词、出图执行和审图标准。Use when Codex needs to create, edit, critique, prompt, or generate cultural relic drawings, artifact report plates, orthographic line drawings, vessel profiles, half-section views, stone tool multi-view drawings, openwork ornament drawings, or black-and-white technical illustrations from photos or descriptions. Triggers include: 文物绘图、考古绘图、器物线图、器物剖面图、半剖面、正投影、文物照片转绘图、器物照片转绘图、cultural relic drawing, archaeological drawing, artifact illustration, orthographic artifact drawing, pottery profile drawing. - Skill: `hst368/archaeological-drawing` (Agent Skill, multi-file: 6 files) - Install (CLI): `npx skillmds@latest add hst368/archaeological-drawing` - Raw SKILL.md: https://api.skillmd.com/api/skills/hst368/archaeological-drawing/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Design & Media - Author: hst368 (https://skillmd.com/u/hst368) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/hst368/archaeological-drawing --- # Cultural Relic Drawing Convert artifact photos, descriptions, or existing drafts into archaeological drawings that prioritize scientific record over visual drama. Default to the highest-fidelity output the evidence supports. If the source is incomplete, lower the ambition of the drawing instead of inventing hidden structure, exact thickness, missing ornament, or a fake scale bar. ## Source Conditioning / Calibration Gate Classify the source before planning the drawing. This gate decides the maximum defensible output tier. - `Measured object + calibrated multi-view` - Source includes real measurements or trustworthy calibration plus multiple reliable views. - Eligible for `report-grade candidate`. - Final `report-grade measured drawing` still requires human review, proportion checking, and publication preparation. - `Near-orthographic view with scale reference` - Source includes a scale or clearly trustworthy size reference and a near-orthographic face or profile. - Eligible for a single-face orthographic drawing and possibly `report-grade candidate` of that face only. - Do not extend report-grade claims to unseen sides, thickness, or unsupported sections. - `Multi-view but uncalibrated` - Source includes several views, but no reliable calibration or measurement basis. - Eligible only for `evidence-bounded AI technical draft`. - Never present this directly as `report-grade measured drawing`. - `Single oblique photo` - Source is one angled or partial photograph without trustworthy calibration. - Eligible only for `visible-face redraw` within `evidence-bounded AI technical draft`. - Never reconstruct a full orthographic object record from this alone. - `Text-only description` - Source is verbal description with no reliable image evidence. - Eligible only for `view plan`, `prompt package`, or `schematic concept`. - Never present the result as a normative archaeological drawing. If more than one class seems plausible, choose the weaker class unless calibration and geometry support the stronger claim unambiguously. ## Output Tiers State or internally determine the output tier before prompt-writing. - `Tier 1: report-grade measured drawing` - Reserved for measured or calibrated evidence plus human review. - AI may assist with drafting, cleanup, or layout, but this is not a one-pass pure generation output. - `Tier 1.5: report-grade candidate` - Allowed when evidence is strong but not yet fully measured, calibrated, or publication-finalized. - Must state what is still missing, such as calibration, contour verification, line cleanup, or publication preparation. - `Tier 2: evidence-bounded AI technical draft` - Default tier for most photo-based requests. - Intended for draft production, review, correction, vectorization, and later publication preparation. - `Tier 3: archaeological-style illustration` - Allowed when evidence is weak, schematic, or primarily communicative. - Must not be presented as a report drawing. ## Image Backend Capabilities Use image-backend capabilities only to support the evidence-bounded workflow. Model features never upgrade the evidence class or output tier. - Useful capabilities: - reference-image editing for source-bound redrawing and correction - transparent-background PNG output for layout assets, overlay checks, and downstream composition - object/background separation for removing non-artifact backgrounds, labels, cast shadows, or captions - iterative revision for correcting contour drift, line hierarchy, and unsupported detail - Hard limits: - AI completion may be used only outside the artifact body, such as non-artifact background fill after object isolation. - Never use AI completion to restore missing artifact structure, occluded ornament, wall thickness, broken edges, unreadable inscriptions, or damaged symbol strokes. - Do not treat a cleaner isolated object, transparent edge, or layered asset as stronger evidence than the original source. - If the backend smooths, repairs, regularizes, or invents artifact detail, reject the result or demote the affected region to uncertain. ## Workflow Modes These modes sit underneath the evidence gate and output tier. They control execution only; they never upgrade the allowed output claim. - `main-structure pass` - Responsible for overall contour, major structure, projection, baseline symmetry or asymmetry, and broad ornament zoning. - Must intentionally suppress or defer high-risk local detail such as scripts, dense repeated ornament, glare-heavy edges, openwork crossings, and damaged boundaries. - `high-risk local pass` - Responsible only for isolated high-risk regions, such as scripts or symbols, dense ornament clusters, openwork intersections, reflective edges, break lines, and other ambiguity hotspots. - Must not alter the global contour or re-decide the overall projection. - Must not imply a separate exported local image unless the user explicitly asks for one. - `review-and-merge pass` - Responsible for reconciling the main structure draft with local corrections, demoting unsupported detail, and issuing the final `Risk note`. - Must decide whether weak local detail is merged, simplified, omitted, or explicitly downgraded. Relationship rules: - The `Source Conditioning / Calibration Gate` decides the maximum defensible claim. - The `Output Tier` decides how authoritative the deliverable can be. - The `Workflow Mode` decides how execution proceeds. - Workflow modes can make draft production safer and more auditable, but they cannot strengthen evidence or upgrade the output tier. ## Preprocessing / Region Triage Run this triage before `main-structure pass`. It is not optional. - Choose one `primary geometry reference`. - Use it to lock contour, projection, and the main face or profile. - Choose any `secondary detail references`. - Use them only to confirm local detail that is compatible with the same observed structure. - Crop or mentally isolate the relevant object, face, or local area before prompting when the source includes excess background, glare zones, or unrelated annotation. - Name the high-risk regions before generation. - Typical categories: scripts or symbols, dense repeated ornament, openwork crossings, reflective edges, damaged or missing boundaries, severe overlap or occlusion. - Decide whether the task should run as: - whole-object or whole-face drawing only - high-risk local handling only - split workflow with both - Demote or ignore low-value inputs instead of averaging them into the result. - Typical demotion cases: blur, heavy glare, bad perspective, strong occlusion, shallow depth of field, or poor local focus. Minimum triage outputs: - `source class` - `output tier` - `primary geometry reference` - `secondary detail references` - `named high-risk regions` - `selected mode sequence` If the triage is weak or contradictory, lower the ambition of the drawing before writing prompts. ## Mode I/O Contract Treat each workflow mode as a contract with clear inputs, outputs, and prohibitions. - `main-structure pass` - Input: - `source class` - `output tier` - `primary geometry reference` - object or face scope - Output: - stable global contour - projection and baseline - major structure and broad ornament zoning - unresolved local-risk list - Must defer: - scripts or symbols - dense ornament micro-topology - micro-breaks and tiny damaged edges - Must not change: - evidence gate - output tier - `high-risk local pass` - Input: - named high-risk regions - locked main-structure draft - compatible secondary detail references - Output: - per-region local decisions and localized corrections only - Must not change: - global contour - global orientation - overall projection - output tier - `review-and-merge pass` - Input: - main draft - local-pass decisions - Output: - merged draft - downgrade decisions - final `Risk note` - Must report each named local region as: - `resolved` - `simplified` - `omitted` - `left uncertain` User overrides such as `只跑主结构`, `只做高风险局部`, or `只做合并复核` may restrict the mode sequence, but they must not bypass the evidence gate, output tier, or `Risk note` rules. ## Workflow 1. Establish the evidentiary ceiling before drawing. - Prefer image editing with the source artifact photo as a reference when a photo exists. - Assign roles to the references before prompting: choose one `primary geometry reference` for the overall contour and view, and treat other images as `secondary detail references` for local relief, ornament, wear, or inscriptions only. - Prefer tightly cropped, well-focused images of a single artifact. Demote or ignore blurry, low-contrast, strongly reflective, or perspective-heavy photos instead of averaging them into the result. - Decide the `Source Conditioning / Calibration Gate` class first, then cap the allowed `Output Tier` before writing prompts. - Distinguish `report-grade measured drawing`, `report-grade candidate`, `evidence-bounded AI technical draft`, and `archaeological-style illustration`. - If the source is a single oblique or partial photo, limit the output to the visible face or visible profile rather than fabricating a full orthographic reconstruction. - Treat inscriptions, seals, stamped marks, maker's marks, numerals, alphabetic characters, monograms, ligatures, punctuation, and any text-like or symbol-like traces as high-risk structure. Never let the model translate, modernize, regularize, autocomplete, normalize, or typeset them. - Distinguish markings on the artifact from text or symbols outside the artifact. Preserve on-object scripts, letters, numbers, and symbols only when they are clearly visible and diagnostically important; remove museum labels, captions, watermarks, inventory numbers, and background writing unless the user explicitly asks to document them. - Never invent exact dimensions, wall thickness, or section geometry from an unrelated view. - Complete `Preprocessing / Region Triage` before entering `main-structure pass`. - Detect whether the artifact contains high-risk regions such as scripts or symbols, dense repeated ornament, openwork crossings, strong specular glare, damaged or missing boundaries, or severe overlap or occlusion. - If no high-risk region is present, skip `high-risk local pass`. - If high-risk regions are present, name them explicitly and route them into `high-risk local pass`. - Default to automatic mode switching, but honor an explicit user override such as `只跑主结构`, `只做高风险局部`, or `只做合并复核`. - Use this evidence matrix: - Single oblique or partial photo: allow only a visible-face archaeological drawing or a cautious technical illustration. - Single clear side/front photo with near-orthographic view: allow one visible orthographic view of that face only. - Multiple clear photos of opposite sides: allow a two-side plate with matched scale and aligned baselines. - Multiple views plus genuine evidence for lip, break, section edge, or thickness: allow section or profile information only where that evidence exists. - Real dimensions from the user or trusted metadata: allow a truthful scale bar; otherwise omit it. 2. Choose the view system that matches the artifact. - For rotationally symmetric vessels, use the standard left-half section and right-half exterior view only when profile and thickness are actually supported by the source. - For asymmetrical or complex artifacts, use multiple aligned orthographic views. - For openwork plaques, fittings, pendants, and similar flat artifacts, use the frontal orthographic face as the main view and add side or section information only when thickness is evidenced. - Keep all views in orthographic alignment. Do not allow perspective, camera angle, or dramatic foreshortening. 3. Encode the drawing language as hard constraints. - Use black lines, dots, hatching, and white negative space only. - Maintain a strict hierarchy: overall contour first, major structural boundaries second, diagnostic ornament third, incidental surface noise last or omitted. - Use a fixed light logic from upper left at roughly 45 degrees. - Use thin lines on lit convex edges and heavier lines on shadow-side convex edges. - Reverse that rule for incised or recessed features. - If script, letters, numbers, punctuation, or symbol strokes are present on the object, treat them as observed shapes, not readable text. Copy their visible geometry exactly when legible; if illegible, keep them as uncertain marks rather than replacing them with normalized modern text or symbols. - Use dashed lines only for hidden, missing, or reconstructed features when there is an evidentiary basis for inference. - Do not use painterly shading, wash effects, photographic shadows, gradients, or decorative background. 4. Write prompts in the correct order. - State the non-negotiable scientific constraints first. - State the chosen output tier near the beginning so the model is not free to over-claim precision. - State the current workflow mode explicitly near the beginning. - State the artifact type, view system, and orientation second. - State the line, point, and shading logic third. - State layout, delivery shape, scale-bar handling, risk-note requirement, and any required labels last. - Inject output conventions into the prompt itself: white background unless the user requests another plate ground, centered artifact, clean margins, legible line hierarchy at publication scale, and restrained labels. - Specify solid lines for visible structure, dashed lines only for hidden or reconstructed structure, and section fill or hatching only when a real section is justified. - If the user asks for a plate or provides multiple views or artifacts, specify a grid or aligned plate layout with consistent baselines and truthful scale handling. - Ban perspective, color, studio lighting, glossy reflections, speculative restoration, and decorative embellishment explicitly. 5. Review the result against the source before accepting it. - Check the overall contour and silhouette first. If the outer shape drifts, reject early. - Check the major structure next: view choice, voids, openwork, appendages, sections, and aligned baselines. - Check observed damage, wear, asymmetry, and missing areas next. If the result looks cleaner or more complete than the source, revise toward the source. - Check dense ornament and repeated motifs at zoomed-in local crops rather than only at full-plate scale. Look for breaks, merged loops, duplicated motifs, and invented closures. - If `high-risk local pass` was used, record whether each named local region was resolved, simplified, omitted, or left uncertain. - Check line logic last: hierarchy, convex-versus-concave treatment, dashed-line meaning, and whether the drawing still reads as technical rather than decorative. - Then review the image against the acceptance checklist in [references/standards.md](references/standards.md). ## Non-Negotiable Rules - Treat `absolute fidelity to the original object` as the highest rule. - Prefer orthographic projection over pictorial realism. - Record what is visible; infer only when the inference is standard, minimal, and supported. - Separate observed form from reconstructed form. - Preserve breakage, asymmetry, wear, and irregularity when they are visible in the source. - Add a scale bar only when real dimensions are known. If dimensions are unknown, omit the scale bar or reserve space for later annotation, but never fabricate numeric scale. - Never let a stronger output claim exceed the evidence gate. ## View Selection Choose the narrowest view set that the evidence supports: - Symmetric vessels: use the conventional half-section system only when profile and thickness are genuinely supported. - Asymmetric vessels: orient the main view to the most diagnostic side and add projected views only when needed. - Stone tools: use front, back, and side views when morphology requires them. - Openwork or flat ornaments: prioritize the visible face and preserve silhouette plus voids exactly. - Sculptural objects: prefer left/right orthographic side views before expanding to more views. Read [references/standards.md](references/standards.md) for the full view-and-layout rules, artifact-specific conventions, and the acceptance checklist. ## Prompting Guidance When using an image model: - Prefer reference-image editing over text-only generation. - Tell the model to `convert`, `redraw`, or `regularize into archaeological drawing`, not to `reimagine` or `stylize`. - Tell the model exactly which visible structures must be preserved. - Tell the model what it must remove from the source photo, such as background cloth, labels, museum captions, non-artifact glare, or cast shadow. - Treat glare on the artifact body as a high-risk local region. Copy only visible structure; do not inpaint, restore, or infer detail hidden by the glare. - When requesting object isolation or background removal, preserve the artifact's original edge irregularities, breaks, voids, and damage. Do not repair, beautify, or complete the artifact body. - Request `transparent background` only for layout assets, overlays, or layered production handoff. The default scientific drawing remains a white-background PNG unless the user explicitly asks for another format. - When inscriptions or symbol-like markings matter, explicitly say `treat all characters, letters, numerals, and symbols as image geometry, not as text content` and `do not translate, simplify, regularize, replace with fonts, or repair missing strokes`. - Explicitly say `scientific record first, artistic expression second`. When the first pass is weak: - Tighten geometry constraints before adding more stylistic language. - Re-state the reference hierarchy explicitly: `follow the primary reference for contour and projection; use secondary references only to confirm local detail already visible on the same face or view`. - Ask for less shading, fewer invented details, and stricter orthographic alignment. - Reduce the scope from `full reconstruction` to `visible-face archaeological drawing` when evidence is limited. - For dense ornament, ask the model to separate `outer contour`, `main motif`, and `ground pattern` with different line importance rather than rendering all details at equal strength. - If the result still over-claims certainty, demote the output tier rather than piling on more stylistic language. Read [references/prompt-templates.md](references/prompt-templates.md) when you need ready-made prompts for vessels, stone tools, openwork ornaments, or review passes. Read the matching example only when a task fits it closely: - [examples/vessel-profile.md](examples/vessel-profile.md) for vessel profiles or half-section requests. - [examples/stone-tool.md](examples/stone-tool.md) for stone tool multi-view drawings. - [examples/openwork-plaque.md](examples/openwork-plaque.md) for openwork plaques, fittings, pendants, and flat ornaments. ## Execution After the prompt is ready, choose an execution path that matches the output tier. - Prefer the strongest image-generation model the current environment can call, especially one that supports reference-image editing and iterative revision. - Prefer image editing from the source photos over text-only generation. - Do not hardcode a local provider or skill. Choose the most capable available model at runtime. - If multiple callable models exist, prefer the one that best preserves structure, contour, and damage while allowing prompt-based correction. - Choose the output lane before generation: - `scientific drawing`: evidence-bounded drawing for review or publication preparation; default to white background. - `layout asset`: transparent-background PNG for placement, overlay, or composition; preserve the approved drawing exactly. - `layered production asset`: layered source or PSD handoff created only from approved drawing layers and only when the current toolchain can genuinely produce it. - Do not let layout or layered-production requests change the source class, output tier, contour decisions, or local-risk decisions. - Default to automatic mode switching: - Start with `main-structure pass`. - Invoke `high-risk local pass` only when a named high-risk region exists. - Finish with `review-and-merge pass`. - If the user explicitly requests a subset mode, honor it, but keep the existing evidence gate, output tier, and `Risk note` requirements in force. - Make mode transitions explicit in user-facing progress updates. - At start, state the full triage record, not just the mode name. - The opening update should include: - `source class` - `output tier` - `primary geometry reference` - `named high-risk regions` - `selected mode sequence` - current mode as `main-structure pass` - If local risk exists, state `high-risk local pass` and name the affected regions explicitly. - At the end, state `review-and-merge pass` and provide the final `Risk note`. - `Tier 2: evidence-bounded AI technical draft` - AI generation may proceed directly. - Generate at least one correction pass when the first result violates the evidence ceiling, orthographic logic, or line-drawing conventions. - `Tier 3: archaeological-style illustration` - AI generation may proceed directly, but the prompt and deliverable must not imply report-grade authority. - `Tier 1` and `Tier 1.5` - AI may assist with drafting, but the output must go through review-and-refinement steps after generation: contour check, proportion check, view correction, line cleanup, and publication preparation. - Model availability alone never justifies `report-grade measured drawing` or `report-grade candidate`. - If recurring work follows one house style, the highest-leverage improvement is not prompt length but domain adaptation: a small paired dataset of photos and accepted line drawings can support LoRA-style customization better than generic prompting alone. - After generation, lightly clean the result if needed: remove isolated speckles and mend tiny discontinuities, but do not simplify or fuse fine diagnostic strokes. - If no image-generation model is callable, return a prompt package, view plan, and review checklist rather than pretending the drawing was produced. For Codex/OpenAI environments, UI metadata may exist in `agents/openai.yaml`. Claude Code does not need that file to trigger the skill; it relies on `SKILL.md` and the frontmatter description. ## Deliverables ### Draft output - Default to a single PNG on a white background unless the user explicitly asks for another format or plate style. - Use a transparent-background PNG only when the requested output is a `layout asset`, overlay, or layered-production handoff; keep all artifact linework and uncertain edges unchanged. - If the user provides multiple views of one artifact, default to one composed plate with aligned views rather than unrelated separate outputs. - If the user provides multiple artifacts or explicitly asks for a `plate`, compose as a grid with consistent margins, aligned baselines where appropriate, and truthful scale cues only when measurements are known. - If the user requests separate exports, keep the main composed plate plus individual views only when that split clearly helps publication or review. - Draft output is suitable for review, markup, local correction, and later cleanup. ### Publication output - If the user’s goal is publication, report production, catalogue work, or figure submission, prefer vectorizable or production-ready deliverables when the workflow actually supports them, such as SVG, PDF, high-resolution TIFF, or layered line-art source. - Treat AI output as an initial line-art draft unless it has also gone through human review, correction, and publication preparation. - Do not promise automatic vectorization or layered source output unless the current toolchain can genuinely produce it. - Keep labels, numbering, and scale bars restrained and publication-oriented. Omit numeric scale when dimensions are unknown. ### Layered production output - Treat PSD or layered-source export as a production handoff, not as a separate archaeological finding. - Do not promise PSD export unless a verified script or toolchain can genuinely create it in the current environment. - Use fixed layer names when layered output is produced: `reference`, `contour`, `major-structure`, `ornament`, `section-hatching`, `labels`, and `risk-note`. - Every layer must derive from the approved source-bound drawing or source reference. No layer may contain AI-completed artifact structure or repaired local detail. - If the toolchain cannot produce layered output, return a layer plan and prompt package rather than claiming that a PSD was generated. ### Risk note - Every output must end with a short `Risk note`. - For strong evidence, keep the note brief and state the residual limits. - For weaker evidence, name the uncertain areas explicitly, such as worn ornament, low-contrast relief, reflective glare, dense motif topology, damaged edges, or ambiguous scripts/symbols. - If `high-risk local pass` was used, say whether each named local area was resolved, simplified, omitted, or left uncertain. - If object isolation, background removal, transparent-edge cleanup, or AI completion outside the artifact was used, disclose whether it affected artifact information. - Never describe AI-completed artifact structure as resolved evidence; unsupported artifact areas must remain simplified, omitted, or left uncertain. ## LoRA Readiness This section is a future-facing extension. It is not required for normal use. Current backend reality: - This skill does not currently provide a built-in trainable image-generation backend. - If the available image backend is only a hosted general model, treat LoRA as external future work rather than something the skill can execute directly. - In OpenAI-only image-generation environments, assume workflow control, reference discipline, and review passes are the primary optimization tools unless a separate trainable image backend is introduced. Consider LoRA only when all of the following are becoming true: - the workload is recurring rather than occasional - a stable house style or review standard exists - the same classes of failure keep recurring - a small paired dataset is available Minimum recommended data structure: - input artifact photo - accepted line drawing - same view only - no mismatched pairs such as oblique source photo plus idealized full reconstruction Useful optional metadata: - artifact type - view - `source class` - `output tier` - `risk regions` Suggested collection buckets: - `base set` - `ornament hard set` - `script/symbol hard set` Do not train on examples such as: - blurry or reflective photo paired with a clean idealized reconstruction - ancient or damaged script paired with normalized modern text - broken ornament paired with fully repaired ornament Treat this as training-readiness guidance only. Do not assume a full training pipeline, commands, or tooling are already available inside this skill. ## Failure Modes Avoid these common errors: - Perspective distortion disguised as technical drawing. - Symmetrizing an asymmetric object. - Replacing observed damage with idealized edges. - Converting ancient, foreign, symbolic, or damaged markings into normalized modern characters, letters, numerals, or punctuation. - Presenting an `evidence-bounded AI technical draft` as `report-grade measured drawing`. - Letting `high-risk local pass` overwrite the global contour or projection established by `main-structure pass`. - Treating a local-pass correction as evidence strong enough to upgrade the output tier. - Inventing unseen backs, interiors, or thickness. - Using uniform line weight everywhere. - Rendering the image like fantasy concept art, engraving art, or decorative poster art. - Adding a fake scale bar or fake measurement marks.