| name | serval-svg-expert |
| description | Use this skill when auditing the serval-svg repository, regenerating support artifacts, interpreting internal SVG support facts, analyzing whether an SVG can render correctly with code-grounded reasoning, or planning and implementing new SVG features. |
Serval SVG Expert
Overview
This is the internal audit and maintenance skill for serval-svg.
Its job is to inspect the codebase, maintain the knowledge artifacts, explain
why support behaves the way it does, and publish the public support contract
consumed by serval-svg.
Canonical Inputs
Load these files first:
Core Responsibilities
1. Repository Audit
Use this skill when the user wants:
- a code audit of
serval-svg
- a support inventory grounded in implementation
- an explanation of parser/render/backend gaps
- refreshed SVG knowledge artifacts
The audit source of truth is:
audit-matrix.json for structured factsdeepwiki.md for engineering context- source files for verification
2. Public Contract Maintenance
This skill owns the publication flow from internal facts to external support
answers.
When support changes:
- regenerate
svg/docs/audit-matrix.json
- regenerate
svg/docs/support-matrix.json
- refresh
svg/docs/deepwiki.md
- update both skills if the support surface changed
3. SVG Compatibility Analysis
Use this skill when the user provides an SVG snippet or file and asks whether
serval-svg can render it correctly, especially if the answer needs code
reasoning.
Preferred command:
python3 svg/tools/svg_support_audit.py analyze --profile audit --svg-file path/to/input.svg --platform all
Use the public profile only when validating the published support contract:
python3 svg/tools/svg_support_audit.py analyze --svg-file path/to/input.svg --platform all
4. Feature Development Guidance
Use this skill when the user wants to add or complete SVG support, especially
for filters, masks, text, image, or backend parity work.
Always evaluate all layers:
- parser registration
- node fields and attribute parsing
- render-path integration
- backend implementation
- sample or regression coverage
- audit-matrix update
- support-matrix update
- deep wiki update
- skill update
Response Rules
- Distinguish
recognized, parsed, rendered, and platform-ready.
- Use
audit-matrix.json as the structured internal source of truth.
- Use
support-matrix.json to verify what the public skill is allowed to say.
- Use
deepwiki.md for architecture and historical caveats.
- Be explicit when a tag is parsed but not rendered.
- Be explicit when something only works on one backend.
- If you infer behavior from code rather than from a sample, say so.
Boundary
Do not use this as the first tool for a simple consumer-facing support question
if the public contract already answers it cleanly. In that case, prefer
serval-svg.
