Skill Writer V2

Skill Writer

Overview

This public intake copy packages plugins/antigravity-awesome-skills/skills/skill-writer from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

Skill Writer Use this as the single canonical workflow for skill creation and improvement. Primary success condition: maximize high-value input coverage before authoring so the resulting skill has minimal blind spots. Load only the path(s) required for the task: | Task | Read | |------|------| | Set skill class and required dimensions | references/mode-selection.md | | Apply writing constraints for depth vs concision | references/design-principles.md | | Select structure pattern for this skill | references/skill-patterns.md | | Select workflow orchestration pattern for process-heavy skills | references/workflow-patterns.md | | Select output format pattern for deterministic quality | references/output-patterns.md | | Choose workflow path and required outputs | references/mode-selection.md | | Load representative synthesis examples by skill type | references/examples/*.md | | Synthesize external/local sources with depth gates | references/synthesis-path.md | | Author or update SKILL.md and supporting files | references/authoring-path.md | | Optimize skill description and trigger precision | references/description-optimization.md | | Iterate using positive/negative/fix examples | references/iteration-path.md | | Evaluate behavior and compare baseline vs with-skill (opt-in quantitative) | references/evaluation-path.md | | Register and validate skill changes | references/registration-validation.md |

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Output format, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• Collect and score relevant sources with provenance.
• Apply trust and safety rules when ingesting external content.
• Produce source-backed decisions and coverage/gap status.
• Load one or more profiles from references/examples/*.md when the skill is hybrid.
• Enforce baseline source pack for skill-authoring workflows.
• Enforce depth gates before moving to authoring.

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Resolve target skill path and intended operation (create, update, synthesize, iterate).
2. Read references/mode-selection.md and select the required path(s).
3. Classify the skill (workflow-process, integration-documentation, security-review, skill-authoring, generic).
4. Ask one direct question if class or depth requirements are ambiguous; otherwise state explicit assumptions.
5. Write or update SKILL.md in imperative voice with trigger-rich description.
6. Create focused reference files and scripts only when justified.
7. Follow references/skill-patterns.md, references/workflow-patterns.md, and

Imported Workflow Notes

Imported: Step 1: Resolve target and path

1. Resolve target skill path and intended operation (create, update, synthesize, iterate).
2. Read references/mode-selection.md and select the required path(s).
3. Classify the skill (workflow-process, integration-documentation, security-review, skill-authoring, generic).
4. Ask one direct question if class or depth requirements are ambiguous; otherwise state explicit assumptions.

Imported: Step 4: Author or update skill artifacts

Read references/authoring-path.md.

1. Write or update SKILL.md in imperative voice with trigger-rich description.
2. Create focused reference files and scripts only when justified.
3. Follow references/skill-patterns.md, references/workflow-patterns.md, and references/output-patterns.md for structure and output determinism.
4. For authoring/generator skills, include transformed examples in references:
   • happy-path
   • secure/robust variant
   • anti-pattern + corrected version

Imported: Step 5: Optimize description quality

Read references/description-optimization.md.

1. Validate should-trigger and should-not-trigger query sets.
2. Reduce false positives and false negatives with targeted description edits.
3. Keep trigger language generic across Codex and Claude.

Imported: Step 6: Evaluate outcomes

Read references/evaluation-path.md.

1. Run a lightweight qualitative check by default (recommended).
2. For integration/documentation and skill-authoring skills, include the concise depth rubric from references/evaluation-path.md.
3. Run deeper eval playbook and quantitative baseline-vs-with-skill only when requested or risk warrants it.
4. Record outcomes and unresolved risks.

Imported: Step 7: Register and validate

Read references/registration-validation.md.

1. Apply repository registration steps.
2. Run quick validation with strict depth gates.
3. Reject shallow outputs that fail depth gates or required artifact checks.

Imported: Output format

Return:

1. Summary
2. Changes Made
3. Validation Results
4. Open Gaps

Examples

Example 1: Ask for the upstream workflow directly

Use @skill-writer-v2 to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @skill-writer-v2 against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @skill-writer-v2 for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @skill-writer-v2 using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
• Treat generated examples as scaffolding; adapt them to the concrete task before execution.
• Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills/skills/skill-writer, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @production-audit-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @production-scheduling-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @quality-nonconformance-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @react-best-practices-v3 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

• authoring-path.md
• description-optimization.md
• design-principles.md
• evaluation-path.md
• authoring-path.md
• description-optimization.md

Imported Reference Notes

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.