orcaflex-batch-manager-100-2026-01-17
Sub-skill of orcaflex-batch-manager: [1.0.0] - 2026-01-17.
Best use case
orcaflex-batch-manager-100-2026-01-17 is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of orcaflex-batch-manager: [1.0.0] - 2026-01-17.
Teams using orcaflex-batch-manager-100-2026-01-17 should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/100-2026-01-17/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How orcaflex-batch-manager-100-2026-01-17 Compares
| Feature / Agent | orcaflex-batch-manager-100-2026-01-17 | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of orcaflex-batch-manager: [1.0.0] - 2026-01-17.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# [1.0.0] - 2026-01-17 ## [1.0.0] - 2026-01-17 **Added:** - Initial release with parallel batch processing - Adaptive worker scaling based on system resources - Chunk-based processing for large batches - Progress tracking and performance metrics
Related Skills
OrcaFlex Specialist Skill
```yaml
orcaflex-reporting-fixture-proof-pattern
Build and extend fixture-backed OrcaFlex reporting proof paths in digitalmodel using stable metadata baselines, normalized HTML snapshots, and reusable reporting test helpers.
digitalmodel-orcawave-orcaflex-proof-workflows
Class-level digitalmodel OrcaWave/OrcaFlex readiness, semantic-proof, fixture-proof, and closeout workflows.
orcawave-orcaflex-readiness-audit
Audit the real readiness of digitalmodel OrcaWave/OrcaFlex spec-driven workflows by reconciling workspace-hub issues, source/tests, semantic-equivalence boundaries, and wiki synthesis gaps.
batch-syntax-repair-from-injection-errors
Detect and fix systematic syntax errors caused by line-injection scripts that split multiline constructs
batch-syntax-fix-with-regex-line-based-fallback
Fix repeated syntax errors across many files using regex, then fall back to line-based parsing when regex fails
batch-syntax-fix-regex-iteration
Iteratively fix widespread syntax errors across many files using regex refinement when initial patterns fail
batch-syntax-fix-pattern
Identify and repair cascading import/syntax errors across multiple files using regex-based line-scanning and verification
batch-regex-fix-import-syntax
Detect and fix mid-import blank-line syntax breaks across multiple files using line-based regex
digitalmodel-orcawave-orcaflex-workflow
Current-state workflow for navigating and extending digitalmodel OrcaWave/OrcaFlex capabilities across code, tests, issues, queue tooling, and licensed-machine boundaries.
orcawave-orcaflex-semantic-proof-wave-closeout
Close out an OrcaWave/OrcaFlex semantic-proof wave after a PR merges, split unrelated CI blockers, and seed the next semantic-proof issue wave without duplicating existing issues.
closure-first-overnight-batch
Run a high-leverage overnight batch by clearing stale-open approved issues first, converting shared blockers into tracked issues, and reserving only one lane for true implementation.