skills/magnus919_agent-skills
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Code Issues Packages Projects Releases Wiki Activity
404 Commits 11 Branches 10 Tags
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Commit Graph
5 Commits
Author SHA1 Message Date
Magnus Hedemark a5f7e74972 fix: resolve skill audit findings 2026-07-11 09:24:58 -04:00
Magnus Hedemark 738ec715e7 Add human-focused README.md to every skill and bundle directory 
Each README is written for a human audience, explaining:
- What the skill does (not what format it follows)
- What benefit the user gets from installing it
- Quick setup and usage patterns
- When to load/trigger the skill
- What scripts, references, and templates it ships

data-scientist already had a README — left unchanged.

48 READMEs added across all skill and bundle directories.
 2026-07-09 22:30:12 -04:00
Magnus Hedemark e3bd060de0 fix: SkillOpt Epoch 2 — langgraph decision intelligence 
Epoch 2 edits (3/3 accepted, 3/3 validation passed):
- ADD 'Start from template' column to Pattern Selection Guide
- ADD 'Choosing Your Starting Point' table (scaffold vs template vs reference)
- ADD concrete template guidance to Quick Start next-steps

Version: 1.0.1 → 1.0.2
 2026-07-08 15:17:25 -04:00
Magnus Hedemark 2731a3a48f fix: SkillOpt Epoch 1 — langgraph prominence and discoverability 
Epoch 1 edits (4/4 accepted, 3/3 validation tasks passed):
- ADD Quick Start section with pip install + hello-world + next-steps
- MOVE 6 design principles from architecture.md into SKILL.md as hard-gate blockquote
- ADD 3 template rows to Reference Files table
- ADD install dependencies blockquote at top

Version: 1.0.0 → 1.0.1
 2026-07-08 15:08:03 -04:00
Magnus Hedemark 4a73657522 feat: add langgraph expert skill — multi-agent patterns, scaffolds, evals, and production guidance 
Comprehensive LangGraph skill covering:
- Core architecture: Graph API, Functional API, state management, agent loops
- Three multi-agent patterns: supervisor (~94% accuracy), swarm (~40% fewer LLM calls),
  hierarchical teams (subgraphs with nested state)
- Persistence: checkpointers vs stores, per-invocation/per-thread/stateless modes
- Production: Agent Server deployment, LangSmith observability, 8 failure modes
- Evals: routing accuracy, resolution coverage, LLM-as-judge methodology
- Troubleshooting: symptom→cause→fix tables per pattern
- 3 Python scripts: supervisor scaffold, swarm scaffold, eval generator
- 3 runnable templates: supervisor, swarm, subgraph composition

Ships 8 reference files, 3 scripts, and 3 templates.
 2026-07-08 14:54:53 -04:00