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Agent Ops Skills

Validate skills

Reusable skills for evidence-backed research, approval-gated operations, structured records, and durable agent handoffs.

These packages extract the operating patterns behind real agent-assisted products without publishing their private prompts, source code, credentials, or user data.

Skills

Skill Use it when Produces
evidence-backed-research Claims need traceable sources and honest confidence labels A structured evidence packet with conflicts and gaps
human-approved-publishing An agent may prepare content but a person must authorize publication A reviewed draft and explicit publication decision
schema-validated-records Research must become machine-readable without losing provenance A schema-valid record plus validation report
context-packet-builder A fresh agent needs the smallest useful view of file-backed state A compact, prioritized handoff packet

Operating model

flowchart LR
    A["Source material"] --> B["Bounded skill"]
    B --> C["Structured artifact"]
    C --> D["Deterministic validation"]
    D --> E["Human decision"]
    E --> F["External action, if approved"]
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The common design principle is simple: agents may gather, transform, check, and recommend. External actions remain visible and approval-gated.

Install

Copy a skill directory into the skill location used by your agent environment, or point your agent at its SKILL.md. Each skill is self-contained and links only to files inside its own directory.

The instruction format is compatible with the common SKILL.md convention. The included scripts are tested with Python 3.11+.

Validate

python3 scripts/validate_skills.py
python3 -m unittest discover -s tests
python3 skills/context-packet-builder/scripts/build_context_packet.py \
  --input skills/context-packet-builder/examples/input/project-state.json \
  --output /tmp/context-packet.md

CI runs the same checks on every pull request.

Design boundaries

  • Synthetic examples only.
  • No private URLs, personal identifiers, customer records, or environment-specific paths.
  • No claim that a model verified something unless a deterministic check or human review did.
  • No external send, submit, merge, or publish action without an explicit approval step.
  • Small core instructions; supporting examples live beside the skill.

Origin

These skills are sanitized extractions from patterns used in TheTechStack and a file-backed agent operations system. The implementations here are standalone public artifacts, not copies of either private system.

License

MIT

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Reusable agent skills for evidence-backed research, approval-gated publishing, schema-validated records, and durable context handoffs.

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