operationalize

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Distill repeated, evidence-backed expertise into a proposed skill, check, reference, or workflow artifact. Triggers: "operationalize this", "turn this expertise into a reusable capability".

AI & Automation 414 stars 40 forks Updated today Apache-2.0

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Skill Content

# Operationalize Turn repeated, cited expertise into a proposal for a reusable artifact. 1. Require cited evidence for the expertise: real occurrences or an explicit authoritative source, subject to the three-instance floor below when the proposal abstracts a rule. 2. State the triggering situation, desired behavior, inputs, outputs, negative examples, and evidence. 3. Choose the smallest fitting shape: reference, skill, deterministic check, or caller-owned workflow. 4. Search existing capabilities and prefer extension over duplication. 5. Provide an activation example, holdout/negative example, owner, and rollback or deletion condition. 6. Return the proposal to the caller or an authoring specialist. ## Three-instance floor A rule needs three real occurrences before it may be abstracted. Count only occurrences that actually happened and can be cited — sessions, diffs, verdicts, or artifacts that resolve in this repository — not hypothetical cases or restatements of one event. With one or two occurrences, propose a quote-anchored reference note instead and stop short of a rule. An explicit authoritative source may substitute for occurrences only when the proposal transcribes that source rather than generalizing beyond it. The named failure mode is premature abstraction: a rule minted from a single vivid incident that encodes the incident's accidents as policy. ## Reapply proof Every proposed rule carries a reapply proof: a demonstration that the rule, as ...

Details

Author
boshu2
Repository
boshu2/agentops
Created
8 months ago
Last Updated
today
Language
Go
License
Apache-2.0

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