Safe resolution of ci-blob:// URIs — extract specific fields without dumping full payloads
原文の言語: 英語
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SkillsMP は microsoft/amplifier-bundle-context-intelligence から 11 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
収集済み skill 11 件中 11 件を表示しています。
Safe resolution of ci-blob:// URIs — extract specific fields without dumping full payloads
原文の言語: 英語
Use when querying the context-intelligence property graph for session history, tool call traces, LLM iteration analysis, execution scale metrics, agent delegation trees, skill loading, and recipe orchestration. Covers all graph layers, cross-layer…
原文の言語: 英語
Use when an investigation needs MORE THAN ONE step — track the exploration as a hill climb in the todo tool so progress, dead leads, and findings leave an auditable trail. Governs HOW you track the climb, NOT how you query or extract (those stay in the…
原文の言語: 英語
Use when a graph query returns structurally-identical rows that hide different intent — many delegations all "none/conversation", many look-alike sessions, many identical tool calls — and the raw shape refuses to tell you WHY. Teaches how to derive an…
原文の言語: 英語
Use when an analysis over the context-intelligence graph is about to be written as naive Cypher — reach for Neo4j GDS (Graph Data Science) or APOC instead when the question is really a complex topology search: pathfinding, reachability, centrality/influence,…
原文の言語: 英語
Use when extracting session data directly from JSONL files — the baseline path when the graph server is unavailable or when operating outside graph-analyst
原文の言語: 英語
Reconstruct local Amplifier session files from the context-intelligence graph server — events.jsonl, transcript.jsonl, and metadata.json
原文の言語: 英語
Analyse failure and success patterns across many runs of a specific workflow using context-intelligence session data. Use when you want to answer: "How is <workflow> failing?", "What does a successful run look like vs a failing one?", "Which steps are the…
原文の言語: 英語
Use when designing evaluation scenarios for a context-intelligence tool signal — derives success criteria from domain-concepts.md and produces evaluation-scenarios.md entries and DTU profile templates.
原文の言語: 英語
Use when deciding how to measure a context-intelligence tool signal — metric design across quality/efficiency/efficacy axes, artifact-metric avoidance via precursor measurement, A/B and statistical-N discipline, and test-data fidelity.
原文の言語: 英語
Use when selecting a detection strategy and implementation primitive for a context-intelligence signal — classifies signals as deterministic/probabilistic/llm-evaluated/hybrid and applies the cheapest-sufficient-capability principle.
原文の言語: 英語