microsoft/amplifier-bundle-context-intelligence

blob-reading

Safe resolution of ci-blob:// URIs — extract specific fields without dumping full payloads

context-intelligence-graph-query

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…

context-intelligence-hill-climbing

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…

context-intelligence-derived-metrics

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…

context-intelligence-gds

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,…

context-intelligence-session-navigation

Use when extracting session data directly from JSONL files — the baseline path when the graph server is unavailable or when operating outside graph-analyst

context-intelligence-session-reconstruction

Reconstruct local Amplifier session files from the context-intelligence graph server — events.jsonl, transcript.jsonl, and metadata.json

workflow-pattern-analysis

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…

context-intelligence-eval-design

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.

context-intelligence-evaluation-methodology

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.

context-intelligence-tool-design

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.