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Showing 12 of 12 collected skills.
Retrieve the prior user and assistant conversation verbatim from the current Context Intelligence capture, or named sessions. Use when a user asks to replay, quote, review, or act on a transcript.
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…
Exact step order, wording, and the "session details" block format for the delete flows the server-data-ops agent drives — delete the current session, clean up every session from the current working directory, find-then-delete a session by description, and…
Use when local Amplifier session files are missing, broken, or incomplete — rebuilds events.jsonl, transcript.jsonl, and metadata.json from the context-intelligence graph server.
Use when asked how a workflow is failing, what separates a successful run from a failing one, which steps are the most common failure points, or what patterns recur across sessions — analyses failure/success patterns and signals across many runs using…
Use when a graph query returns structurally-identical rows hiding different intent — many delegations all "none/conversation", look-alike sessions, identical tool calls. Derives an INTERPRETIVE metric by joining a second graph layer onto the blanket shape…
Use when designing evaluation scenarios for a context-intelligence tool signal. Derives success criteria from domain-concepts.md and produces evaluation-scenarios.md entries plus DTU profile templates.
Use when deciding how to measure a context-intelligence tool signal. Covers metric design across quality/efficiency/efficacy axes, artifact-metric avoidance via precursor measurement, A/B and statistical-N discipline, and test-data fidelity.
Use when about to write naive Cypher for a graph-topology question — pathfinding, reachability, centrality/influence, community/clustering, structural similarity, or similar event paths/trajectories (with/without time) — reach for Neo4j GDS or APOC instead of…
Use when an investigation needs more than one step — track it in todo as a hill climb so progress and dead leads leave an audit trail. Governs HOW you track the climb, not how you query or extract — that stays in graph-query / session-navigation.
Use when extracting session data directly from JSONL files — the fallback when the graph server is unavailable or outside graph-analyst.
Use when selecting a detection strategy and implementation primitive for a context-intelligence signal. Classifies signals as deterministic, probabilistic, llm-evaluated, or hybrid, and applies the cheapest-sufficient-capability principle.
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