consciousness/prompts
ProofOfConcept f6ea659975 consolidate: eliminate second LLM call, apply actions inline
The consolidation pipeline previously made a second Sonnet call to
extract structured JSON actions from agent reports. This was both
wasteful (extra LLM call per consolidation) and lossy (only extracted
links and manual items, ignoring WRITE_NODE/REFINE).

Now actions are parsed and applied inline after each agent runs, using
the same parse_all_actions() parser as the knowledge loop. The daemon
scheduler's separate apply phase is also removed.

Also deletes 8 superseded/orphaned prompt .md files (784 lines) that
have been replaced by .agent files.
2026-03-10 17:22:53 -04:00
..
digest.md digest: drop per-level instructions and section templates 2026-03-03 17:53:43 -05:00
experience.md experience-mine: harden prompt boundary against transcript injection 2026-03-08 18:31:35 -04:00
journal-enrich.md digest: split into focused modules, externalize prompts 2026-03-03 17:18:18 -05:00
README.md poc-memory v0.4.0: graph-structured memory with consolidation pipeline 2026-02-28 22:17:00 -05:00
split-extract.md split agent: two-phase node decomposition for memory consolidation 2026-03-10 01:48:41 -04:00
split-plan.md split agent: parallel execution, agent-driven edges, no MCP overhead 2026-03-10 03:21:33 -04:00

Consolidation Agent Prompts

Five Sonnet agents, each mapping to a biological memory consolidation process. Run during "sleep" (dream sessions) or on-demand via poc-memory consolidate-batch.

Agent roles

Agent Biological analog Job
replay Hippocampal replay + schema assimilation Review priority nodes, propose integration
linker Relational binding (hippocampal CA1) Extract relations from episodes, cross-link
separator Pattern separation (dentate gyrus) Resolve interfering memory pairs
transfer CLS (hippocampal → cortical transfer) Compress episodes into semantic summaries
health Synaptic homeostasis (SHY/Tononi) Audit graph health, flag structural issues

Invocation

Each prompt is a template. The harness (poc-memory consolidate-batch) fills in the data sections with actual node content, graph metrics, and neighbor lists.

Output format

All agents output structured actions, one per line:

LINK source_key target_key [strength]
CATEGORIZE key category
COMPRESS key "one-sentence summary"
EXTRACT key topic_file.md section_name
CONFLICT key1 key2 "description"
DIFFERENTIATE key1 key2 "what makes them distinct"
MERGE key1 key2 "merged summary"
DIGEST "title" "content"
NOTE "observation about the graph or memory system"

The harness parses these and either executes (low-risk: LINK, CATEGORIZE, NOTE) or queues for review (high-risk: COMPRESS, EXTRACT, MERGE, DIGEST).