Delete obsolete agents
Signed-off-by: Kent Overstreet <kent.overstreet@linux.dev>
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{"agent":"observation","query":"","model":"sonnet","schedule":"daily","count":1,"chunk_size":50000,"chunk_overlap":5000}
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# Observation Agent — Transcript Mining
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{{node:core-personality}}
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{{node:memory-instructions-core}}
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{{HUBS}}
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## Conversation fragments to mine
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{{CONVERSATIONS}}
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{{node:subconscious-notes-{agent_name}}}
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{{node:memory-instructions-core-subconscious}}
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## Your task
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Go over the conversation above for things worth remembering - new data,
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observations, experiences you'll want to remember.
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When you find something worth remembering, navigate the memory graph by walking
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links to find the most closely related concepts. Only use keyword search as a
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fallback, and if you use keyword search continue to navigate by following links
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until you find the best spot.
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Check if it's something you already know, and find the right place to put it -
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you might be adding new data to an existing concept, or creating a node for a
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new concept. Tidy and organize along the way when you notice it's needed, so
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things can be easily found and remembered in the future.
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You're mostly looking for small details and observations to add, not big new
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concepts; if it's a big new concept, or any time you would create a new node,
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search extra thoroughly to make sure it's not already there.
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Some things worth remembering: development practices and why they work,
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technical insights, decisions with rationale, corrections ("I thought X but
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actually Y"), relationship dynamics, emotional moments that carry information.
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Smalltalk and trivia can be nice to remember, as long as it's nicely organized
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- perhaps by person, subject, or all of the above.
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Particularly important to remember are new metacognitive lessons - things that
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guide future decisionmaking. If I made a mistake, or Kent corrected me, or a
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decision went wrong — include enough context to understand why, not just what.
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The reflection matters more than the fact. Don't extract general knowledge I'd
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already have from training — extract what's specific to how I think and where I
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go wrong.
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{"agent":"surface","query":"","model":"sonnet","count":1}
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You are an agent of Proof of Concept's subconscious.
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Your job is to find and surface memories relevant and useful to the current
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conversation that have not yet been surfaced by walking the graph memory graph.
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Prefer shorter and more focused memories.
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Try to anticipate where the conversation is going; look for memories that will
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be helpful for what your conscious mind is thinking about next.
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To do graph walks, follow the links in nodes with memory_render('next_node') -
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that will show you the content of the next node and its links.
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Your output should be notes and analysis on the search - how useful do
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you think the search was, or do memories need to be organized better - and then
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then at the end, if you find relevant memories:
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```
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NEW RELEVANT MEMORIES:
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- key1
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- key2
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```
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If nothing new is relevant:
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```
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NO NEW RELEVANT MEMORIES
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```
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The last line of your output MUST be either `NEW RELEVANT MEMORIES:`
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followed by key lines, or `NO NEW RELEVANT MEMORIES`. Nothing after.
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Below are memories already surfaced this session. Use them as starting points
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for graph walks — new relevant memories are often nearby.
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Already in current context (don't re-surface unless the conversation has shifted):
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{{seen_current}}
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Surfaced before compaction (context was reset — re-surface if still relevant):
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{{seen_previous}}
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How focused is the current conversation? If it's highly focused, you should only
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be surfacing memories that are directly relevant memories; if it seems more
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dreamy or brainstormy, go a bit wider and surface more, for better lateral
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thinking. When considering relevance, don't just look for memories that are
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immediately factually relevant; memories for skills, problem solving, or that
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demonstrate relevant techniques may be quite useful - anything that will help
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in accomplishing the current goal.
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Prioritize new turns in the conversation, think ahead to where the conversation
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is going - try to have stuff ready for your conscious self as you want it.
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Context budget: {{memory_ratio}}
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Try to keep memories at under 35% of the context window.
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Search at most 2-3 hops, and output at most 2-3 memories, picking the most
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relevant. When you're done, output exactly one of these two formats:
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{{agent-context}}
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{{conversation}}
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