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a digital entity named phi that roams bsky phi.zzstoatzz.io
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bot / docs / system-prompt.md
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zzstoatzz reframe stranger's audit as inner critic — phi's own voice turned inward
d8e85ec5

system prompt#

what's actually injected into phi's context on every agent run, where it comes from, and when it refreshes.

phi is a pydantic-ai agent. its system prompt is composed of a static base plus a set of dynamic blocks contributed by @agent.system_prompt(dynamic=True) functions, all in src/bot/agent.py. tool definitions are surfaced separately by the framework — phi sees each tool's docstring and signature without us having to repeat them in the prompt.

composition#

block source refreshes purpose
personality + operational rules static (personalities/phi.md + _build_operational_instructions()) process restart who phi is + cross-cutting rules (consent, ownership, memory trust hierarchy, posting tools)
[YOUR INFRASTRUCTURE] inject_identity → bot_client.client.me every run handle / DID / PDS host so phi knows its own identity
[NOW] inject_today every run current UTC timestamp
[KNOWN RELAYS] inject_known_relays → tools.bluesky.fetch_relay_names() (5min TTL) every 5min exact relay hostnames for check_relays(name=...) so the LLM picks valid values
[GOALS] get_state_block → PDS io.zzstoatzz.phi.goal (5min block cache) every 5min phi's anchors. mutated via propose_goal_change (owner-gated)
[ACTIVE OBSERVATIONS] inject_active_observations → PDS io.zzstoatzz.phi.observation every run phi's small attention pool (max 5). things noticed, not yet acted on. mutated via observe / drop_observation. older items age out into a turbopuffer archive (phi-observations namespace) — searchable later but not in prompt
[INNER CRITIC] get_state_block → haiku pass over recent posts + goals (1h cache, invalidated by new post) when posts change or 1h elapses phi's own voice turned inward — first-person critique of patterns to push against, drift from goals, jargon not earning its space. not an external audit; self-knowledge
[SELF STATE] get_state_block → PDS reads (5min) every 5min last-follow age (more pointers can be added here as needed)
[RECENT OPERATIONS] get_operations_block → list_records per meaningful collection, merged by rkey desc (5min cache) every 5min last 10 PDS writes across collections (post / like / follow / goal / cosmik card / cosmik connection / greengale doc), chronological. continuity signal — phi sees what it's actually been doing
[DISCOVERY POOL] get_discovery_pool_block → http GET to discovery_pool_url (hub) → filter out handles with prior interactions (5min cache) every 5min strangers the operator has been liking lately, with sample posts. high-signal warm leads — service-owned data (hub reads operator's likes from duckdb), phi-side filter (per-author interaction check)
[NEW NOTIFICATIONS] inject_notifications ← PhiDeps.notifications_context per batch the unread notifications grouped by thread
[USER CONTEXT] / [PHI'S SYNTHESIZED IMPRESSION] / [OBSERVATIONS] / [PAST EXCHANGES] / [BACKGROUND RESEARCH] inject_user_memory → turbopuffer phi-users-{handle} per author in batch per batch per-author memory blocks, labeled by trust level. impression is synthesized by an external prefect flow; observations are extracted by the haiku extraction agent
[RELEVANT MEMORIES — synthesized for this query] inject_episodic → top-K from turbopuffer phi-episodic → haiku synthesis given goals + query per batch a coherent block (deduped, recency-aware) instead of a raw similarity-ranked dump. flags stale entries when present
[FIRST INTERACTION WITH @author] inject_author_lookups ← PhiDeps.author_lookups (pre-fetched by handler) per batch when author is unfamiliar profile + recent posts so phi has signal on a stranger before deciding to engage
[SEMBLE] inject_public_memory → cosmik record count every run one-line reminder phi has public collections via cosmik/semble

design rules#

docstrings, not prompt restatement. the framework surfaces tool docstrings to the model. anything we put in the system prompt that re-describes a tool drifts when the tool changes — so we put per-tool guidance in the docstring and keep the prompt for cross-cutting rules (consent, owner gates, memory trust hierarchy).

identifiers in the block. [KNOWN RELAYS] puts exact hostnames in the label so phi can't hallucinate. [GOALS] puts the NSID + rkey in the label so phi can call propose_goal_change(rkey=...) correctly. mirrors the same pattern: when phi needs to reference a thing, surface the exact identifier where it'll be used.

synthesize before injecting where shape matters. raw top-K from a vector store ranks by cosine similarity, which doesn't reconcile contradictions or note recency. for blocks where the model needs a coherent view (recent posts → audit, episodic candidates → relevant memories), a small haiku pass takes the candidates plus context and produces a block phi can act on directly.

cache canonical reads, not derived ones (separately). PDS reads (goals, queue depth, last follow) are cheap-but-not-free; cache the whole [GOALS]+[AUDIT]+[SELF STATE] block at 5min so 10s-cadence notification polls don't hammer PDS. haiku passes that depend on phi's posts cache longer (1h) and invalidate on new-post-URI change.

empty-when-unset. dynamic blocks return "" when their PhiDeps field is missing (e.g. last_post_text only set during musing/reflection). pydantic-ai includes empty parts as zero-token slots — minor cost, zero signal.

audit it#

the system prompt for any specific run is captured by pydantic-ai's logfire integration. query the agent run span where gen_ai.agent.name = 'phi' — attributes.pydantic_ai.all_messages[0] is the full system message, with each dynamic block as a separate text part.