Leo Kim
e7738832c2
Status-line's context_pct segment was computing tokens via calculatePromptTokens(lastAssistantMessage.usage), which sums input + cacheRead + cacheWrite from the Anthropic API usage object. The /context slash command is computed by computeContextBreakdown, an offline estimate over the live session state (systemPrompt + tools + skills + messages). Both numbers are correct under their own definition, but they can diverge by 2x+ on the same session when a turn rotates cache tiers (e.g. 5m → 1h ephemeral re-cache) and cache_creation_input_tokens spikes. Users read the two surfaces as one consistent dashboard and treat the mismatch as a bug. Repro: same session at the same moment reports 212K (21.2%) in /context and 44.2%/1M in the status line — ~230K gap driven by per-turn cache_creation on a system-prompt boundary. This change makes status-line use the same computeContextBreakdown source as /context so both surfaces stay consistent. The breakdown result is cached with a 2s TTL inside the component so the per-frame status-line render does not re-walk every message via estimateMessagesTokens on long sessions. The Anthropic API per-turn prompt size remains observable via existing token_in / cache_read / cache_write / token_total segments.
@oh-my-pi/pi-coding-agent
Core implementation package for the omp coding agent in the oh-my-pi monorepo.
For installation, setup, provider configuration, model roles, slash commands, and full CLI reference, see:
Package-specific references:
- CHANGELOG
- MCP configuration guide
- MCP runtime lifecycle
- MCP server/tool authoring
- DEVELOPMENT
- RenderMermaid guide
Memory backends
The agent supports three mutually-exclusive memory backends, selected via the memory.backend setting (Settings → Memory tab, or ~/.omp/config.yml):
off(default) — no memory subsystem runs.local— existing rollout-summarisation pipeline; writesmemory_summary.mdand consolidated artifacts under the agent dir.hindsight— talks to a Hindsight server (Cloud or self-hosted Docker), retains transcripts every Nth user turn, recalls memories on the first turn of a session, and exposesretain,recall, andreflect.
Hindsight quickstart
- Run a Hindsight server (Cloud or
docker run -p 8888:8888 ghcr.io/vectorize-io/hindsight:latest). - Set
memory.backend = "hindsight"andhindsight.apiUrl = "http://localhost:8888"(or your Cloud URL). - Optional environment overrides (env wins over settings):
HINDSIGHT_API_URL,HINDSIGHT_API_TOKEN— connectionHINDSIGHT_BANK_ID,HINDSIGHT_DYNAMIC_BANK_ID,HINDSIGHT_AGENT_NAME— bank addressingHINDSIGHT_AUTO_RECALL,HINDSIGHT_AUTO_RETAIN,HINDSIGHT_RETAIN_MODE— lifecycleHINDSIGHT_RECALL_BUDGET,HINDSIGHT_RECALL_MAX_TOKENS— recall sizingHINDSIGHT_BANK_MISSION,HINDSIGHT_DEBUG
Switching backends mid-session is honoured on the next system-prompt rebuild and the next /memory slash command. Existing users with memories.enabled = true|false are migrated to memory.backend = "local"|"off" exactly once on first launch.