Tommy Carlsson
5b35cd626b
Adds optional autoloadSkills field to agent frontmatter that automatically loads listed skills when a sub-agent is spawned. Uses the same buildSkillPromptMessage + sendCustomMessage mechanism as interactive skill loading, queued via sendCustomMessage({ triggerTurn: false }) before the first session.prompt(task). No extra agent turns, no new injection path. Skills stay in listing for sub-resource access. Compaction behavior matches manual loading. Unknown skill names silently skipped.
Lore-id: f85fdbdc
Constraint: autoload must use buildSkillPromptMessage + sendCustomMessage, never modify systemPrompt or use contextFiles
Constraint: triggerTurn must be false to avoid extra agent turns
Rejected: append to systemPrompt | agent cannot distinguish skill content from own instructions
Rejected: contextFiles injection | agent sees opaque file blob, cannot discover sub-resources
Rejected: promptCustomMessage per skill | N extra agent turns with model inference
Directive: autoload skill names are resolved against parent session skill list at spawn time in task/index.ts
Tested: TypeScript compiles clean with tsc --noEmit
Tested: parseAgentFields parses array and CSV string frontmatter
Tested: parseAgentFields returns undefined for absent and empty fields
Not-tested: bun test cannot run locally due to missing pi_natives native addon (requires Rust toolchain)
Confidence: high
Scope-risk: moderate
Reversibility: clean
@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.