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It learns when to act, when to propose, when to ask, and when to explore — calibrated to your actual preferences, not a static policy you had to","maintainers":[{"name":"akalsey","email":"adam@kalsey.com"}],"readme":"# Sapience Suite for OpenClaw\n\nThe Sapience Suite transforms OpenClaw from a reactive assistant into a proactive agent with genuine autonomy. It learns when to act, when to propose, when to ask, and when to explore — calibrated to your actual preferences, not a static policy you had to configure upfront.\n\nThe suite has four plugins that each work independently and compose into a whole:\n\n| Plugin | Does |\n|--------|------|\n| `sapience-thinking` | Periodic thinking passes; generates observations and proposals |\n| `sapience` *(this plugin)* | Routes proposals through autonomy tiers; calibrates to your preferences; delivers weekly digest |\n| `sapience-feedback` | Captures corrections and confirmations from chat; recalibrates autonomy profile |\n| `sapience-goals` | Accepts fuzzy long-running goals; decomposes them; tracks progress; weekly status |\n\n## How it works\n\n`sapience-thinking` runs a thinking pass every 15 minutes and writes proposals to `proposals.jsonl`. `sapience` reads that sidecar, routes each proposal through an autonomy decision function, and delivers it to your main session at the right level:\n\n- **Act** — high-confidence, reversible, low-blast-radius → executed autonomously, result reported\n- **Propose** — worth doing, needs your approval → surfaces it for a yes/no\n- **Ask** — agent can do it but needs one piece of information → asks exactly what's needed\n- **Explore** — the problem is real but the right path is unclear → presents 2–3 options with tradeoffs\n- **Learning** — new domain or low confidence → calibration question before acting\n\nThe routing decision uses a calibration profile: per-domain, per-action-class entries with a confidence score. Until a domain is calibrated, everything goes through **Learning** mode and will ask you to confirm its choices before acting.\n\nTwo hard gates sit on top of calibration:\n\n- **Evidence gates tiers.** Observations arrive with an evidence grade (`hunch`, `quick_check`, `replicated`). An unverified hunch never routes to act or propose, no matter how much confidence the domain has earned — it's capped at explore (and may get investigated first, below).\n- **Reversibility gates autonomy.** Only actions the thinking pass explicitly marked `reversible: true` can execute at the act tier. Unknown blast radius caps at propose.\n\nAnd trust doesn't linger: routing uses a **decayed view** of the calibration profile — confidence earned long ago and never reinforced decays toward the uncalibrated default with a 90-day half-life. The stored values are untouched; the decay is computed at routing time, so reinforcement history is never destroyed.\n\n### Investigation of hunches\n\nBefore a hunch-graded item at or above `investigation.minPriority` surfaces, sapience can spend a bounded, read-only subagent run (at most three queries, `investigation.timeoutSec` cap, `investigation.maxPerDay` budget) testing whether the pattern holds. Supported hunches upgrade to `quick_check` — with the finding appended — and re-route; refuted ones are dropped (the `investigation_completed` event is the trace); inconclusive ones stay gated at explore.\n\n### The hypothesis ledger\n\nHunches that don't clear the evidence bar don't evaporate. Every investigated-or-budget-blocked hunch becomes (or updates) a case in `/sapience/hypotheses.json`: near-identical sightings merge into one evolving case file with a sighting count and an evidence trail of verdicts. Thinking passes see the open cases and re-test them opportunistically instead of re-alerting on every sighting.\n\n### Act-tier execution\n\nAct items run in isolated subagent sessions at routing time (`act.execute`, timeout `act.timeoutSec`). The execution session is told to prefer the most reversible path and to stop rather than push through anything riskier than described. Your main session then gets the **result** — what was done, with the undo path — not a request to do it. Failures are reported too, with a question about whether to try differently. Without the subagent runtime, sapience falls back to the legacy act injection into your main session.\n\n### Channel push\n\nNext-turn injection alone means the agent can never initiate contact. For initiative-worthy items — act/propose at or above `push.minPriority` — sapience requests a heartbeat targeting the last active channel, so the agent delivers as a real outbound message. Budgeted at `push.maxPerDay` per local day; the weekly digest always pushes. Notable watch readings and act results share the same budget.\n\n### Skill proposals\n\nWork the agent does repeatedly should become a skill, not a habit of re-deriving the same steps. When a thinking pass (or the agent mid-task) notices the same multi-step task done more than once, it calls `skill_proposal(name, summary, spec_markdown)` — the spec captures what the skill would do, what triggered it, and the actual queries or scripts used. Proposals dedupe by normalized name: a second sighting appends evidence and bumps `evidence_count` rather than creating a twin.\n\nA proposal is only worth logging when nothing already does the job, so the tool checks the skills this install actually has — `/skills`, the state dir's `skills/`, and any extra roots in `skillsDirs` — before it writes anything. A proposal naming an installed skill is refused outright. A proposal that merely overlaps one is refused once, with the closest skills named; to log it anyway the agent must re-call with `not_covered_by` saying what the existing skill can't do, and that answer is recorded in the spec. Refusals emit `skill_proposal_duplicate_blocked` — a run of them on one name means the agent keeps rediscovering a skill it isn't using.\n\nTwo files back this, following the hypothesis-ledger pattern: `/sapience/skill-proposals.json` is machine state, and `/skill-proposals.md` is the append-only human-readable spec doc, kept at the workspace root where you'd actually read it. The markdown is never parsed back or rewritten, so hand edits survive.\n\nNew proposals surface through the normal delivery path (`[SAPIENCE: SKILL PROPOSAL]`); evidence appends stay quiet, and open proposals resurface in the weekly digest. When you decide, the agent records it with `skill_proposal_update(ref, status)` — `building`, `installed`, or `declined`. **Nothing is ever built or installed unbidden**; the ledger exists to surface the pattern and track your decision. `skill_proposal_list` prints the current state.\n\n### Metric watches\n\n\"Keep an eye on X\" is a first-class primitive. The agent calls `watch_metric(name, query_hint, cadence_hours?, policy?, threshold?)` when you ask it to watch a number; `watch_remove(name)` stops. Each routing pass checks up to `watch.maxChecksPerRun` due watches with a bounded read-only fetch; the delta policy — `percent` (vs the recent baseline mean, default ±20%), `above`, `below`, or `always` — decides whether a reading is worth surfacing. Notable moves go to your main session (and push, budget permitting); steady readings stay in the event stream. Watches live in `/sapience/watches.json`; list them with `/sapience watches`.\n\n## Setup\n\n### Prerequisites\n\nInstall `sapience-thinking` first. Sapience reads its output.\n\n### Install order\n\n```bash\nopenclaw plugins install npm:@akalsey/sapience-thinking\nopenclaw plugins install npm:@akalsey/sapience\nopenclaw plugins install npm:@akalsey/sapience-feedback # optional\nopenclaw plugins install npm:@akalsey/sapience-goals # optional\n```\n\n### Configuration (sapience)\n\nConfig lives under `plugins.entries.sapience.config` — the full path shape; the short `plugins.sapience` form is silently ignored.\n\n```json\n{\n \"plugins\": {\n \"entries\": {\n \"sapience\": {\n \"config\": {\n \"autonomy\": {\n \"defaultTier\": \"propose\",\n \"domainFloors\": {\n \"github\": \"propose\",\n \"salesforce\": \"ask\"\n }\n },\n \"learning\": {\n \"enabled\": true,\n \"confidenceDropThreshold\": 0.4\n },\n \"digest\": {\n \"enabled\": true,\n \"day\": \"friday\",\n \"time\": \"17:00\"\n }\n }\n }\n }\n }\n}\n```\n\n**`defaultTier`** — What tier to use for uncalibrated actions when learning mode is off. Default: `\"propose\"`.\n\n**`domainFloors`** — Minimum tier for a domain. If calibration says `act` for a domain with floor `propose`, it routes as `propose`. Use this for domains where you never want autonomous action regardless of confidence.\n\n**`confidenceDropThreshold`** — Below this confidence, Learning mode fires instead of the calibrated tier. Default: `0.4`.\n\n**`digest`** — Weekly summary of what was acted on, what's pending review, and what's planned. Delivered at the configured day and time.\n\n**`push` / `investigation` / `act` / `watch`** — budgets and timeouts for channel push, hunch investigation, act-tier execution, and metric watches (all on by default; see above).\n\n**`delivery`** — `maxPerCycle` (default 1) caps how many items ride the single note injected per routing run; the rest queue for the delivery cron. `dedupeWindowHours` (default 72) suppresses an item whose text was already delivered inside the window. `sessionKey` routes injections at a specific session instead of the agent main session — required when `session.dmScope` makes the main session machine-only ([docs/configuration.md](../docs/configuration.md#delivery-target)).\n\n**`domains`** — extend the domain taxonomy with `{\"\": \"\"}` patterns, checked against proposal text before the builtins. Use the same key on `sapience-feedback` so feedback lands on the domains routing emits.\n\n**`activeHours`** — Invalid values (a start/end that isn't `HH:MM`, or a bad IANA timezone) don't disable the plugin: it falls back to the defaults and emits a `config_invalid` event. Overnight windows (start later than end, e.g. `22:00`–`06:00`) are supported.\n\nFull key-by-key reference: [docs/configuration.md](../docs/configuration.md).\n\n### Output files\n\nRelative paths resolve under the agent workspace dir (`/`), not `~/.openclaw` — see [\"Where files live\"](../README.md#where-files-live). Absolute and `~/` overrides in config are honored.\n\n| File | Purpose |\n|------|---------|\n| `/sapience/calibration.json` | Autonomy calibration profile (shared with `sapience-feedback`) |\n| `/sapience/processed-passes.json` | Tracks which proactive-thinking passes have been routed |\n| `/sapience/action-log.md` | Log of every Act-tier item delivered |\n| `/sapience/events.jsonl` | Unified event log (all suite plugins append here) |\n| `/sapience/dashboard.md` | Auto-generated dashboard, regenerated every routing pass |\n| `/sapience/digest-state.json` | Date the weekly digest last went out |\n| `/sapience/hypotheses.json` | Hypothesis ledger — open cases with sightings and evidence trails |\n| `/sapience/watches.json` | Metric watches and their reading history |\n| `/sapience/push-state.json` | Daily channel-push budget tracking |\n| `/sapience/investigation-state.json` | Daily investigation budget tracking |\n| `/sapience/pending-deliveries.json` | Queue drained by the `sapience-delivery` cron — per-cycle overflow and failed injections |\n| `/sapience/delivered-ledger.json` | Content hashes of recent deliveries, capped at 500 entries |\n| `/sapience/skill-proposals.json` | Skill-proposal ledger — status and evidence counts |\n| `/skill-proposals.md` | Human-readable skill specs, append-only (workspace root, not `sapience/`) |\n\n`action-log.md` rotates at 5 MB (newest 500 lines kept, previous contents in `action-log.md.old`); `events.jsonl` rotates to timestamped archives with only the newest two archives kept. If a JSON state file is corrupt, it's quarantined to `.corrupt-` and rebuilt.\n\n## Training: calibrating autonomy\n\nCalibration is the process of teaching the agent your preferences per domain and action type.\n\n### Learning mode\n\nWhen sapience sees a domain/action-class combination with no calibration data (or low confidence), it fires a **Learning** prompt instead of acting:\n\n> \"I noticed [item]. My instinct is to surface this as a proposal. Is that the right level of initiative, or would you prefer I handle this differently?\"\n\nYou respond to confirm or redirect. The calibration profile updates accordingly.\n\n### How confidence builds\n\n| Event | Effect |\n|-------|--------|\n| You confirm the proposed approach (\"yes, that's right\") | Confidence +0.1 |\n| You act on or accept a delivered proposal (recorded via `record_outcome`) | Confidence +0.1 |\n| You reject a delivered proposal | Confidence −0.1 |\n| You correct the approach (\"no, just do it\") | Confidence −0.3, tier updated |\n| No feedback | Confidence unchanged |\n\nConfidence caps at 1.0 and floors at 0.0. A domain needs roughly 3–5 confirmations to reach the default threshold (0.4) from zero — and confidence that isn't reinforced decays with a 90-day half-life in the routing view.\n\n### Reading and adjusting the profile: `/sapience`\n\nThe `/sapience` chat command shows the profile grouped by tier, with the decayed confidence routing actually uses:\n\n```\n/sapience # show the profile\n/sapience set # one-line tier override\n/sapience watches # list metric watches\n```\n\nThe raw file is still plain JSON:\n\n```bash\ncat /sapience/calibration.json\n```\n\nEach entry:\n```json\n{\n \"domain\": \"github\",\n \"action_class\": \"github/action\",\n \"tier\": \"propose\",\n \"confidence\": 0.7,\n \"confirmed_count\": 4,\n \"corrected_count\": 1,\n \"last_calibrated\": \"2026-05-20T14:00:00Z\",\n \"notes\": \"\"\n}\n```\n\n### Resetting a domain\n\nDelete the entry from `calibration.json` to reset a domain to Learning mode.\n\n## Day-to-day use\n\nOnce installed, the suite runs in the background. What you'll see in your sessions:\n\n- `[SAPIENCE: PROPOSE]` — a proposal needing your yes/no\n- `[SAPIENCE: ACT RESULT]` — an autonomous action just executed (or failed); includes the undo path\n- `[SAPIENCE: ASK]` — a question needed before proceeding\n- `[SAPIENCE: EXPLORE]` — a problem with options for you to choose from\n- `[SAPIENCE: CALIBRATE]` — a calibration question for a new domain\n- `[SAPIENCE: WATCH]` — a watched metric moved notably\n- `[SAPIENCE: SKILL PROPOSAL]` — a repeated multi-step task was logged as a skill spec\n- `[SAPIENCE: WEEKLY DIGEST]` — Friday summary of actions, pending items, and plans\n\nThese markers instruct the agent, they aren't the text you see: each prompt describes what to convey and the agent writes the note in its own words, varying phrasing between notes. Every injected prompt also opens by subordinating itself to your own message — an injection prepends to your next turn, and your message gets answered first.\n\n### How a delivery reaches you\n\n1. **Injection** into the target session — the agent main session (`agent::`) by default, or `delivery.sessionKey` when set. One note per routing run, carrying at most `delivery.maxPerCycle` items (act-tier first, then priority) and a single copy of the priority guard; each item is logged as `item_delivered`. The cap spans the whole run, however many thinking passes it drained.\n2. **Overflow and failures queue.** Items past the cap, and items the gateway declines, go to `/sapience/pending-deliveries.json` (`item_queued` / `delivery_failed` with `queued: true`). The `sapience-delivery` cron drains that queue every 15 minutes and composes one concise message delivered through your channel via cron announce — so a dead injection path degrades to latency, not silence.\n3. **Push** — high-priority act/propose items, notable watch moves, and the weekly digest additionally request a heartbeat targeting your last active channel, within the daily `push` budget.\n\nRepeats are suppressed before any of this: an item whose normalized text was delivered within `delivery.dedupeWindowHours` (default 72h) is dropped with an `item_suppressed` event, because the thinking model re-emits persistent findings under a fresh id every pass and pass-id dedupe never catches that.\n\n### Weekly digest\n\nEvery Friday at 5pm (or your configured `digest.day`/`digest.time` — minutes are honored, `17:45` means 17:45), the digest summarizes:\n- What was acted on this week\n- Proposals still waiting on your input\n- Open skill proposals — repeated tasks worth codifying, still awaiting your decision\n- What's planned for next week\n\nIt ends with one calibration question drawn from the week's autonomous actions — \"I did X without asking 4 times this week; keep it that way, or check in first?\" — skipped when nothing ran autonomously.\n\nThe digest fires on the first routing run at or after the configured time on the configured day, at most once per day (tracked in `/sapience/digest-state.json`). If a slot was missed — say the gateway was down at 17:00 — it catches up later the same day.\n\n## Troubleshooting\n\nStart with the diagnostic command — it checks plugins, crons (including tool grants), output-file freshness, memory config, and version skew:\n\n```bash\nopenclaw sapience doctor\nopenclaw sapience doctor --probe # trigger one real thinking pass and verify it writes\n```\n\nSee [docs/troubleshooting.md](../docs/troubleshooting.md) for the full guide.\n\n**Nothing being delivered to my session**\nCheck that sapience-thinking is writing `proposals.jsonl`:\n```bash\ntail -1 /proactive-thinking/proposals.jsonl | python3 -m json.tool\n```\nIf the file is empty or missing, sapience-thinking isn't running — run the doctor. If proposals exist, follow the delivery chain in `events.jsonl`: `item_delivered` means it's waiting for your next turn, `item_queued`/`delivery_failed` means the `sapience-delivery` cron owns it now (that job must exist, grant `get_pending_deliveries`, and be registered `--announce`), and `item_suppressed` means it was a repeat inside the dedupe window. If items are delivered but you never see them, you're reading a different session than the one they land in — `openclaw sapience doctor` flags this as `delivery:target`.\n\n**Everything is going to Learning mode**\nExpected behavior for the first week or two. Each calibration response builds confidence. If it continues beyond 2–3 weeks for a domain you use daily, check `calibration.json` — entries may not be getting written.\n\n**Calibration profile not updating**\nFeedback plugin (`sapience-feedback`) handles explicit correction/confirmation capture. If it's not installed, calibrations only happen through the Learning mode prompts. Install `sapience-feedback` for passive capture from chat messages.\n\n**`domainFloors` not respected**\nFloors only prevent routing *above* the floor — they don't push Act-tier items down to propose. `\"github\": \"propose\"` means github/action can be at most `propose`, `ask`, or `explore`, never `act`. If you're seeing Act-tier github items, check the floor config key matches the domain name exactly (lowercase).\n\n**processed-passes.json is missing or was corrupt**\nNothing gets re-delivered. A corrupt file is quarantined to `processed-passes.json.corrupt-`, and a missing/empty processed set triggers a bootstrap that marks **all** existing passes as processed — routing resumes with the next new pass. The cost of losing this file is skipping any genuinely-unrouted passes, not duplicates.\n","readmeFilename":"README.md"}