reconcile
SkillAI & modelsUse this skill when the user wants to reconcile learnings into rules, run /reconcile, propose rules from learnings, turn learnings into .claude/rules/ entries, or review what rules would be generated from current session learnings. On-demand version of session-end Phase 3.6.8.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the reconcile skill
What this skill tells your AI
The instructions your AI receives, as published by kanevry/session-orchestrator in skills/reconcile/SKILL.md and read by ahel’s review.
Platform Note: State files use the platform's native directory:
.claude/(Claude Code),.codex/(Codex CLI), or.cursor/(Cursor IDE). Shared metrics live in.orchestrator/metrics/. Seeskills/_shared/platform-tools.md.
Reconcile Skill
On-demand version of the session-end Phase 3.6.8 reconciliation flow. Turns eligible learnings
from .orchestrator/metrics/learnings.jsonl into proposed .claude/rules/<slug>.md entries,
presenting each batch of 4 to the coordinator via AUQ multiSelect for operator approval before
any file is written. Advisory-only — rules are NEVER auto-applied.
Posture Contract (load-bearing — read before executing)
- Advisory-only. No rule is ever written without explicit operator approval via AUQ. The AUQ multiSelect is the mandatory gate; there is no bypass.
- Never-always-on invariant. The reconcile engine's emitter (
emitter.mjs) throws on any eligible learning that would produce analwaysApply: truerule — the engine structurally cannot emit always-on rules. This invariant is enforced upstream, not by this skill. - Engine never writes
.claude/rules/.runReconcilecomputes proposals and records them in the idempotency sidecar only. The only module that writes.claude/rules/iswriter.mjs, and only AFTER the operator approves proposals via AUQ. - The candidate store belongs to
mergeCandidates— nothing else writes it..orchestrator/runtime/reconcile-candidates.jsonlis a mutable work-queue whose only sanctioned writer ismergeCandidates(scripts/lib/reconcile/idempotency.mjs); it is not a scratch pad, and no report, analysis run, or agent may append to it by hand. A hand-written record there corrupts downstream readers — the session-start reconcile nudge banner derives "last run" fromcreated_at, so a foreign-shaped record makes a non-empty store report no reconcile run on record. Candidate analyses and dry-run reports write their findings todocs/reconcile/<date>-<topic>.md, never into the store. (Since 2026-07-31 a read-side shape guard drops records lackinglearning_key/created_atandmergeCandidatesreports the count asskipped— that guard is a backstop, not a licence.) - Same pipeline as session-end Phase 3.6.8. This skill uses the identical engine and writer seams as the automatic session-end reconciliation phase — operator experience is consistent, and any fixes to the engine benefit both paths.
reconcile.enabledgates the AUTOMATIC session-end phase only./reconcileis an on-demand command and runs regardless ofreconcile.enabled. It still honoursrule-expiry-daysandconfidence-floorfrom thereconcileconfig block.
Phase 0: Bootstrap Gate
Read skills/_shared/bootstrap-gate.md and execute the gate check. If the gate is CLOSED,
invoke skills/bootstrap/SKILL.md and wait for completion before proceeding. If the gate
is OPEN, continue to Phase 1.
Phase 1: Config & Argument Loading
1.1 Read Session Config
Read and parse Session Config per skills/_shared/config-reading.md. Store result as $CONFIG.
1.2 Extract Reconcile Config
Extract the reconcile block from $CONFIG:
# rule-expiry-days defaults to EMPTY (not a number) so the engine falls back to
# its per-type TTL (deriveExpiresAt, default 60d). A numeric override forces flat
# N-day expiry — matching the `null` default of the reconcile: config resolver.
RULE_EXPIRY_DAYS=$(echo "$CONFIG" | jq -r '.reconcile["rule-expiry-days"] // empty')
CONFIDENCE_FLOOR=$(echo "$CONFIG" | jq -r '.reconcile["confidence-floor"] // 0.5')
RECONCILE_MODE=$(echo "$CONFIG" | jq -r '.reconcile.mode // "warn"')
MIN_RULE_DAYS=$(echo "$CONFIG" | jq -r '.reconcile["min-rule-days"] // 7')
MIN_INSIGHT_CHARS=$(echo "$CONFIG" | jq -r '.reconcile["min-insight-chars"] // 24')
MAX_PROPOSALS_PER_RUN=$(echo "$CONFIG" | jq -r '.reconcile["max-proposals-per-run"] // 10')
When RULE_EXPIRY_DAYS is empty, pass ruleExpiryDays: undefined to runReconcile so the engine uses its per-type TTL. Defaults when the reconcile block is absent or a field is missing:
rule-expiry-days: empty → per-type TTL (deriveExpiresAt, default 60d). Preserves FA2 behaviour; matches thenullresolver default.confidence-floor: 0.5mode: warn (enumoff|warn)min-rule-days: 7 — floor window (days) applied to a proposed rule'sexpires-atso a near-dead or already-elapsed natural expiry never produces a born-dead rule (issue #741.1).min-insight-chars: 24 — opt-in minimum insight length gating the eligibility placeholder-insight check (issue #741.2).max-proposals-per-run: 10 — volume brake (issue #900 D); the engine sorts eligible learnings by confidence DESC and proposes at most this many per run.
Note: reconcile.enabled is intentionally NOT checked — this on-demand command always runs.
1.3 Parse Arguments
Check $ARGUMENTS for --dry-run:
DRY_RUN=false
if echo "$ARGUMENTS" | grep -q -- '--dry-run'; then
DRY_RUN=true
fi
Phase 2: Run the Reconciliation Engine
2.1 Resolve Plugin Root
Resolve $PLUGIN_ROOT per skills/_shared/config-reading.md (the standard resolution chain:
$CLAUDE_PLUGIN_ROOT → $CODEX_PLUGIN_ROOT → $CURSOR_RULES_DIR → common install locations).
2.2 Resolve the Effective Write-Targets
reconcile.targets says WHERE approved rules land. Resolve it BEFORE surfacing
the approval AUQ — the operator must never be asked to approve a write to a
destination that cannot exist:
import { resolveEffectiveTargets } from '$PLUGIN_ROOT/scripts/lib/reconcile/engine.mjs';
const { targets, baselineRoot, dropped, reason } = resolveEffectiveTargets({
targets: CONFIG.reconcile?.targets, // ['repo-local'] | ['baseline'] | both
baselineRoot: CONFIG['plan-baseline-path'], // already 3-tier-resolved by config.mjs
});
| Target | Writes to | Root |
|---|---|---|
repo-local (default) | <repoRoot>/.claude/rules/<slug>.md | repoRoot |
baseline (#1099) | <baselineRoot>/proposals/<slug>.md | plan-baseline-path, resolved SO_BASELINE_PATH env > owner.yaml paths.baseline-path > committed |
baseline is DROPPED (with one stderr WARN, and dropped: ['baseline'] in the
return) when the root is unresolvable on all three tiers, is still the committed
OVERRIDE-IN-… placeholder, or is not absolute. A dropped target means: do not
surface its proposals in the AUQ at all. If targets comes back EMPTY, stop
here and report the reason — there is nowhere to write.
Writing to baseline is still advisory and AUQ-gated exactly like repo-local:
files land under proposals/ in the baseline checkout, nothing is committed
there, and no branch is touched. The operator reviews and commits in that repo
himself.
2.3 Invoke runReconcile
import { runReconcileFromSkill } from '$PLUGIN_ROOT/scripts/lib/reconcile/engine.mjs';
const { proposals, rejected, summary, error } = await runReconcileFromSkill({
repoRoot, // absolute path from git rev-parse --show-toplevel
ruleExpiryDays: RULE_EXPIRY_DAYS, // empty → undefined → engine per-type TTL
minRuleDays: MIN_RULE_DAYS, // default 7 — floors a near-dead expires-at
minInsightChars: MIN_INSIGHT_CHARS, // default 24 — opt-in placeholder-insight length gate
maxProposalsPerRun: MAX_PROPOSALS_PER_RUN, // default 10 — volume brake (issue #900 D)
now: new Date(),
dryRun: DRY_RUN, // true → engine touches no disk (no idempotency sidecar write)
// trigger is pinned to 'skill' IN CODE by runReconcileFromSkill (#1201 Part A) —
// this prose block no longer sets it.
targets, // from resolveEffectiveTargets above; recorded when non-empty, omitted otherwise
});
// The engine does NOT apply a confidence floor — it proposes every eligible
// learning and carries each one's `confidence` through. `confidence-floor` is a
// DELIVERY gate: filter proposals here before the sidecar + AUQ (mirrors
// session-end Phase 3.6.8). Use `surfaced` everywhere "proposals" appears below.
const surfaced = proposals.filter((p) => typeof p.confidence === 'number' && p.confidence >= CONFIDENCE_FLOOR);
runReconcile NEVER throws — a top-level error populates result.error instead.
If error is present, surface it to the user and abort:
"Reconcile engine error:
<error>. Check.orchestrator/metrics/learnings.jsonland retry."
2.3 Handle Empty / Zero-Proposal Cases
If summary.totalLearnings === 0:
"No learnings found in
.orchestrator/metrics/learnings.jsonl. Run/evolve analyzefirst to extract session patterns." Exit cleanly.
If summary.eligible === 0 (learnings exist but none are eligible — already proposed,
or wrong learning type — eligibility is type/file_paths-based, NOT confidence-based):
"No eligible learnings for rule proposals (total:
summary.totalLearnings, already proposed or ineligible type: all). Run more sessions to accumulate evidence." Exit cleanly. Optionally list the rejection reasons fromrejected[](fieldreason) as an informational table.
If summary.eligible > 0 but surfaced.length === 0 (proposals exist but ALL fall below
confidence-floor):
"No proposals above the confidence floor (
CONFIDENCE_FLOOR). Lowerreconcile.confidence-flooror run more sessions so the underlying learnings accrue confidence." Exit cleanly.
If summary.proposed === 0 but summary.eligible > 0 (emit/render failures consumed all
candidates — unusual):
"Engine produced 0 proposals from N eligible learnings. See rejection log." List
rejected[].reasonand exit.
Phase 3: Dry-Run Branch
Only when DRY_RUN=true.
Print the proposals in a readable table. Do NOT write the sidecar, do NOT render an AUQ, and
do NOT write candidates into .orchestrator/runtime/reconcile-candidates.jsonl — that store
is mergeCandidates' alone (see Posture Contract). A dry-run write-up belongs in
docs/reconcile/.
## Reconcile — Dry Run (N proposals, M rejected)
| # | Slug | Confidence | Learning Key | Rule Path |
|---|------|-----------|-------------|-----------|
| 1 | <slug> | 0.72 | <learningKey> | .claude/rules/<slug>.md |
| 2 | ... | ... | ... | ... |
Rejected (not eligible for proposal):
| Learning Key | Reason |
|-------------|--------|
| <key> | <reason> |
Re-run without --dry-run to enter the approval flow.
Exit after printing. Do not proceed to Phase 4.
Phase 4: Write Pending Sidecar (Normal Mode Only)
Create the runtime proposal sidecar .orchestrator/metrics/reconcile-pending.md as a human-readable
record before presenting the AUQ. This sidecar is informational only — it lets the operator
see the full proposal set in an editor alongside the AUQ prompt.
# Reconcile Pending — <ISO date>
Generated by `/reconcile` on <timestamp>. N proposals, M rejected.
## Proposals
| # | Slug | Confidence | Learning Key | Rendered Rule Path |
|---|------|-----------|-------------|-------------------|
| 1 | <slug> | 0.72 | <key> | .claude/rules/<slug>.md |
...
## Rejected
| Learning Key | Type | Reason |
|-------------|------|--------|
| <key> | <type> | <reason> |
...
Write via standard file write (not atomic, not lock-protected — this is a disposable sidecar, not a critical artifact).
Phase 5: AUQ Approval Flow (Normal Mode Only)
Present proposals to the operator in batches of 4. Mirror the session-end Phase 3.6.3 / 3.6.8 multiSelect pattern exactly.
For each batch (proposals sliced into groups of 4):
AskUserQuestion({
questions: [{
question: "Batch K of N — which rule proposals should be written into .claude/rules/?",
header: "Regeln",
options: [
{
label: "<slug>.md (confidence: 0.72)",
description: "From learning <learningKey>. Becomes a file under .claude/rules/ — where this repo keeps its rules. Text: <first 100 chars of rendered content>"
},
...up to 4 options per batch...
{
label: "Skip all in this batch",
description: "Decline all proposals in this batch — they are archived to the rejected log."
}
],
multiSelect: true
}]
})
Collect responses across all batches:
- Selected options (excluding "Skip all") →
approved[] - Unselected options + "Skip all" batches →
rejected_by_operator[]
Codex CLI fallback: AskUserQuestion is unavailable in subagents and on Codex CLI (AUQ-004). In those contexts, present proposals as a numbered Markdown list and ask the operator to reply with the numbers they wish to approve.
Phase 6: Write Approved Rules
6.1 Invoke writeApprovedRules
import { writeApprovedRules } from '$PLUGIN_ROOT/scripts/lib/reconcile/writer.mjs';
const { written, archived, errors } = await writeApprovedRules({
approved: approved, // proposals the operator approved
rejected: rejected_by_operator, // proposals the operator declined
repoRoot,
baselineRoot, // from Phase 2.2; omit/undefined ⇒ baseline is a no-op
targets, // from Phase 2.2; omitted ⇒ ['repo-local']
sessionId: currentSessionId, // informational; from STATE.md or 'manual'
});
writeApprovedRules NEVER throws — per-item failures are collected in errors[].
written is a FILE count, not a proposal count: one proposal approved with both
targets in effect writes two files and counts 2, while stamping the idempotency
sidecar exactly once. A baseline root that does not exist on disk (the
fresh-clone / CI case) skips that target with an errors[] entry — it is NEVER
created, because a typo'd path that silently mints a directory tree looks
exactly like a successful write.
6.2 Handle Errors
If errors.length > 0, surface each error to the operator:
"Warning:
Nrule(s) failed to write:<error list>. Successfully written:written. Archived:archived."
Log each error but do NOT abort — partial success is acceptable.
6.3 Report
## Reconcile Complete
- Written: <written> rule file(s) to .claude/rules/
- Archived: <archived> declined proposal(s) to .orchestrator/reconcile.rejected.log
- Errors: <errors.length> (see warnings above, if any)
New rules take effect immediately — they are loaded by the wave-executor's rule-loader
on the next wave dispatch.
If written === 0 and approved.length === 0:
"No proposals approved. No rules written."
Consolidating and Dropping Generated Rules (merge contract)
.claude/rules/ grows one file per approved learning, so it accumulates. This
repo consolidated 43 generated files (112,443 B, 46.2 % frontmatter+provenance
overhead) into 8 thematic files plus 10 drops on 2026-09-06. Both operations
are safe ONLY under the contract below — the full authoring spec is
docs/rule-authoring.md § "Consolidated rules:
N provenance pairs in ONE file". The three facts that decide whether a
consolidation survives the next /reconcile:
- A target file may carry N provenance bullet PAIRS. Frontmatter
learning-key:is a scalar, so at most one marker fits there; the other N−1 live in the body as- learning-key: `…`+- learning-id: `…`bullets, whichengine.mjsreads viaBODY_LEARNING_KEY_RE/BODY_LEARNING_ID_RE. One pair per absorbed learning — a missing pair regenerates that learning as a standalone file on the next run. - A merged file's
expires-atis the EARLIEST of its parts, never the latest: it must not outlive its shortest-lived content. - A dropped learning must be STAMPED before deletion, or it regenerates.
rm .claude/rules/<slug>.mdalone leavesisProcessed()false and no on-disk marker, so the engine re-proposes it. Stamp it terminal first withmarkCandidateProcessed({ learningKey, outcome: 'rejected', fallbackSlug, repoRoot })fromscripts/lib/reconcile/idempotency.mjs— the ONLY sanctioned writer of.orchestrator/runtime/reconcile-candidates.jsonl(never append to that file by hand; the read-side shape guard drops foreign records andmergeCandidatesrewrites the store in full).
Verify a consolidation with a dry run, not by eye: alreadyMaterialized
must equal absorbed + dropped. If it equals only the absorbed count, the drops
were not stamped and the next run will resurrect them. Do the whole operation
while reconcile.enabled: false in Session Config, so nothing regenerates
underneath you mid-edit.
Critical Rules
- NEVER call
writeApprovedRulesbefore the operator has confirmed via AUQ — this is the only write-protection gate for.claude/rules/. - NEVER pass
dryRun: falsetorunReconcileand then skip the AUQ — the idempotency sidecar is written during the engine run; writing rules without AUQ confirmation would create an inconsistency between the sidecar and the actual rule files. - ALWAYS surface
errors[]fromwriteApprovedRules— per-item isolation must not silently swallow failures. - ALWAYS present proposals in batches of ≤4 via AUQ multiSelect — mirrors session-end 3.6.3 / 3.6.8 and keeps the operator prompt readable.
- ALWAYS honour
confidence-floor,rule-expiry-days,min-rule-days,min-insight-chars, andmax-proposals-per-runfrom Session Configreconcileblock — the engine reads these, but the skill must pass them explicitly.
Anti-Patterns
- DO NOT write any file to
.claude/rules/without AUQ operator confirmation. - DO NOT check
reconcile.enabled— that flag gates the automatic session-end phase, not this on-demand command. - DO NOT emit or approve a rule with
alwaysApply: true— the engine structurally prevents it, but the reviewer should reject any proposal that would produce an always-on rule. - DO NOT skip the dry-run branch when
--dry-runis passed — the entire AUQ + write flow must be bypassed. - DO NOT treat
runReconcilefailures as fatal — check theerrorfield and surface it, then exit cleanly.
Signals
- GitHub stars
- 50
- Forks
- 7
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
reconcile-kanevry- Source
- github.com/kanevry/session-orchestrator