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echo/echo-memory.plugin.src/skills/echo-reflect/SKILL.md
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Jason Stedwell 446cd9a0ff 2.1.0 — quick-wins train: brief load, offline-durable capture, session-end verb
Three independently useful changes (IMPROVEMENT-PLANS #1/#3/#7), no schema changes:

- load --brief: token-budgeted cold-start digest (facts full, last-10 observations,
  scope+freshness, last session's key sections, agent-log lines, inbox count;
  ECHO_LOAD_BUDGET ~8000 chars, lowest-priority-first trimming). SessionStart hook
  injects the brief form; /echo-load keeps the full dump. All load reads (+ the
  sessions listing, which also feeds the heartbeat fallback) fetched in parallel.
- Offline capture durability: a fully-offline capture queues the WHOLE op as one
  semantic record; flush replays it through capture so routing/gate/aliasing re-run
  against the current index; a gate stop on replay is kept + flagged
  (needs_attention, surfaced by flush and load), never landed blind; update-path
  and ensure_daily_log writes ride safe_request; same-args captures dedupe.
- session-end: one call, one lock — session log -> agent-log line -> reflect
  proposals (gate-aware) -> optional scope set -> heartbeat LAST as the commit
  marker; dry-run default; ECHO_NOW pins HHMM; validation runs before any write.
  Stop hook nudge names the command and recognizes it as reflected.
- Fix: main() now catches the __main__ twin-module EchoError (via RuntimeError +
  .code) so helper-module errors exit with their intended codes, not tracebacks.

+19 e2e checks; all suites green. Plans renumbered: MCP container is 2.2.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-28 22:34:42 -05:00

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---
name: echo-reflect
description: Reflect on this session — extract durable memories and propose them for one-tap capture
argument-hint: "[optional focus, e.g. 'just decisions']"
allowed-tools: Bash(python3 *echo.py*), Bash(python *echo.py*), Bash(py -3 *echo.py*), Bash(ls /sessions/*)
---
Use the **echo-memory** skill to run **session reflection** (H5). Scan this conversation for
things worth remembering across sessions, then propose them — don't write blindly.
1. **Extract** durable items from the conversation: new facts, preferences, decisions,
commitments, people/companies/projects introduced, and anything the operator said to remember.
Skip the ephemeral. Anchor relative dates on the conversation's `currentDate`.
2. **Emit a JSON array** of proposals (one per item), each:
`{"title","kind","body","aliases","tags","sources","confidence"}``kind`
`person, company, concept, reference, meeting, project, area, semantic, episodic,
working, skill, decision`; set `"inbox": true` when the home is genuinely unknown;
`confidence` 01 (items below 0.6 are dropped — send those to the inbox instead).
Write the array to a file with the Write tool (cross-platform; no heredoc).
3. **Preview, then apply.** Dry-run first (writes nothing) and show the operator the plan; only
apply after they confirm.
```bash
ECHO="${CLAUDE_PLUGIN_ROOT}/skills/echo-memory/scripts/echo.py" # python3 (Windows: python / py -3)
[ -f "$ECHO" ] || ECHO=$(ls /sessions/*/mnt/.remote-plugins/*/skills/echo-memory/scripts/echo.py 2>/dev/null | head -1) # CoWork sandbox fallback
python3 "$ECHO" reflect proposals.json # dry-run: validate + classify + preview
python3 "$ECHO" reflect proposals.json --apply # write — routes each via capture (indexed, linked, logged)
```
`reflect` dedups every proposal against the entity index (so it shows create-vs-update),
skips below-confidence items, and routes `inbox` proposals to the capture inbox. Each
applied item goes through the normal `capture` path — canonical frontmatter, auto-linking,
and the recall index — and the writes are lock-guarded.
**Finishing the session?** Prefer the one-call bundle — `python3 "$ECHO" session-end
bundle.json --apply` — which applies the reflect proposals AND writes the session log,
Agent Log line, optional scope switch, and the heartbeat (last, as the commit marker)
together. See the echo-memory skill's **Session Logging** section for the bundle shape. $ARGUMENTS