agentic/code/addons/agent-loop/skills/reflection-injection/SKILL.md
Inject relevant past reflections into agent context at iteration start so agents learn from prior mistakes without repeating them
npx skillsauth add jmagly/aiwg reflection-injectionInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Automatically inject relevant past reflections into agent context when starting new iterations or retrying after failures.
Alternate expressions and non-obvious activations (primary phrases are matched automatically from the skill description):
This skill implements the Reflexion episodic memory injection pattern. Before each iteration, it loads relevant past reflections and injects them into the agent's context, enabling learning from past mistakes without repeating them.
When triggered, this skill:
Load reflection history:
.aiwg/ralph/reflections/loops/ for current loop reflections.aiwg/ralph/reflections/patterns/ for cross-loop patternsFilter for relevance:
Format for injection:
Track usage:
activation:
always_active_for:
- ralph-loop-orchestrator
- ralph-verifier
triggered_by:
- ralph_iteration_start
- agent_retry_after_failure
- explicit_user_request
skip_when:
- no_reflection_history: true
- first_iteration_of_first_loop: true
This skill uses:
project-awareness: Context for relevance filtering.aiwg/ralph/reflections/This skill's persistence flows through resolveStorage('reflections'). On the default fs backend reflections live at .aiwg/reflections/. To redirect into Obsidian, Logseq, Fortemi, or another backend without changing this skill, configure roots.reflections or backends.reflections in .aiwg/storage.config (#934).
When this skill needs to read/write reflections from a Bash step, prefer the storage-routed CLI:
aiwg reflections list --prefix sessions/
aiwg reflections get sessions/2026-04-28.md
echo "# reflection" | aiwg reflections put sessions/2026-04-28.md
echo '{"event":"reflect","summary":"..."}' | aiwg reflections append-log sessions/log.jsonl
The legacy direct-fs paths continue to work on the default fs backend — byte-identical to what the adapter writes — but only the adapter route honors storage.config redirection.
data-ai
Report which research-corpus radar sidecars are overdue for refresh. Computes staleness (days since last refresh vs the cadence window) for every radar, sorted most-overdue-first. Runs via `aiwg corpus radar-status`.
data-ai
Aggregate research-corpus radar sidecars into a corpus or per-cluster freshness report — totals, overdue count, per-cluster / per-GRADE / per-trajectory breakdowns, an overdue table, and per-radar rationale snippets. Runs via `aiwg corpus radar-report`.
testing
Scaffold radar/freshness sidecars for research-corpus REFs. Pulls title/authors from the citation sidecar and GRADE from the analysis doc, defaults the refresh cadence from GRADE and the cluster from a corpus-local map, and stamps documentation/radar/REF-XXX-radar.md. Runs via `aiwg corpus radar-init`.
data-ai
Compute an entity's publication trajectory — per-year paper counts, topic drift, hot-streak detection (≥3 consecutive A-grade years), and career phase. Runs via `aiwg corpus profile-temporal`.