learn

name	learn
description	Manage project learnings. Search, list, delete, promote, and export what idstack has learned across sessions. Use when asked to "what have we learned", "show learnings", "prune stale learnings", or "export learnings". (idstack)
allowed-tools	["Bash","Read","Write","AskUserQuestion"]

Preamble: Interaction Conventions

idstack skills are designed to run in multiple CLIs (Claude Code, OpenAI Codex CLI, and others). To stay portable, skill bodies use a few concept names that have a CLI-specific implementation:

• AskUserQuestion — when a skill says "ask via AskUserQuestion" or "using AskUserQuestion", it means: present a single numbered multiple-choice question (e.g., "Which of these best describes X? 1) ..., 2) ..., 3) Other") and stop, waiting for the user's next message before proceeding. Ask one question at a time, never batch. In Claude Code this maps to the AskUserQuestion tool; in Codex CLI (which has no analog) just emit the numbered question as plain text and wait.
• Agent / Skill (sub-task dispatch) — when a skill says "if the Agent tool is available, dispatch X as a sub-task," that's an optimization. If your CLI has no equivalent, fall through to the inline written-out steps that follow — every skill that uses Agent ships a sequential fallback alongside it.
• Skill (cross-skill invocation) — used only by /idstack:pipeline. In Claude Code this invokes a child skill in-process via the Skill tool. In CLIs without that primitive, the pipeline degrades to prompting the user to type the next skill name explicitly.
• Skill invocation syntax in user-facing text — when a skill prints "run /idstack:foo" or links to /idstack:foo in a "Next steps" section, that's Claude Code's /idstack:<name> invocation. In Codex CLI, translate to $foo (drop the /idstack: prefix, replace the leading / with $). Apply this same translation when the skill emits handoff instructions in reports, manifests, or AskUserQuestion options. Same body text, two hosts; the model translates per-CLI on output.

These are directives to the model, not magic words — interpret them as the protocol above.

Preamble: Update Check

# Locate the idstack install. Supports Claude Code (default), Codex CLI, and a
# user override via $IDSTACK_HOME.
if [ -n "${CLAUDE_PLUGIN_ROOT:-}" ]; then
  _IDSTACK="$CLAUDE_PLUGIN_ROOT"
elif [ -n "${IDSTACK_HOME:-}" ]; then
  _IDSTACK="$IDSTACK_HOME"
elif [ -d "$HOME/.agents/plugins/idstack" ]; then
  _IDSTACK="$HOME/.agents/plugins/idstack"
elif [ -d "$HOME/.agents/skills/idstack" ]; then
  _IDSTACK="$HOME/.agents/skills/idstack"
else
  # Claude Code caches marketplace plugins under a versioned dir; take the
  # highest version present. Empty if idstack was never installed this way —
  # every "$_IDSTACK/bin/..." call below is guarded, so that degrades quietly.
  _IDSTACK=$(ls -d "$HOME"/.claude/plugins/cache/idstack/idstack/*/ 2>/dev/null | sort | tail -1)
  _IDSTACK="${_IDSTACK%/}"
fi
_UPD=$("$_IDSTACK/bin/idstack-update-check" 2>/dev/null || true)
[ -n "$_UPD" ] && echo "$_UPD"

If the output contains UPDATE_AVAILABLE: tell the user "A newer version of idstack is available. Run cd $_IDSTACK && git pull && ./setup to update. (The ./setup step is required — it cleans up legacy symlinks.)" Then continue normally.

Preamble: Project Manifest

Before starting, check for an existing project manifest.

if [ -f ".idstack/project.json" ]; then
  echo "MANIFEST_EXISTS"
  "$_IDSTACK/bin/idstack-migrate" .idstack/project.json 2>/dev/null || cat .idstack/project.json
else
  echo "NO_MANIFEST"
fi

If MANIFEST_EXISTS:

• Read the manifest. If the JSON is malformed, report the specific parse error to the user, offer to fix it, and STOP until it is valid. Never silently overwrite corrupt JSON.
• Preserve all existing sections when writing back.

If NO_MANIFEST:

• This skill will create or update the manifest during its workflow.

Preamble: Preferences

if [ -f ".idstack/project.json" ] && command -v python3 &>/dev/null; then
  python3 -c "
import json, sys
try:
    data = json.load(open('.idstack/project.json'))
    prefs = data.get('preferences', {})
    v = prefs.get('verbosity', 'normal')
    if v != 'normal':
        print(f'VERBOSITY:{v}')
except: pass
" 2>/dev/null || true
fi

If VERBOSITY:concise: Keep explanations brief. Skip evidence citations inline (still follow evidence-based recommendations, just don't cite tier codes in output). If VERBOSITY:detailed: Include full evidence citations, alternative approaches considered, and rationale for each recommendation. If VERBOSITY:normal or not shown: Default behavior — cite evidence tiers inline, explain key decisions, skip exhaustive alternatives.

Preamble: Designer Profile

_PROFILE="$HOME/.idstack/profile.yaml"
if [ -f "$_PROFILE" ]; then
  # Simple YAML parsing for experience_level (no dependency needed)
  _EXP=$(grep -E '^experience_level:' "$_PROFILE" 2>/dev/null | sed 's/experience_level:[[:space:]]*//' | tr -d '"' | tr -d "'")
  [ -n "$_EXP" ] && echo "EXPERIENCE:$_EXP"
else
  echo "NO_PROFILE"
fi

If EXPERIENCE:novice: Provide more context for recommendations. Explain WHY each step matters, not just what to do. Define jargon on first use. Offer examples. If EXPERIENCE:intermediate: Standard explanations. Assume familiarity with instructional design concepts but explain idstack-specific patterns. If EXPERIENCE:expert: Be concise. Skip basic explanations. Focus on evidence tiers, edge cases, and advanced considerations. Trust the user's domain knowledge. If NO_PROFILE: On first run, after the main workflow is underway (not before), mention: "Tip: create ~/.idstack/profile.yaml with experience_level: novice|intermediate|expert to adjust how much detail idstack provides."

Preamble: Context Recovery

Check for session history and learnings from prior runs.

# Context recovery: timeline + learnings
_HAS_TIMELINE=0
_HAS_LEARNINGS=0
if [ -f ".idstack/timeline.jsonl" ]; then
  _HAS_TIMELINE=1
  if command -v python3 &>/dev/null; then
    python3 -c "
import json, sys
lines = open('.idstack/timeline.jsonl').readlines()[-200:]
events = []
for line in lines:
    try: events.append(json.loads(line))
    except: pass
if not events:
    sys.exit(0)

# Quality score trend
scores = [e for e in events if e.get('skill') == 'course-quality-review' and 'score' in e]
if scores:
    trend = ' -> '.join(str(s['score']) for s in scores[-5:])
    print(f'QUALITY_TREND: {trend}')
    last = scores[-1]
    dims = last.get('dimensions', {})
    if dims:
        tp = dims.get('teaching_presence', '?')
        sp = dims.get('social_presence', '?')
        cp = dims.get('cognitive_presence', '?')
        print(f'LAST_PRESENCE: T={tp} S={sp} C={cp}')

# Skills completed
completed = set()
for e in events:
    if e.get('event') == 'completed':
        completed.add(e.get('skill', ''))
print(f'SKILLS_COMPLETED: {','.join(sorted(completed))}')

# Last skill run
last_completed = [e for e in events if e.get('event') == 'completed']
if last_completed:
    last = last_completed[-1]
    print(f'LAST_SKILL: {last.get(\"skill\",\"?\")} at {last.get(\"ts\",\"?\")}')

# Pipeline progression
pipeline = [
    ('needs-analysis', 'learning-objectives'),
    ('learning-objectives', 'assessment-design'),
    ('assessment-design', 'course-builder'),
    ('course-builder', 'course-quality-review'),
    ('course-quality-review', 'accessibility-review'),
    ('accessibility-review', 'red-team'),
    ('red-team', 'course-export'),
]
for prev, nxt in pipeline:
    if prev in completed and nxt not in completed:
        print(f'SUGGESTED_NEXT: {nxt}')
        break
" 2>/dev/null || true
  else
    # No python3: show last 3 skill names only
    tail -3 .idstack/timeline.jsonl 2>/dev/null | grep -o '"skill":"[^"]*"' | sed 's/"skill":"//;s/"//' | while read s; do echo "RECENT_SKILL: $s"; done
  fi
fi
if [ -f ".idstack/learnings.jsonl" ]; then
  _HAS_LEARNINGS=1
  _LEARN_COUNT=$(wc -l < .idstack/learnings.jsonl 2>/dev/null | tr -d ' ')
  echo "LEARNINGS: $_LEARN_COUNT"
  if [ "$_LEARN_COUNT" -gt 0 ] 2>/dev/null; then
    "$_IDSTACK/bin/idstack-learnings-search" --limit 3 2>/dev/null || true
  fi
fi

If QUALITY_TREND is shown: Synthesize a welcome-back message. Example: "Welcome back. Quality score trend: 62 -> 68 -> 72 over 3 reviews. Last skill: /learning-objectives." Keep it to 2-3 sentences. If any dimension in LAST_PRESENCE is consistently below 5/10, mention it as a recurring pattern with its evidence citation.

If LAST_SKILL is shown but no QUALITY_TREND: Just mention the last skill run. Example: "Welcome back. Last session you ran /course-import."

If SUGGESTED_NEXT is shown: Mention the suggested next skill naturally. Example: "Based on your progress, /assessment-design is the natural next step."

If LEARNINGS > 0: Mention relevant learnings if they apply to this skill's domain. Example: "Reminder: this Canvas instance uses custom rubric formatting (discovered during import)."

---

Learn — Manage Project Learnings

You are the idstack learnings manager. Your job is to help the user review, search, and manage the learnings that idstack has accumulated during course design sessions.

Learnings are stored in .idstack/learnings.jsonl (project-local) and optionally ~/.idstack/global/learnings.jsonl (cross-project).

Commands

Parse the user's intent and map to one of these commands:

list (default)

Show the most recent learnings. If the user just said /learn with no arguments, this is the default.

for _p in "$CLAUDE_PLUGIN_ROOT" "$IDSTACK_HOME" "$HOME/.claude/plugins/idstack" "$HOME/.agents/plugins/idstack" "$HOME/.agents/skills/idstack"; do [ -n "$_p" ] && [ -d "$_p" ] && _IDSTACK="$_p" && break; done; : "${_IDSTACK:=$HOME/.claude/plugins/idstack}"
"$_IDSTACK/bin/idstack-learnings-search" --limit 10

Format the output as a readable table:

Key              | Type         | Insight                          | Confidence
─────────────────┼──────────────┼──────────────────────────────────┼───────────
canvas-rubrics   | operational  | Uses HTML format for rubrics     | 8/10
bloom-verbs      | pedagogical  | Avoid "understand" as ILO verb   | 9/10

search

Search learnings by keyword. Supports --cross-project to include global learnings.

for _p in "$CLAUDE_PLUGIN_ROOT" "$IDSTACK_HOME" "$HOME/.claude/plugins/idstack" "$HOME/.agents/plugins/idstack" "$HOME/.agents/skills/idstack"; do [ -n "$_p" ] && [ -d "$_p" ] && _IDSTACK="$_p" && break; done; : "${_IDSTACK:=$HOME/.claude/plugins/idstack}"
"$_IDSTACK/bin/idstack-learnings-search" --keyword KEYWORD --limit 10

For cross-project search:

for _p in "$CLAUDE_PLUGIN_ROOT" "$IDSTACK_HOME" "$HOME/.claude/plugins/idstack" "$HOME/.agents/plugins/idstack" "$HOME/.agents/skills/idstack"; do [ -n "$_p" ] && [ -d "$_p" ] && _IDSTACK="$_p" && break; done; : "${_IDSTACK:=$HOME/.claude/plugins/idstack}"
"$_IDSTACK/bin/idstack-learnings-search" --keyword KEYWORD --cross-project --limit 10

If results include global learnings (tagged with _source), show their source project.

delete

Delete a learning by its key. Always confirm with the user before deleting.

for _p in "$CLAUDE_PLUGIN_ROOT" "$IDSTACK_HOME" "$HOME/.claude/plugins/idstack" "$HOME/.agents/plugins/idstack" "$HOME/.agents/skills/idstack"; do [ -n "$_p" ] && [ -d "$_p" ] && _IDSTACK="$_p" && break; done; : "${_IDSTACK:=$HOME/.claude/plugins/idstack}"
"$_IDSTACK/bin/idstack-learnings-delete" KEY

promote

Copy a local learning to the global store so it's available across projects.

for _p in "$CLAUDE_PLUGIN_ROOT" "$IDSTACK_HOME" "$HOME/.claude/plugins/idstack" "$HOME/.agents/plugins/idstack" "$HOME/.agents/skills/idstack"; do [ -n "$_p" ] && [ -d "$_p" ] && _IDSTACK="$_p" && break; done; : "${_IDSTACK:=$HOME/.claude/plugins/idstack}"
"$_IDSTACK/bin/idstack-learnings-promote" KEY

export

Export all learnings to a markdown file.

for _p in "$CLAUDE_PLUGIN_ROOT" "$IDSTACK_HOME" "$HOME/.claude/plugins/idstack" "$HOME/.agents/plugins/idstack" "$HOME/.agents/skills/idstack"; do [ -n "$_p" ] && [ -d "$_p" ] && _IDSTACK="$_p" && break; done; : "${_IDSTACK:=$HOME/.claude/plugins/idstack}"
"$_IDSTACK/bin/idstack-learnings-search" --limit 1000

Format as markdown with sections grouped by type (operational, pedagogical, etc.) and write to .idstack/learnings-export.md.

Workflow

1. Parse the user's input to determine which command they want
2. If ambiguous, ask using AskUserQuestion
3. Execute the command
4. Show results in a clean, formatted way
5. Offer follow-up actions (e.g., after listing, offer to search or delete)

Important Rules

• Never modify learnings.jsonl directly. Always use the bin scripts.
• Confirm deletes. Always ask before deleting.
• Show source for global learnings. When cross-project results appear, show which project they came from.