---
name: post-release
description: Run automated post-release workflow (eval baselines, dashboard, docs) for AILANG releases. Runs the tier-based benchmark suite (core+stretch by default) for standard + agent evals with validation and progress reporting. Use when user says "post-release tasks for vX.X.X" or "update dashboard". Fully autonomous with pre-flight checks.
---

# AILANG Post-Release Tasks

Run post-release tasks for an AILANG release: evaluation baselines, dashboard updates, and documentation.

## Current State

- **Current version**: !'cat std/VERSION'
- **Latest tag**: !'git describe --tags --abbrev=0 2>/dev/null || echo "no tags"'
- **GitHub release**: !'gh release list --limit 3 2>/dev/null | head -3 || echo "gh not available"'
- **Existing baselines**: !'ls eval_results/baselines/ 2>/dev/null | tail -5 || echo "none"'
- **Dashboard version**: !'jq -r .version docs/static/benchmarks/latest.json 2>/dev/null || echo "not found"'
- **Active changelog**: !'ls changelogs/ | grep current 2>/dev/null'

> **Use the data above first.** Only re-run these commands manually if the injected context is empty or you need to refresh after making changes.

## Quick Start

**Most common usage:**
```bash
# User says: "Run post-release tasks for v0.3.14"
# This skill will:
# 1. Run eval baseline (extended_suite: 7 production models + lang-harness sweep) - ALWAYS USE --full FOR RELEASES
# 2. Update website dashboard (JSON with history preservation)
# 3. Update axiom scorecard KPI (if features affect axiom compliance)
# 4. Extract metrics and UPDATE CHANGELOG.md automatically
# 5. Move design docs from planned/ to implemented/
# 6. Run docs-sync to verify website accuracy (version constants, PLANNED banners, examples)
# 7. Commit all changes to git
```

**🚨 CRITICAL: For releases, ALWAYS use --full flag by default**
- Dev models (without --full) are only for quick testing/validation, NOT releases
- Users expect full benchmark results when they say "post-release" or "update dashboard"
- Never start with dev models and then try to add production models later

## When to Use This Skill

Invoke this skill when:
- User says "post-release tasks", "update dashboard", "run benchmarks"
- After successful release (once GitHub release is published)
- User asks about eval baselines or benchmark results
- User wants to update documentation after a release

## Available Scripts

### `scripts/run_eval_baseline.sh <version> [--full] [--cross-harness]`
Run evaluation baseline for a release version.

**🚨 CRITICAL: ALWAYS use --full for releases!**

**Usage:**
```bash
# ✅ RECOMMENDED release baseline (standard + agent + 4-language Explorer sweep) — ~$23
.claude/skills/post-release/scripts/run_eval_baseline.sh 0.15.0 --full --lang-harness

# Standard + agent only (no 4-lang Explorer sweep) — ~$16
.claude/skills/post-release/scripts/run_eval_baseline.sh v0.15.0 --full

# Major release: includes cross-harness comparison (gpt5-5 + opencode-gpt5-5 etc.) — ~$47
.claude/skills/post-release/scripts/run_eval_baseline.sh 0.15.0 --full --cross-harness

# ❌ Dev only — 3 cheap models, AILANG lang only (quick testing/validation) — ~$3.50
.claude/skills/post-release/scripts/run_eval_baseline.sh 0.15.0
```

**Output:**
```
Running eval baseline for 0.3.14...
Mode: FULL (extended_suite: 7 production models)
Expected cost: ~$16 (FULL) or ~$23 (FULL + lang-harness) or ~$47 (FULL + cross-harness)
Expected time: ~30-60 minutes

[Running benchmarks...]

✓ Baseline complete
  Results: eval_results/baselines/0.3.14
  Files: 726 result files
```

**What it does:**
- **Step 1**: Standard eval (0-shot + self-repair)
  - Uses `extended_suite` (--full, 6 models): **gpt5-5** (Apr 2026 flagship), gpt5-4-mini, claude-opus-4-7, claude-sonnet-4-6, gemini-3-1-pro, gemini-3-flash
  - Or `dev_models` (default): gpt5-4-mini, claude-haiku-4-5, gemini-3-flash
  - Both AILANG and Python; all benchmarks in selected tier(s)
- **Step 2**: Agent eval — flagship models × AILANG+Python
  - `agent_suite` (4 cost-tuned models): claude-sonnet-4-6 (longitudinal anchor), gemini-3-flash, gpt5-4-mini, **opencode-sonnet-4-6** (cross-harness pair)
  - **Tier system** (v0.14.0+): `smoke` (15), `core` (22), `stretch` (11), `vision` (6)
  - Default scope: `core,stretch` — Core is the headline metric, Stretch is harder mixed results
  - Expected: `core` 70%+ for AILANG; `vision` intentionally low
  - Feeds the ailang-vs-python comparison story in the Model Leaderboard page
- **Step 3** (--lang-harness): Language × Harness sweep — cheapest models × 4 languages
  - `lang_harness_suite`: claude-haiku-4-5, gemini-3-flash, gpt5-4-mini, opencode-haiku
  - All 4 languages: ailang, python, javascript, go
  - **Tier: `core` only** (22 benchmarks) — stretch is skipped here even if `--tier core,stretch` was set globally
  - Note: 4 core benchmarks are AILANG/Python-only (`contract_bst_validate`, `contract_roman_numeral`, `effect_composition`, `effect_tracking_io_fs`) and auto-skip on JS/Go runs
  - Feeds the **Agent Harness Explorer** language spread and cross-harness comparison data
  - Cost: ~$7 extra
- **--cross-harness**: Replaces Step 2 with `harness_suite` (6 models, paired across harnesses)
  - claude-sonnet-4-6 + opencode-sonnet-4-6, gemini-3-flash + opencode-gemini-3-flash, **gpt5-5 + opencode-gpt5-5**
  - Cost: ~$31 extra vs base FULL (3x)
- Saves combined results to `eval_results/baselines/vX.X.X/`
- Accepts version with or without 'v' prefix

**⚠️ Note**: `gpt5-5-pro` is in `models.yml` but **not in any default suite** — agent mode is blocked
(codex rejects with ChatGPT account, opencode returns 0 tool calls). Don't add it to suites.

### `scripts/update_dashboard.sh <version>`
Update website benchmark dashboard with new release data.

**Usage:**
```bash
.claude/skills/post-release/scripts/update_dashboard.sh 0.3.14
```

**Output:**
```
Updating dashboard for 0.3.14...

1/5 Generating Docusaurus markdown...
  ✓ Written to docs/docs/benchmarks/performance.md

2/5 Generating dashboard JSON with history...
  ✓ Written to docs/static/benchmarks/latest.json (history preserved)

3/5 Validating JSON...
  ✓ Version: 0.3.14
  ✓ Success rate: 0.627

4/5 Clearing Docusaurus cache...
  ✓ Cache cleared

5/5 Summary
  ✓ Dashboard updated for 0.3.14
  ✓ Markdown: docs/docs/benchmarks/performance.md
  ✓ JSON: docs/static/benchmarks/latest.json

Next steps:
  1. Test locally: cd docs && npm start
  2. Visit: http://localhost:3000/ailang/docs/benchmarks/performance
  3. Verify timeline shows 0.3.14
  4. Commit: git add docs/docs/benchmarks/performance.md docs/static/benchmarks/latest.json
  5. Commit: git commit -m 'Update benchmark dashboard for 0.3.14'
  6. Push: git push
```

**What it does:**
- Generates Docusaurus-formatted markdown
- Updates dashboard JSON with history preservation
- Validates JSON structure (version matches input exactly)
- Clears Docusaurus build cache
- Provides next steps for testing and committing
- Accepts version with or without 'v' prefix

### `scripts/extract_changelog_metrics.sh [json_file]`
Extract benchmark metrics from dashboard JSON for CHANGELOG.

**Usage:**
```bash
.claude/skills/post-release/scripts/extract_changelog_metrics.sh
# Or specify JSON file:
.claude/skills/post-release/scripts/extract_changelog_metrics.sh docs/static/benchmarks/latest.json
```

**Output:**
```
Extracting metrics from docs/static/benchmarks/latest.json...

=== CHANGELOG.md Template ===

### Benchmark Results (M-EVAL)

**Overall Performance**: 59.1% success rate (399 total runs)

**By Language:**
- **AILANG**: 33.0% - New language, learning curve
- **Python**: 87.0% - Baseline for comparison
- **Gap: 54.0 percentage points (expected for new language)

**Comparison**: -15.2% AILANG regression from 0.3.14 (48.2% → 33.0%)

=== End Template ===

Use this template in CHANGELOG.md for 0.3.15
```

**What it does:**
- Parses dashboard JSON for metrics
- Calculates percentages and gap between AILANG/Python
- **Auto-compares with previous version from history**
- **Formats comparison text automatically** (+X% improvement or -X% regression)
- Generates ready-to-paste CHANGELOG template with no manual work needed

### `scripts/cleanup_design_docs.sh <version> [--dry-run] [--force] [--check-only]`
Move design docs from planned/ to implemented/ after a release.

**Features:**
- Detects **duplicates** (docs already in implemented/)
- Detects **misplaced docs** (Target: field doesn't match folder version)
- Only moves docs with "Status: Implemented" in their frontmatter
- Docs with other statuses are flagged for review

**Usage:**
```bash
# Check-only: Report issues without making changes
.claude/skills/post-release/scripts/cleanup_design_docs.sh 0.5.9 --check-only

# Preview what would be moved/deleted/relocated
.claude/skills/post-release/scripts/cleanup_design_docs.sh 0.5.9 --dry-run

# Execute: Move implemented docs, delete duplicates, relocate misplaced
.claude/skills/post-release/scripts/cleanup_design_docs.sh 0.5.9

# Force move all docs regardless of status
.claude/skills/post-release/scripts/cleanup_design_docs.sh 0.5.9 --force
```

**Output:**
```
Design Doc Cleanup for v0.5.9
==================================

Checking 5 design doc(s) in design_docs/planned/v0_5_9/:

Phase 1: Detecting issues...

  [DUPLICATE] m-fix-if-else-let-block.md
              Already exists in design_docs/implemented/v0_5_9/
  [MISPLACED] m-codegen-value-types.md
              Target: v0.5.10 (folder: v0_5_9)
              Should be in: design_docs/planned/v0_5_10/

Issues found:
  - 1 duplicate(s) (can be deleted)
  - 1 misplaced doc(s) (wrong version folder)

Phase 2: Processing docs...

  [DELETED] m-fix-if-else-let-block.md (duplicate - already in implemented/)
  [RELOCATED] m-codegen-value-types.md → design_docs/planned/v0_5_10/
  [MOVED] m-dx11-cycles.md → design_docs/implemented/v0_5_9/
  [NEEDS REVIEW] m-unfinished-feature.md
                 Found: **Status**: Planned

Summary:
  ✓ Deleted 1 duplicate(s)
  ✓ Relocated 1 doc(s) to correct version folder
  ✓ Moved 1 doc(s) to design_docs/implemented/v0_5_9/
  ⚠ 1 doc(s) need review (not marked as Implemented)
```

**What it does:**
- **Phase 1 (Detection)**: Identifies duplicates and misplaced docs
- **Phase 2 (Processing)**:
  - Deletes duplicates (same file already exists in implemented/)
  - Relocates misplaced docs (Target: version doesn't match folder)
  - Moves docs with "Status: Implemented" to implemented/
  - Flags docs without Implemented status for review
- Creates target folders if needed
- Removes empty planned folder after cleanup
- Use `--check-only` to only report issues, `--dry-run` to preview actions, `--force` to move all

## Post-Release Workflow

### 1. Verify Release Exists

```bash
git tag -l vX.X.X
gh release view vX.X.X
```

If release doesn't exist, run `release-manager` skill first.

### 2. Run Eval Baseline

**🚨 CRITICAL: ALWAYS use --full for releases!**

**Correct workflow:**
```bash
# ✅ RECOMMENDED for releases — adds 4-language Explorer data for ~$7 more
.claude/skills/post-release/scripts/run_eval_baseline.sh X.X.X --full --lang-harness

# Minimum acceptable for releases
.claude/skills/post-release/scripts/run_eval_baseline.sh X.X.X --full
```

This runs all 7 production models (`extended_suite`) with both AILANG and Python.

**Tier scope for releases:**
- Default (release): `--tier core,stretch` — 33 benchmarks (22 core + 11 stretch)
- Dev/fast mode: `--tier core` — 22 benchmarks (Core is the headline metric)
- Full audit: `--tier smoke,core,stretch` — 48 benchmarks (include smoke for sanity)
- `vision` benchmarks are research-grade and excluded by default — opt in explicitly
  with `--tier vision` if you want to publish those numbers.

Override tier via the script's `--tier` flag (see `run_eval_baseline.sh --help`). If
unsure, the default is tuned to produce a release-ready baseline in ~30–60 minutes.

**Cost & time** (default tier `core,stretch` = 33 benchmarks):
| Mode | Cost | Time | Use for |
|---|---|---|---|
| `--full` | ~$16 | ~30-40 min | Standard release |
| `--full --lang-harness` | ~$23 | ~45-60 min | **Recommended** — adds 4-lang Explorer data |
| `--full --cross-harness` | ~$47 | ~45-60 min | Major releases (vX.0, quarterly) |
| dev (no flags) | ~$3.50 | ~10-15 min | Quick validation only — never for releases |

**❌ WRONG workflow (what happened with v0.3.22):**
```bash
# DON'T do this for releases!
.claude/skills/post-release/scripts/run_eval_baseline.sh X.X.X  # Missing --full!
# Then try to add production models later with --skip-existing
# Result: Confusion, multiple processes, incomplete baseline
```

**If baseline times out or is interrupted:**
```bash
# Resume with ALL 6 models (maintains --full semantics)
ailang eval-suite --full --langs python,ailang --parallel 5 \
  --output eval_results/baselines/X.X.X --skip-existing
```

The `--skip-existing` flag skips benchmarks that already have result files, allowing resumption of interrupted runs. But ONLY use this for recovery, not as a strategy to "add more models later".

### 3. Update Website Dashboard

**Use the automation script:**
```bash
.claude/skills/post-release/scripts/update_dashboard.sh X.X.X
```

**IMPORTANT**: This script automatically:
- Generates Docusaurus markdown (docs/docs/benchmarks/performance.md)
- Updates JSON with history preservation (docs/static/benchmarks/latest.json)
- Does NOT overwrite historical data - merges new version into existing history
- Validates JSON structure before writing
- Clears Docusaurus cache to prevent webpack errors

**Test locally (optional but recommended):**
```bash
cd docs && npm start
# Visit: http://localhost:3000/ailang/docs/benchmarks/performance
```

Verify:
- Timeline shows vX.X.X
- Success rate matches eval results
- No errors or warnings

**Commit dashboard updates:**
```bash
git add docs/docs/benchmarks/performance.md docs/static/benchmarks/latest.json
git commit -m "Update benchmark dashboard for vX.X.X"
git push
```

### 4. Update Axiom Scorecard

**Review and update the axiom scorecard:**
```bash
# View current scorecard
ailang axioms

# The scorecard is at docs/static/benchmarks/axiom_scorecard.json
# Update scores if features were added/improved that affect axiom compliance
```

**When to update scores:**
- +1 → +2 if a partial implementation becomes complete
- New feature aligns with an axiom → update evidence
- Gaps were fixed → remove from gaps array
- Add to history array to track KPI over time

**Update history entry:**
```json
{
  "version": "vX.X.X",
  "date": "YYYY-MM-DD",
  "score": 18,
  "maxScore": 24,
  "percentage": 75.0,
  "notes": "Added capability budgets (A9 +1)"
}
```

### 5. Extract Metrics for CHANGELOG

**Generate metrics template:**
```bash
.claude/skills/post-release/scripts/extract_changelog_metrics.sh X.X.X
```

This outputs a formatted template with:
- Overall success rate
- Standard eval metrics (0-shot, final with repair, repair effectiveness)
- Agent eval metrics by language
- **Automatic comparison with previous version** (no manual work!)

**Update changelog automatically:**
1. Run the script to generate the template
2. Insert the "Benchmark Results (M-EVAL)" section into the active changelog file in `changelogs/` (find with `ls changelogs/ | grep current`)
3. Place it after the feature/fix sections and before the next version
4. Note: Root `CHANGELOG.md` is an index file — do NOT write entries there

For CHANGELOG template format, see [`resources/version_notes.md`](resources/version_notes.md).

### 5a. Analyze Agent Evaluation Results

**v0.8.0+ (chain-based - recommended):**
```bash
# Find the chain ID from the latest eval run
ailang eval-chains list

# View per-benchmark pass/fail with cost and turns
ailang eval-chains view <chain-id>

# Pass rate breakdown
ailang eval-chains stats <chain-id>

# Show failures with error details
ailang eval-chains failures <chain-id>

# Generate chain-based report
ailang eval-report --from-chain <chain-id> X.X.X --format=json
```

**Legacy (file-based):**
```bash
# Get KPIs (turns, tokens, cost by language)
.claude/skills/eval-analyzer/scripts/agent_kpis.sh eval_results/baselines/X.X.X
```

Target metrics: Avg Turns ≤1.5x gap, Avg Tokens ≤2.0x gap vs Python.

For detailed agent analysis guide, see [`resources/version_notes.md`](resources/version_notes.md).

### 5b. Tag-Based Analysis and Rotation Check (v0.14.0+)

After dashboard + changelog metrics, run the curation analysis primitives. These inform
what to keep, demote, or promote for the next release — the suite is curated, not
accumulated. See `benchmarks/CURATION.md` for the full philosophy.

```bash
# Tag coverage: which of the 12 canonical tags are thin or over-represented?
ailang eval-matrix eval_results/baselines/vX.X.X vX.X.X --by-tags

# AILANG-only wins: AILANG beats Python by ≥ 10pp — protect these from regressions
ailang eval-matrix eval_results/baselines/vX.X.X vX.X.X --ailang-wins

# Dual-mode saturation audit (RECOMMENDED for demotion decisions):
# Lists every benchmark's standard AND agent pass rate per language.
# Demote candidates require ≥95% on ALL 4 dimensions (std-AI, std-Py, agent-AI, agent-Py).
# Standard-only saturation is misleading: many benchmarks are 100/100 in standard
# but drop to 12-50% in agent mode — those are still valuable signal, KEEP IN CORE.
.claude/skills/benchmark-manager/scripts/audit_saturation.sh vX.X.X

# Built-in saturated check (uses topline successRate only — less reliable, prefer the script above):
ailang eval-matrix eval_results/baselines/vX.X.X vX.X.X --show-saturated

# Optional: compare this release's tag deltas against the previous baseline
ailang eval-report eval_results/baselines/vX.X.X vX.X.X --format=json
```

Record three things in the release notes (or the design doc retro):
- **Demote candidates** — saturated benchmarks that should move to `stretch` or be
  retired in the next sprint.
- **Keep as value evidence** — AILANG-only wins that prove the language's ROI.
- **Thin tags** — taxonomy gaps (<3 benchmarks in a tag) to target with new benchmarks.

This step is cheap (seconds), has no external dependencies, and produces the input
for the next release's benchmark-manager / eval-gap-finder work.

### 6. Move Design Docs to Implemented

**Step 1: Check for issues (duplicates, misplaced docs):**
```bash
.claude/skills/post-release/scripts/cleanup_design_docs.sh X.X.X --check-only
```

**Step 2: Preview all changes:**
```bash
.claude/skills/post-release/scripts/cleanup_design_docs.sh X.X.X --dry-run
```

**Step 3: Check any flagged docs:**
- `[DUPLICATE]` - These will be deleted (already in implemented/)
- `[MISPLACED]` - These will be relocated to correct version folder
- `[NEEDS REVIEW]` - Update `**Status**:` to `Implemented` if done, or leave for next version

**Step 4: Execute the cleanup:**
```bash
.claude/skills/post-release/scripts/cleanup_design_docs.sh X.X.X
```

**Step 5: Commit the changes:**
```bash
git add design_docs/
git commit -m "docs: cleanup design docs for vX_Y_Z"
```

The script automatically:
- Deletes duplicates (same file already in implemented/)
- Relocates misplaced docs (Target: version doesn't match folder)
- Moves docs with "Status: Implemented" to implemented/
- Flags remaining docs for manual review

### 7. Update Public Documentation

- Update `prompts/` with latest AILANG syntax (`ailang prompt`)
- Update `prompts/devtools/` with latest toolchain docs (`ailang devtools-prompt`)
  - New CLI commands or flags should be added to the devtools prompt
  - Verify with: `ailang devtools-prompt | grep "new-command"`
- Update website docs (`docs/`) with latest features
- Remove outdated examples or references
- Add new examples to website
- Update `docs/guides/evaluation/` if significant benchmark improvements
- **Update `docs/LIMITATIONS.md`**:
  - Remove limitations that were fixed in this release
  - Add new known limitations discovered during development/testing
  - Update workarounds if they changed
  - Update version numbers in "Since" and "Fixed in" fields
  - **Test examples**: Verify that limitations listed still exist and workarounds still work
    ```bash
    # Test examples from LIMITATIONS.md
    # Example: Test Y-combinator still fails (should fail)
    echo 'let Y = \f. (\x. f(x(x)))(\x. f(x(x))) in Y' | ailang repl

    # Example: Test named recursion works (should succeed)
    ailang run examples/factorial.ail

    # Example: Test polymorphic operator limitation (should panic with floats)
    # Create test file and verify behavior matches documentation
    ```
  - Commit changes: `git add docs/LIMITATIONS.md && git commit -m "Update LIMITATIONS.md for vX.X.X"`

### 8. Run Documentation Sync Check

**Run docs-sync to verify website accuracy:**
```bash
# Check version constants are correct
.claude/skills/docs-sync/scripts/check_versions.sh

# Audit design docs vs website claims
.claude/skills/docs-sync/scripts/audit_design_docs.sh

# Generate full sync report
.claude/skills/docs-sync/scripts/generate_report.sh
```

**What docs-sync checks:**
- Version constants in `docs/src/constants/version.js` match git tag
- Teaching prompt references point to latest version
- Architecture pages have PLANNED banners for unimplemented features
- Design docs status (planned vs implemented) matches website claims
- Examples referenced in website actually work

**If issues found:**
1. Update version.js if stale
2. Add PLANNED banners to theoretical feature pages
3. Move implemented features from roadmap to current sections
4. Fix broken example references

**Commit docs-sync fixes:**
```bash
git add docs/
git commit -m "docs: sync website with vX.X.X implementation"
```

See [docs-sync skill](../docs-sync/SKILL.md) for full documentation.

### 9. Verify μRAG Corpus Reindex (REQUIRED)

`release-manager` runs `make brain-index-syntax-reset` immediately after the
tag pushes. This step **verifies** that the reset actually populated the
brain with chunks tagged with the new release version — protects against
silent indexer failures that would leave Claude pulling stale snippets.

**Spot-check ≥5 chunks reference the active version:**

```bash
EXPECTED_VERSION="$(ailang prompt --version-active)"
ailang cache search --namespace ailang-syntax --limit 5 "string" \
  | grep -c "version:${EXPECTED_VERSION}" \
  || { echo "FAIL: μRAG corpus does not reference $EXPECTED_VERSION"; exit 1; }
```

**Quick stat check:**

```bash
ailang cache stats | grep -E "ailang-(syntax|builtins|examples)"
# Expect: ailang-syntax >= 50, ailang-builtins >= 250, ailang-examples >= 100
```

**Append a one-line audit to release notes** (or `eval_results/baselines/<version>/notes.md`):

```
μRAG corpus reindex verified: <ailang-syntax count>, <ailang-builtins count>, <ailang-examples count> chunks @ <version>.
```

**If verification fails:**
- Re-run `make brain-index-syntax-reset` from the project root.
- Check `ailang prompt --version-active` returns the new release tag.
- If it returns nothing, the prompt directory wasn't published in the
  release — escalate to release-manager rather than masking the issue.

## Resources

### Post-Release Checklist
See [`resources/post_release_checklist.md`](resources/post_release_checklist.md) for complete step-by-step checklist.

## Prerequisites

- Release vX.X.X completed successfully
- Git tag vX.X.X exists
- GitHub release published with all binaries
- `ailang` binary installed (for eval baseline)
- Node.js/npm installed (for dashboard, optional)

## Common Issues

### Eval Baseline Times Out
**Solution**: Use `--skip-existing` flag to resume:
```bash
bin/ailang eval-suite --full --skip-existing --output eval_results/baselines/vX.X.X
```

### Dashboard Shows "null" for Aggregates
**Cause**: Wrong JSON file (performance matrix vs dashboard JSON)
**Solution**: Use `update_dashboard.sh` script, not manual file copying

### Webpack/Cache Errors in Docusaurus
**Cause**: Stale build cache
**Solution**: Run `cd docs && npm run clear && rm -rf .docusaurus build`

### Dashboard Shows Old Version
**Cause**: Didn't run update_dashboard.sh with correct version
**Solution**: Re-run `update_dashboard.sh X.X.X` with correct version

## Progressive Disclosure

This skill loads information progressively:

1. **Always loaded**: This SKILL.md file (YAML frontmatter + workflow overview)
2. **Execute as needed**: Scripts in `scripts/` directory (automation)
3. **Load on demand**: `resources/post_release_checklist.md` (detailed checklist)

Scripts execute without loading into context window, saving tokens while providing powerful automation.

## Version Notes

For historical improvements and lessons learned, see [`resources/version_notes.md`](resources/version_notes.md).

Key points:
- All scripts accept version with or without 'v' prefix
- Use `--validate` flag to check configuration before running
- Agent eval scopes benchmarks by tier (`--tier core,stretch` default) — benchmarks
  are resolved from `benchmarks/*.yml` by tier, not a hardcoded list
- Tag-based curation analysis runs via `ailang eval-matrix --by-tags/--show-saturated/
  --ailang-wins` in Step 5b

## Notes

- This skill follows Anthropic's Agent Skills specification (Oct 2025)
- Scripts handle 100% of automation (eval baseline, dashboard, metrics extraction, design docs)
- Can be run hours or even days after release
- Dashboard JSON preserves history - never overwrites historical data
- Always use `--full` flag for release baselines (all production models)
- Design docs cleanup now handles duplicates, misplaced docs, and status-based moves
  - `--check-only` to report issues without changes
  - `--dry-run` to preview all actions
  - `--force` to move all regardless of status