Batch Filing Gaps

Batch Filing Gaps

Scan all observer canvases for ### GAP-* sections, deduplicate similar gaps across users, route to the correct repo (score-api or midi-interface), draft issue bodies with user quotes as evidence, present for operator confirmation, and file approved issues via gh issue create.

Core Principle

Gaps are user-grounded. Every issue filed must trace back to at least one direct user quote or feedback entry. No speculative issues.

Triggers

/gap-to-issues                                # Scan all canvases
/gap-to-issues --canvas <username>            # Single canvas only
/gap-to-issues --repo score-api               # Filter to score-api issues only
/gap-to-issues --repo midi-interface          # Filter to midi-interface issues only
/gap-to-issues --dry-run                      # Preview without filing

When to Use

• After a /daily-synthesis run that detected new gaps
• When 3+ canvases exist and cross-user patterns are visible
• Before sprint planning — to populate the backlog with user-grounded issues
• Periodically to ensure no gaps are accumulating unfiled

Workflow

Step 1: Scan Canvases

Glob grimoires/observer/canvas/*.md and grep for ### GAP- sections.

For each GAP found, extract:

• GAP ID (e.g., GAP-DATA-001)
• Type: ACCURACY, WEIGHTINGS, UX, FEATURE
• Severity: HIGH, MEDIUM, LOW
• Status: IDENTIFIED, FILED, RESOLVED
• Source user and canvas
• Supporting quotes

Skip gaps with status FILED or RESOLVED.

Step 2: Deduplicate

Group similar gaps across canvases:

• Same GAP type + similar description → merge into single issue
• Track all contributing users as evidence sources
• Use the highest severity across duplicates

Example: "Data staleness" appearing in 3 canvases → single issue with 3 user citations.

Step 2.5: Source Fidelity Classification

Before routing or filing any gap, classify its evidence to prevent filing inferred features as concrete requests.

4-Category Evidence Taxonomy:

Gate Logic:

1. For each IDENTIFIED gap, locate the supporting quote in the source canvas
2. Verify the quote directly supports the issue — no interpretation required
3. Category (d) gaps: remove from the filing batch, output warning, log to NOTES.md
4. Category (c) gaps: keep in batch but add observed-pattern to labels

Apply this gate per-gap before proceeding to Step 3.

Step 3: Route to Repos

Step 4: Draft Issue Bodies

For each deduplicated gap, draft a GitHub issue:

## User Feedback Gap

**Gap Type**: {ACCURACY|WEIGHTINGS|UX|FEATURE}
**Severity**: {HIGH|MEDIUM|LOW}
**Users Affected**: {N} ({usernames})

### Evidence

> "{direct user quote}" — @{username} (Rank #{rank}, {crowd_tier})

> "{another quote}" — @{username2} (Rank #{rank}, {crowd_tier})

### Context

{Description of the gap, what users expected vs what happened}

### Score API Position of Reporters

| User | Rank | Tier | Signal Weight |
|------|------|------|---------------|
| {username} | #{rank} | {crowd_tier}/{elite_tier} | HIGH |

---

*Filed from observer gap analysis — grimoires/observer/canvas/{canvas}.md*
*Generated by /gap-to-issues*

Labels: feedback, {gap_type} (e.g., data-accuracy, calibration, ux)

Step 4.5: Enrich with Visual Evidence

For each deduplicated gap, scan the MER timeline for snapshots of affected wallets:

# For each affected wallet in the gap
for wallet_alias in "${affected_wallets[@]}"; do
    mer_files=$(grep -rl "wallet_alias: $wallet_alias" grimoires/observer/timeline/MER-*.md 2>/dev/null || true)
    if [[ -n "$mer_files" ]]; then
        # Use most recent MER (last in sorted list)
        latest_mer=$(echo "$mer_files" | sort | tail -1)
        # Extract screenshot_url and score position from frontmatter/Data State
    fi
done

If MER(s) found for any affected wallet, append to the issue body (after Evidence, before footer):

### Visual Evidence

| User | MER | Screenshot | Rank | Tier |
|------|-----|------------|------|------|
| {username} | [[timeline/{mer_id}]] | ![snapshot]({screenshot_url}) | #{rank} | {crowd_tier} |
| {username2} | [[timeline/{mer_id2}]] | (data-only) | #{rank2} | {crowd_tier2} |

For wallets with screenshots, embed the image inline. For data-only MERs, show "(data-only)" in the screenshot column. For wallets with no MER at all, omit the row.

If no MERs exist for any affected wallet, skip this section entirely — the issue uses text-only evidence (existing behavior).

Score Position at Capture table (one per wallet with a MER):

### Score Position at Capture

| User | Combined | OG | NFT | Onchain | Crowd Tier | Elite Tier |
|------|----------|----|-----|---------|------------|------------|
| {username} | {combined} | {og} | {nft} | {onchain} | {crowd_tier} | {elite_tier} |

Step 5: Present Batch Summary

Display all drafted issues to operator for confirmation:

Gap Issues Ready to File:

  1. [score-api] Data staleness in NFT holdings (HIGH)
     Evidence: 3 users (xabbu, elcapitan, ncs)
     → File? [Y/n]

  2. [midi-interface] Badge checklist missing earned indicators (MEDIUM)
     Evidence: 1 user (xabbu)
     → File? [Y/n]

  3. [score-api] Trust filter threshold unclear (LOW)
     Evidence: 1 user (juri23)
     → File? [Y/n]

In --dry-run mode: Show drafts without the confirmation prompt.

Step 6: File Confirmed Issues

For each confirmed issue:

gh issue create --repo 0xHoneyJar/{repo} \
  --title "{title}" \
  --body "{body}" \
  --label "feedback,{type_label}"

Capture the issue URL from output.

Step 7: Update Canvas GAP Status

For each filed gap, update the canvas:

• Change status from IDENTIFIED to FILED
• Add issue link: Issue: {url}
• Add filed date

Error Handling

Validation

• Only scans IDENTIFIED gaps (skips FILED/RESOLVED)
• Deduplication groups similar gaps correctly
• Each issue has at least one direct user quote
• Correct repo routing (ACCURACY/WEIGHTINGS → score-api)
• Labels applied correctly
• Canvas GAP status updated after filing
• --dry-run creates no issues

Related

• /analyze-gap — Single canvas gap analysis
• /file-gap — Single gap filing (this skill batches across canvases)
• /daily-synthesis — Detects gaps from UI feedback