# GOVERNANCE_REALITY_CHECK_REPORT.md

**Initiative:** INITIATIVE-007R — Governance Reality Check  
**Date:** 2026-06-23  
**Status:** ✅ GOVERNANCE_REALITY_CHECK_COMPLETE

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## Files Read (Evidence Sources)

| File | SHA | Size | Purpose |
|---|---|---|---|
| `tools/dependency_auditor.py` | `4a3e7a3e` | 19,358 bytes | Read completely — pip/badge tool, NOT graph tool |
| `tools/recommend.py` | `3d95d515` | ~12 KB | Read completely — recommendation engine |
| `.github/workflows/validate-graph.yml` | `667323ca` | 5,226 bytes | Read completely — graph CI |
| `.github/workflows/pr-checks.yml` | `c5414f05` | 4,211 bytes | Read completely — PR gate CI |
| `meta/MEMORY_STATE.md` | `1d7e0d5f` | Read | Current state context |

**Note:** `tools/build_graph.py` and `tools/extract_edges.py` were not read in this initiative pass. Their governance impact is UNKNOWN until read directly.

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## Critical Findings

### Finding 1 — `dependency_auditor.py` Is Not a Graph Governance Tool

The file is a **Python package dependency auditor** for skill `.md` files. It installs pip packages and runs code snippets. It has zero graph topology awareness. It never reads `data/SKILLS_GRAPH.json`. The name created a false impression that graph dependency governance was partially implemented.

**Governance impact:** Any prior roadmap that counted `dependency_auditor.py` as a graph governance capability was incorrect.

### Finding 2 — Only 4 Graph Checks Exist in CI

`validate-graph.yml` implements exactly 4 graph checks:
1. Schema validity (is it valid JSON with `meta.node_count`?)
2. Duplicate node IDs
3. Self-loop edges
4. Invalid source node references

All other topology checks are absent.

### Finding 3 — `pr-checks.yml` Has Zero Graph Governance Scope

The file itself documents this in its header comment. Its sole validation is HTML relative path checking in `docs/index.html`.

### Finding 4 — Cycle Detection Exists But Is Suppressed

`recommend.py` reaches the cycle condition in `topological_sort()` but responds with a silent bypass rather than a failure signal. Cycles in the REQUIRES graph will not be detected by any CI check.

### Finding 5 — Tags Are Unpopulated (Confirmed Cross-Reference)

`MEMORY_STATE.md` documents `Tags populated: 0/368`. `recommend.py` tag matching logic is structurally correct but functionally inert for all 368 current nodes.

---

## Deliverables Created

| File | Content |
|---|---|
| `meta/GOVERNANCE_CAPABILITY_MATRIX.md` | Full capability matrix: 15 capabilities, EXISTS/PARTIAL/MISSING per evidence |
| `meta/GOVERNANCE_DEAD_CODE_AUDIT.md` | 6 dead code findings with verbatim evidence |
| `meta/GOVERNANCE_GAP_CLASSIFICATION.md` | 8 gaps classified as Category A/B/C |
| `meta/GOVERNANCE_PRIORITY_MATRIX.md` | 8 items ranked by leverage with implementation order |

---

## What Was NOT Done

Per the mission mandate:
- No new governance systems designed
- No new validators created
- No new workflows created
- No roadmap generated beyond gap prioritization
- No synthetic metrics introduced
- No previous agent claims copied

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## Immediate Next Steps (Evidence-Based)

The highest-ROI actions based on gap classification:

1. **Add dangling target detection** to `validate-graph.yml` — copy existing source-check step, change `source` → `target`. ~10 lines.
2. **Add duplicate edge detection** to `validate-graph.yml` — copy existing node-dedup step, apply to edge tuples. ~12 lines.
3. **Fix cycle suppression** in `recommend.py` `topological_sort()` — raise instead of bypass at lines 126–129.

These three actions close the three highest-priority gaps with the lowest implementation risk. They are the correct starting point for INITIATIVE-008R.

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*No synthetic metrics. No inferred relationships. All findings traceable to direct file reads.*
