Context audit

Context Audit

Score every file in the default-loaded context set on 4 deterministic dimensions (footprint, load-bearing, integrity, redundancy). Emit KEEP / TRIM / DEMOTE / CUT verdicts and a total token budget. Optionally run the Tier-2 ablation harness to verify a proposed cut is safe.

Default-Loaded Set

Layer	Files	Loaded how
Bootloader	CLAUDE.md	always
Rules	context/rules/*.md	always (auto via .claude/rules symlink)
Context	context/SOUL.md, context/IDENTITY.md, context/TOOLS.md, context/USER.md	session start
Memory	memory/MEMORY.md (+ today's log)	session start
Skill metadata	frontmatter of all **/SKILL.md	always injected

Instructions

1. Parse arguments

Arguments received: $ARGUMENTS

Argument	Mode
empty or all	Tier-1 scorecard only
--baseline	Tier-1 scorecard + record durable baseline snapshot to memory/YYYY-MM-DD/context-audit-baseline/
--ablate <file>	Tier-1 scorecard + Tier-2 ablation against <file> (path relative to harness root)

2. Inventory the default-loaded set

HARNESS=/home/sandbox/harness
TODAY=$(date -u +%Y-%m-%d)

# Enumerate all files and their footprint
for f in \
  "$HARNESS/CLAUDE.md" \
  "$HARNESS"/context/rules/*.md \
  "$HARNESS/context/SOUL.md" \
  "$HARNESS/context/IDENTITY.md" \
  "$HARNESS/context/TOOLS.md" \
  "$HARNESS/context/USER.md" \
  "$HARNESS/memory/MEMORY.md"; do
  [ -f "$f" ] || continue
  chars=$(wc -c < "$f")
  words=$(wc -w < "$f")
  echo "$((chars/4)) $words $f"
done

# Skill metadata aggregate (all SKILL.md description fields)
skill_chars=$(grep -h -A10 '^description:' \
  "$HARNESS"/.claude/skills/*/SKILL.md \
  "$HARNESS"/workspace/.claude/skills/*/SKILL.md 2>/dev/null \
  | wc -c)
echo "$((skill_chars/4)) skill-metadata-aggregate (all trigger descriptions)"

Collect the list as ALL_FILES for use in the scoring steps below.

3. Score each file on 4 dimensions

For every file in the inventory (skip the skill-metadata aggregate row — no verdict, budget line only), compute 4 dimensions using shell commands only.

---

Dimension A — Footprint (0-2)

Token cost (chars/4). Lower cost earns a higher score — every token in the default-loaded set is paid on every session start.

TOKENS=$(($(wc -c < "$f") / 4))

Tokens	Score
< 500	2
500 – 1,500	1
> 1,500	0

---

Dimension B — Load-bearing (0-2)

Citation count: how many skills, agents, tracked docs, and orchestrator files reference this file by name (a measurable proxy for "this content is actively consumed").

FILE_BASE=$(basename "$f")
REFS=$(grep -rl "$FILE_BASE" \
  "$HARNESS/.claude/skills" \
  "$HARNESS/.claude/agents" \
  "$HARNESS/AGENTS.md" \
  "$HARNESS/CLAUDE.md" \
  "$HARNESS/context" \
  "$HARNESS/docs" 2>/dev/null \
  | grep -v "^${f}$" | wc -l)

Citations	Score
>= 5	2
1 – 4	1
0	0

---

Dimension C — Integrity (0-2)

Verify that every file path and skill reference within the file resolves. Broken references are load-bearing context that actively misleads.

# Absolute paths referenced in backticks or quotes
PATH_REFS=$(grep -oP '`[^`]+`|"[^"]+"' "$f" \
  | grep -oP '/[a-zA-Z0-9_./-]+' | sort -u)

# Skill invocations like /release, /ci-status (exclude filesystem paths)
SKILL_REFS=$(grep -oP '/[a-z][a-z0-9-]+' "$f" \
  | grep -v '^/home' | sort -u)

BROKEN=0
for p in $PATH_REFS; do
  [ -e "$p" ] || BROKEN=$((BROKEN + 1))
done
for s in $SKILL_REFS; do
  name="${s#/}"
  { [ -d "$HARNESS/.claude/skills/$name" ] || \
    [ -d "$HARNESS/workspace/.claude/skills/$name" ]; } \
    || BROKEN=$((BROKEN + 1))
done

Broken refs	Score
0	2
1 – 2	1
3+	0

---

Dimension D — Redundancy (0-2)

Check whether this file's section-header structure substantially duplicates another loaded file. Redundant files add cost without adding unique signal.

HEADS=$(grep '^## ' "$f" | sed 's/^## //')
OVERLAP=0
for other in $ALL_FILES; do
  [ "$other" = "$f" ] && continue
  [ -f "$other" ] || continue
  match=$(grep '^## ' "$other" | sed 's/^## /' \
    | grep -cFf <(echo "$HEADS") 2>/dev/null || echo 0)
  [ "$match" -gt 2 ] && OVERLAP=$((OVERLAP + 1))
done

Overlap files	Score
0	2
1	1
2+	0

---

4. Compute total and verdict

TOTAL = A + B + C + D  (max 8)

Total	Verdict	Meaning
7 – 8	KEEP	Signal justified; no action needed
5 – 6	TRIM	Reduce footprint or remove duplicate sections; stays default-loaded
3 – 4	DEMOTE	Move to on-demand (session-start explicit read or skill); remove from auto-load
0 – 2	CUT	Not earning its slot; remove or merge. Run Tier-2 ablation first if B > 0.

5. Emit Tier-1 report

Print today's date as YYYY-MM-DD.

## Context Audit — YYYY-MM-DD

### Budget
Total default-loaded (scored files): X tokens
Skill metadata aggregate: ~Y tokens
Grand total: ~Z tokens

### Scorecard
| File | Tokens | A:Foot | B:Load | C:Integ | D:Redun | Total | Verdict |
|------|-------:|:------:|:------:|:-------:|:-------:|------:|---------|
| ...  |        |        |        |         |         |       |         |

(sorted by Total ascending — worst first)

### Recommendations
- **CUT**: <file> — <one-line reason>
- **DEMOTE**: <file> — <one-line reason>
- **TRIM**: <file> — <one-line reason>

Omit KEEP files from Recommendations. Use the short filename (e.g. recursive-delegation.md), not the full path.

6. Tier-2 ablation (skip if mode is all)

Purpose: determine whether removing a file degrades observable behavior. This is the only step that goes beyond static proxies to provide an empirical signal measurement.

Do not apply Tier-2 to CLAUDE.md — removing orchestrator instructions produces meaningless probe results.

6a. Baseline probe run

Run all probes in .claude/skills/context-audit/probes/ with the full default-loaded set present.

SKILL_DIR="$HARNESS/.claude/skills/context-audit"
PROBE_DIR="$SKILL_DIR/probes"
RESULTS="/tmp/context-audit-$(date +%s)"
mkdir -p "$RESULTS"

extract_body() {
  # strips YAML frontmatter; prints body (text after closing ---)
  awk '/^---/{n++; if(n==2){p=1;next}} p{print}' "$1"
}

for probe in "$PROBE_DIR"/*.md; do
  pname=$(basename "$probe" .md)
  claude -p "$(extract_body "$probe")" --output-format text \
    > "$RESULTS/baseline-${pname}.txt" 2>&1
  echo "baseline: $pname → $RESULTS/baseline-${pname}.txt"
done

If --baseline mode: copy results to memory/$TODAY/context-audit-baseline/ for durable storage.

mkdir -p "$HARNESS/memory/$TODAY/context-audit-baseline"
cp "$RESULTS"/baseline-*.txt "$HARNESS/memory/$TODAY/context-audit-baseline/"

6b. Ablation run

Back up the target file, run all probes, restore. Use trap to guarantee restore on error.

TARGET="$HARNESS/$ARGUMENTS_FILE"   # the <file> arg from --ablate
cp "$TARGET" "${TARGET}.bak"
trap 'mv "${TARGET}.bak" "$TARGET" 2>/dev/null; echo "restored $TARGET"' EXIT

mv "${TARGET}.bak.tmp" "${TARGET}.bak" 2>/dev/null || true
mv "$TARGET" "${TARGET}.bak"

for probe in "$PROBE_DIR"/*.md; do
  pname=$(basename "$probe" .md)
  claude -p "$(extract_body "$probe")" --output-format text \
    > "$RESULTS/ablation-${pname}.txt" 2>&1
  echo "ablation: $pname → $RESULTS/ablation-${pname}.txt"
done

# trap fires on EXIT and restores the file

6c. Evaluate degradation

For each probe, read MUST-CONTAIN markers from the probe's frontmatter markers: list. Count how many markers appear in the baseline vs. ablation response.

extract_markers() {
  # prints one marker per line from YAML frontmatter markers: list
  awk '/^markers:/{f=1;next} f && /^  - /{print substr($0,5)} f && /^[a-z]/{exit}' "$1"
}

for probe in "$PROBE_DIR"/*.md; do
  pname=$(basename "$probe" .md)
  baseline_hits=0; ablation_hits=0; total=0

  while IFS= read -r marker; do
    [ -z "$marker" ] && continue
    total=$((total + 1))
    grep -qi "$marker" "$RESULTS/baseline-${pname}.txt" \
      && baseline_hits=$((baseline_hits + 1))
    grep -qi "$marker" "$RESULTS/ablation-${pname}.txt" \
      && ablation_hits=$((ablation_hits + 1))
  done < <(extract_markers "$probe")

  drop=$((baseline_hits - ablation_hits))
  [ "$drop" -le 0 ] && severity="none" \
    || { [ "$drop" -eq 1 ] && severity="LOW" || severity="HIGH"; }
  echo "$pname|$baseline_hits|$ablation_hits|$total|$drop|$severity"
done

6d. Emit Tier-2 report

## Ablation: <target-file> — YYYY-MM-DD HH:MM UTC

### Probe Results
| Probe | Baseline | Ablation | Markers | Drop | Severity |
|-------|:--------:|:--------:|:-------:|:----:|:--------:|
| probe-git-branch | 3/3 | 1/3 | 3 | 2 | HIGH |
| ...              |     |     |   |   |      |

### Verdict
SAFE TO CUT — all probes degraded ≤ 1 marker
  OR
SIGNAL DETECTED — N probe(s) degraded >1 marker; <target-file> earns its slot

Degradation threshold: SIGNAL DETECTED if any probe's ablation hits fall more than 1 below baseline hits. SAFE TO CUT otherwise.

7. Memory Protocol

mkdir -p "$HARNESS/memory/$TODAY"
cat >> "$HARNESS/memory/$TODAY/log.md" <<EOF

## [Context Audit] — $(date -u +%H:%M) UTC
- **Result**: OP
- **Budget**: Z tokens total (scored files + skill metadata)
- **Top finding**: <VERDICT> — <file> (<tokens> tokens, <citations> citations)
- **Ablation**: SAFE TO CUT | SIGNAL DETECTED | N/A
- **Observation**: [one sentence — the single most actionable finding]
EOF

See context/rules/memory.md for the canonical Memory Improvement Protocol.

Guidelines

• All Tier-1 scoring is deterministic — same shell commands twice produce the same scores. No LLM judgment in Tier 1.
• Tier-2 ablation uses trap to restore the target file even if claude -p errors mid-run.
• The skill-metadata aggregate row gets a budget line but no verdict (it's aggregate; verdicts apply per-file only).
• Tier-2 probe results are probabilistic, not deterministic — claude -p is non-deterministic. Run ablation twice if a verdict is borderline.
• For before/after token diff: the Memory log's Budget: line from each run is the comparison data point. No separate snapshot mechanism needed for the diff.
• When --baseline mode is used, probe outputs are persisted to memory/YYYY-MM-DD/context-audit-baseline/ and are gitignored (daily memory dirs are gitignored per .gitignore).
• Do not penalize CLAUDE.md on Dimension B (load-bearing) because it's the source of truth and may have few inbound citations by design — it doesn't need to be cited; it is the orchestrator instructions.

Reference

Verdict thresholds

Score	Verdict	Recommended action
7–8	KEEP	No action
5–6	TRIM	Edit for concision; remove duplicate sections
3–4	DEMOTE	Move to on-demand; remove from auto-load set
0–2	CUT	Remove; run Tier-2 ablation first if B score > 0

Probe file format

---
name: <identifier>
target: <rule-filename>   # which default-loaded file this probe exercises
markers:
  - <keyword or phrase that should appear when the rule is present>
  - ...
---

<Prompt text — what gets sent to claude -p. One task that requires the target rule to answer correctly.>

Ablation runner (standalone)

For running ablation outside a Claude session:

.claude/skills/context-audit/runner.sh --ablate context/rules/<file>.md

See runner.sh in this skill directory.

Scoring cheatsheet

Dimension	2 (healthy)	1 (warning)	0 (noise)
Footprint	< 500 tokens	500–1,500	> 1,500
Load-bearing	5+ citations	1–4 citations	0 citations
Integrity	0 broken refs	1–2 broken	3+ broken
Redundancy	no overlap	1 overlap file	2+ overlap files