@d-o-hub/memory-harness
AUniversal agent memory harness — record, replay, and benchmark real agent sessions. Use when testing memory system learning, generating test fixtures, or benchmarking CLI performance.
Install
agr install @d-o-hub/memory-harness --target claudeWrites 4 files into .claude/skills/, pinned to git-7a123218.
- .claude/skills/memory-harness/SKILL.md
- .claude/skills/memory-harness/evaluate-learning.sh
- .claude/skills/memory-harness/export-fixtures.sh
- .claude/skills/memory-harness/replay-trace.sh
Document
name: memory-harness description: "Universal agent memory harness — record, replay, and benchmark real agent sessions. Use when testing memory system learning, generating test fixtures, or benchmarking CLI performance." version: "1.0" category: testing
Memory Harness
Record, replay, and benchmark real agent sessions against do-memory-cli.
Modes
| Mode | Purpose | Command |
|---|---|---|
| record | Capture live session as JSON trace | During normal agent work |
| replay | Replay traces, measure latency | CI, benchmarking |
| evaluate | Run N traces, measure learning | Quality gates |
Record Mode
# Create trace file
TRACE_DIR=".memory-traces"
mkdir -p "$TRACE_DIR"
TRACE_FILE="$TRACE_DIR/$(date +%Y%m%d-%H%M%S)-$(echo "$TASK" | tr ' ' '-' | head -c 40).json"
# Create episode via CLI
EPISODE_ID=$(do-memory-cli --format json episode create --task "$TASK" --domain "$DOMAIN" 2>/dev/null | jq -r '.id')
# Write trace header
echo '{"version":"1.0","episode_id":"'$EPISODE_ID'","steps":[]}' > "$TRACE_FILE"
# Log steps (after each tool use)
do-memory-cli episode log-step "$EPISODE_ID" --tool "$TOOL" --action "$ACTION" --latency-ms "$MS" --success
# Complete episode
do-memory-cli episode complete "$EPISODE_ID" success
Replay Mode
# Single trace replay (script in skill directory)
bash .agents/skills/memory-harness/replay-trace.sh "$TRACE"
# All traces
for trace in .memory-traces/*.json; do bash replay-trace.sh "$trace"; done
Evaluate Mode
Measure learning effectiveness over N episodes:
- Pattern count should increase with more data
- Search latency should stay <100ms
- Retrieval relevance should improve
Tools to Record
| Tool | Record As |
|---|---|
| Read | read |
| Grep | grep |
| Edit | edit |
| Bash (cargo test) | test |
| Bash (cargo build) | build |
| Bash (git) | git |
Trace Format
{
"version": "1.0",
"episode_id": "...",
"steps": [{"tool":"read","action":"...","latency_ms":12,"success":true}]
}
Performance Targets
| Operation | Target |
|---|---|
| Episode create | < 50ms |
| Step logging | < 20ms |
| Episode complete | < 500ms |
| Search (100 episodes) | < 100ms |
Trustgrade A
- passBody integrity
Whether the stored document is plausibly the kind of file the artifact declares, rather than something fetched by mistake.
- passType matchnot applicable to this artifact type
Whether the artifact is really the kind of thing its metadata claims it is.
- passFreshness
How long since the source repository was last pushed to.
- passPrompt injection
Scans the artifact's own text for instructions aimed at your agent rather than at you.
- passLicense
Whether the source repository declares an SPDX license permissive enough to redistribute.
How the grade is calculated
Each check contributes 0 points when it passes, 1 when it warns, and 2 when it fails. The total maps to a letter:
- Aevery check passed
- Bone warning
- Ctwo warnings
- Dprompt injection or body integrity failed, or three warnings
- Fone of those failed, and something else is wrong
These are automated hygiene checks, not a security audit, and not a dependency or vulnerability scan. A grade of A means nothing was flagged — not that the artifact is safe.
Versions
git-7a12321885552026-07-31