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SKILL verified MIT Self-run

Memory Harness

skill-d-o-hub-rust-self-learning-memory-memory-harness · by d-o-hub

Universal agent memory harness — record, replay, and benchmark real agent sessions. Use when testing memory system learning, generating test fixtures, or benchmarking CLI performance.

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Install

$ agentstack add skill-d-o-hub-rust-self-learning-memory-memory-harness

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

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 |

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.

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