Borrowing it
Nothing to install: this file belongs to Chachamaru127/codex-harness. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Chachamaru127/codex-harness/main/.codex/skills/_archived/harness-mem/SKILL.mdgit clone --depth 1 https://github.com/Chachamaru127/codex-harnessWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/chachamaru127/codex-harness/harness-mem)<a href="https://agentmods.dev/skills/chachamaru127/codex-harness/harness-mem"><img src="https://agentmods.dev/badge/skills/chachamaru127/codex-harness/harness-mem.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00070 | $0.01206 |
| Opus 5 | $0.00035 | $0.00603 |
| Sonnet 5 | $0.00014 | $0.00241 |
| Haiku 4.5 | $0.00007 | $0.00121 |
Grade C, and why
harness-mem scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -fsSL https://bun.sh/install | bash Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -fsSL https://bun.sh/install | bash How it starts
The opening of the file, as written. The whole thing — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Harness-Mem Skill
Customize Claude-mem for harness specifications to enhance cross-session quality and context maintenance.
Quick Reference
- "Integrate with Claude-mem" → this skill
- "Enable cross-session memory" → this skill
- "Set up harness-mem" → this skill
Deliverables
- Harness-specific mode settings for Claude-mem: Auto-record guardrail activations, Plans.md updates, and SSOT changes
- Cross-session learning: Utilize past mistakes and solutions in future sessions
- Japanese localization option: Record observations and summaries in Japanese
Prerequisites
Claude-mem plugin must be installed. If not installed, this skill will support the installation.
Execution Flow
Step 0: OS Detection
if [[ "$OSTYPE" == "msys" ]] || [[ "$OSTYPE" == "cygwin" ]] || [[ -n "$WINDIR" ]]; then
OS_TYPE="windows"
elif [[ "$OSTYPE" == "darwin"* ]]; then
OS_TYPE="mac"
else
OS_TYPE="linux"
fi
Step 1: Bun Installation Check
Claude-mem v7.3.7+ uses Bun-based workers.
if command -v bun &> /dev/null; then
echo "Bun is installed: $(bun --version)"
else
echo "Bun is not installed"
fi
If Bun not installed, offer installation:
macOS / Linux / WSL:
curl -fsSL https://bun.sh/install | bash
source ~/.bashrc
bun --version
Windows (PowerShell):
powershell -c "irm bun.sh/install.ps1 | iex"
# Or: npm install -g bun
bun --version
Step 2: Claude-mem Installation Check
if [ -d "$HOME/.claude/plugins/claude-mem" ]; then
echo "Claude-mem is installed"
else
echo "Claude-mem not found"
fi
If not installed:
Claude-mem is not installed.
Install now?
- Yes - Install from npm
- Manual - Show installation instructions
Step 3: Configure Harness Mode
Create/update .claude-mem.config.yaml:
# Harness-specific Claude-mem configuration
mode: harness
# Auto-recording settings
auto_record:
guardrail_activations: true
plans_updates: true
ssot_changes: true
review_results: true
# Learning settings
learning:
enabled: true
store_failures: true
store_solutions: true
# Localization
locale: ja # or 'en'
# Memory paths
paths:
observations: .claude/memory/observations.md
summaries: .claude/memory/summaries.md
decisions: .claude/memory/decisions.md
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 190 lines · 70 tokens per session scan C cb23d5264578
harness-mem is a skill published in the GitHub repository Chachamaru127/codex-harness (2 stars, last pushed 6mo ago), licensed MIT. It adds 70 tokens to every session and 1,206 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
media-ingest
Ingest video, audio, PDF, book, screenshot, and GitHub repo content into the brain. Multi-format handling with entity extraction and backlink propagation. Covers video-ingest, youtube-ingest, and book-ingest subtypes.
mem0-oss-to-platform
Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local Memory class) to the mem0 Platform / hosted / managed SDK (the MemoryClient class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g.…
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…
establishing-project-context
Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.