Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add cacheforge-ai/cacheforge-skills --skill context-engineergit clone --depth 1 https://github.com/cacheforge-ai/cacheforge-skillsWrote 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/cacheforge-ai/cacheforge-skills/context-engineer)<a href="https://agentmods.dev/skills/cacheforge-ai/cacheforge-skills/context-engineer"><img src="https://agentmods.dev/badge/skills/cacheforge-ai/cacheforge-skills/context-engineer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cacheforge-ai/cacheforge-skills/context-engineer"><img src="https://agentmods.dev/badge/skills/cacheforge-ai/cacheforge-skills/context-engineer.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00030 | $0.00675 |
| Opus 5.5 | $0.00012 | $0.00270 |
| Sonnet 5.5 | $0.00006 | $0.00135 |
| Haiku 4.5 | $0.00003 | $0.00068 |
Grade A, and why
context-engineer scanned grade A with 0 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 1mo 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to use this skill
Use this skill when the user wants to:
- Understand where their context window tokens are going
- Analyze workspace files (SKILL.md, SOUL.md, MEMORY.md, etc.) for bloat
- Audit tool definitions for redundancy and overhead
- Get a comprehensive context efficiency report
- Compare before/after snapshots to measure optimization progress
- Optimize system prompts for token efficiency
Commands
# Analyze workspace context files — token counts, efficiency scores, recommendations
python3 skills/context-engineer/context.py analyze --workspace ~/.openclaw/workspace
# Analyze with a custom budget and save a snapshot for later comparison
python3 skills/context-engineer/context.py analyze --workspace ~/.openclaw/workspace --budget 128000 --snapshot before.json
# Audit tool definitions for overhead and overlap
python3 skills/context-engineer/context.py audit-tools --config ~/.openclaw/openclaw.json
# Generate a comprehensive context engineering report
python3 skills/context-engineer/context.py report --workspace ~/.openclaw/workspace --format terminal
# Compare two snapshots to see projected token savings
python3 skills/context-engineer/context.py compare --before before.json --after after.json
What It Analyzes
- System prompt efficiency — Length, redundancy detection, compression potential
- Tool definition overhead — Count tools, per-tool token cost, identify unused/overlapping
- Memory file bloat — MEMORY.md size, stale entries, optimization suggestions
- Skill overhead — Installed skills contributing to context, per-skill token cost
- Context budget — What % of model context window is consumed by static content vs available for conversation
Options
--workspace PATH— Path to workspace directory (default:~/.openclaw/workspace)--config PATH— Path to OpenClaw config file (default:~/.openclaw/openclaw.json)--budget N— Context window token budget (default: 200000)--snapshot FILE— Save analysis snapshot to FILE for later comparison--format terminal— Output format (currently: terminal)
What ships with it
4 files 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.
- 1mo ago First seen · 72 lines · 30 tokens per session scan A b558be4337a6
context-engineer is a skill published in the GitHub repository cacheforge-ai/cacheforge-skills (10 stars, last pushed 8mo ago), licensed MIT. It adds 30 tokens to every session and 675 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
kayba-ace
This skill ships learnfromtraces.py, a script that reads OpenClaw session transcripts, feeds them through the ACE learning pipeline, and writes an updated skillbook to disk.
thread
Manage persistent context threads for cross-session work.
titen-memory
Use the Titen MCP server to recall bounded evidence-grounded context, record verified durable signals, submit feedback, and coordinate checkpoints, leases, or handoffs. Use when work may benefit from prior project memory or when a verified outcome should be preserved for another agent; do not use it to capture raw…
kmp-guide
Read KMP's brief agent entry, consult extended verbs and examples on demand, synchronize guide assets, and open the human guide in ChronoLoom. Use for guide setup, updates, or showing and explaining the guide.
kmp-doctor
Diagnose KMP binary, backend, selected store, tool surface, host wiring, and every kmp-mcp engine on this machine. Use when memory or KMP setup is missing, stale, duplicated, or failing.
kmp-uninstall
Preview or perform KMP removal while protecting memory and respecting plugin versus standalone ownership.