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.
git clone --depth 1 https://github.com/lx-wnk/Agent-ContextWrote 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/commands/lx-wnk/agent-context/decision-review)<a href="https://agentmods.dev/commands/lx-wnk/agent-context/decision-review"><img src="https://agentmods.dev/badge/commands/lx-wnk/agent-context/decision-review.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 | $0.00010 | $0.00057 |
| Opus 5 | $0.00005 | $0.00028 |
| Sonnet 5 | $0.00002 | $0.00011 |
| Haiku 4.5 | $0.00001 | $0.00006 |
Grade A, and why
decision-review 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 7d 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.
What it actually says
Read .agent-context/decision-review-prompt.md and follow it exactly to review .agent-context/decisions.json. This is the manual trigger for the same review you can also schedule via /schedule.
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.
- 7d ago First seen · 6 lines · 10 tokens per session scan A 58eeca29a174
decision-review is a command published in the GitHub repository lx-wnk/Agent-Context (7 stars, last pushed 2d ago), licensed MIT. It adds 10 tokens to every session and 57 once invoked, about $0.0001 per session on Opus 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 commands, from other repositories
research-verify
Verify existing research findings against independent primary sources. Upgrades confidence from 'sources agree' to 'independently verified.'.
story-continue
Resume an interrupted story from where you left off.
review-pr-staging
Staging review mode — comprehensive review of staging branch before deploy to main.
forgedock-init
AI-powered forge.yaml config generator — scans codebase, queries GitHub, auto-fills all optional sections from detection.
security-audit
Periodic security posture audit — runs a scripted 4-phase checklist against repo files (not diffs), creates GitHub issues for confirmed findings.
adopt
Bootstrap an existing repo for ForgeDock — triage open issues, apply labels, suggest a starter milestone, and identify first /work-on candidates.