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 agentmods add commands/naimkatiman/continuous-improvement/model-forwardgit clone --depth 1 https://github.com/naimkatiman/continuous-improvementWhat 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 | $0.00034 | $0.00172 |
| Opus 5 | $0.00017 | $0.00086 |
| Sonnet 5 | $0.00007 | $0.00034 |
| Haiku 4.5 | $0.00003 | $0.00017 |
Grade A, and why
model-forward 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 2d 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
/model-forward
Load the model-forward skill and apply its stance to the current session.
- Restate the two invariants: goal-driven execution (anchor on the highest stated goal) and self-discipline guardrails (the 7 Laws).
- Audit the current task for places where custom scaffolding fights a native Claude Code capability; list each with the native alternative.
- Apply the decision rules from the skill before adding any new skill, hook, or wrapper to the workflow.
- Close with one line naming which native capability was preferred, which scaffold (if any) was proposed for retirement, and that the operator decides.
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.
- 2d ago First seen · 14 lines · 34 tokens per session scan A 84417c34be46
model-forward is a command published in the GitHub repository naimkatiman/continuous-improvement (7 stars, last pushed 7d ago), licensed MIT. It adds 34 tokens to every session and 172 once invoked, about $0.0002 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
coder-eval-implement-plan
Implement an approved codereval plan phase by phase with risk-scaled per-phase review, then a final code review.
OPSX: Bulk Archive
Archive multiple completed changes at once.
VibeGuard: Cross Review
Dual-model adversarial review — Claude generates review reports, Codex does adversarial verification, and iterates until convergence.
safe-build
Build the application for development or production.
auto-run
PitWay: Manage auto-run authorization for automatic task continuation.
task-integrate
PitWay: Apply a dispatched task's worktree commit to the main tree.