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/aegntic/compound-engineering/slfggit clone --depth 1 https://github.com/aegntic/compound-engineeringWhat 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 | $0.00014 | $0.00288 |
| Opus 5 | $0.00007 | $0.00144 |
| Sonnet 5 | $0.00003 | $0.00058 |
| Haiku 4.5 | $0.00001 | $0.00029 |
Grade A, and why
slrj 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
Swarm-enabled LRJ. Run these steps in order, parallelizing where indicated.
Sequential Phase
/workflows:plan $ARGUMENTS/compound-engineering:deepen-plan/workflows:work— Use swarm mode: Make a Task list and launch an army of agent swarm subagents to build the plan. This is the default Ralph-driven execution path and should emit red, green, and post-refactor green evidence unless the plan declares an explicit exception.
Parallel Phase
After work completes, launch steps 4 and 5 as parallel swarm agents (both only need code to be written):
/workflows:review— spawn as background Task agent/compound-engineering:test-browser— spawn as background Task agent
Wait for both to complete before continuing.
Finalize Phase
/compound-engineering:resolve_todo_parallel— resolve any findings from the review/compound-engineering:feature-video— record the final walkthrough and add to PR- Output
<promise>DONE</promise>when video is in PR
Start with step 1 now.
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 · 34 lines · 14 tokens per session scan A 485007027d36
slrj is a command published in the GitHub repository aegntic/compound-engineering (2 stars, last pushed 2mo ago), licensed MIT. It adds 14 tokens to every session and 288 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
Professional equity research analysis with institutional-grade formatting.
cli-anything-web:list
List all available CLI-Anything-Web CLIs (installed and generated).
cli-anything-web:refine
Refine an existing cli-anything-web CLI by recording additional traffic and expanding command coverage. Invokes the gap-analyzer skill as its first step, then implements missing endpoints.
pi-code-review
Adversarial code review via Codex — break confidence in changes, not validate them.
review
Run a standard Gemini code review of recent git changes.
pi-ask-gemini
Ask Gemini a question — get Google's perspective alongside Claude's.