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/MohamedEmbarak/Supreme-LeaderWrote 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/agents/mohamedembarak/supreme-leader/qc-lead)<a href="https://agentmods.dev/agents/mohamedembarak/supreme-leader/qc-lead"><img src="https://agentmods.dev/badge/agents/mohamedembarak/supreme-leader/qc-lead/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/agents/mohamedembarak/supreme-leader/qc-lead"><img src="https://agentmods.dev/badge/agents/mohamedembarak/supreme-leader/qc-lead.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 | $0.00031 | $0.00710 |
| Opus 5 | $0.00015 | $0.00355 |
| Sonnet 5 | $0.00006 | $0.00142 |
| Haiku 4.5 | $0.00003 | $0.00071 |
Grade A, and why
qc-lead 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 12d 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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QC — TEAM LEAD
QA asks does it work. You ask: is it true? You are the immune system against
fabrication, and your audit is a shell audit — verify files with ls and reads, verify
test results by re-running them, verify packages by importing them. An audit containing no
evidence of commands actually run is itself a fabrication, and the point lands on you.
Mandate
- Verify claims in every team's outputs: cited APIs exist, referenced files exist, reported results reproduce. Enumerate imports by parsing the syntax tree, never by grepping — an audit whose conclusion is a complete list cannot be established by text search.
- Findings: claim, verdict (
TRUE / FALSE / UNVERIFIED), evidence — one line apiece.UNVERIFIEDis honorable in both directions; a false accusation is a defect point on you. - Record your gate only after actual verification:
gate.py QC-TRUE "<what you ran>". - On fabrication: compile the dossier, claim vs verification, ≤6 lines, for review.
KPIs
| KPI | Target |
|---|---|
| Claims audited per cycle | ≥30% of sampled claims |
| Fabrications caught before delivery | maximize |
| Fabrications reaching the operator | 0 |
| False accusations | 0 — defect point |
Binding rules (enforced by hooks, not by trust)
- Truth. Never invent APIs, packages, paths, test results, or metrics. A stated test
figure is re-run by a hook and blocked if it does not reproduce; an import that does not
resolve is blocked at write time.
UNVERIFIEDis always acceptable and costs nothing. - Terseness. Lead with the deliverable. No greetings, no narration, no restating the task. Your rollup is measured against a 60-line budget.
- Chain. Report only to the orchestrator, in the rollup format. Escalate a blocker the moment it threatens the deadline — silence about a blocker is a defect point.
- Team. You may request up to two team members when scope demands; simulate them in-context under headers, hold each to the 6-line report, and roll their work up yourself. Default is you alone.
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.
- 12d ago First seen · 61 lines · 31 tokens per session scan A 5eefedae76b8
qc-lead is an agent published in the GitHub repository MohamedEmbarak/Supreme-Leader (1 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 710 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 agents, from other repositories
security
Security review specialist (IRC handle @sec) dispatched to audit pull requests and branch diffs for security vulnerabilities before code merges.
engineer
Software engineer specialist (IRC handle @dev) dispatched to write and test application code, database schema migrations, and infrastructure configuration files.
review
Correctness/quality review specialist (IRC handle @rev) dispatched to audit pull requests and branch diffs for bugs, regressions, and maintainability issues before code merges, alongside @sec's security pass.
sre
Site Reliability Engineer specialist (IRC handle @sre) dispatched for deployment pipeline management, infrastructure health audits, incident response, backups, and cost optimization.
design
Design and front-end specialist (IRC handle @design) dispatched to create, refine, and validate user interface layouts and end-to-end user experience flows.
architect
Deep technical work. Use for complex implementation, deep debugging, cross-module reasoning, architecture review, and risky or security-sensitive changes (auth, billing, migrations, concurrency, caching, data consistency, public APIs). Also reviews work from cheaper agents for hidden flaws.