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 Bilal140202/the-lord-of-the-skills --skill agentcontrol-migrategit clone --depth 1 https://github.com/Bilal140202/the-lord-of-the-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/bilal140202/the-lord-of-the-skills/agentcontrol-migrate)<a href="https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/agentcontrol-migrate"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/agentcontrol-migrate/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/bilal140202/the-lord-of-the-skills/agentcontrol-migrate"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/agentcontrol-migrate.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 | $0.00096 | $0.13042 |
| Opus 5.5 | $0.00038 | $0.05217 |
| Sonnet 5.5 | $0.00019 | $0.02608 |
| Haiku 4.5 | $0.00010 | $0.01304 |
Grade A, and why
migrate 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 — 573 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Migrate to AgentControl
You're using a skill that will guide you through migrating an application from hardcoded LLM prompts to a full LaunchDarkly AgentControl implementation. Your job is to run the migration in five stages, stopping at each stage for the user to confirm:
- Audit the code — read-only scan that produces a structured list of everything hardcoded (prompt, model, parameters, tools, app-scoped knobs).
- Wrap the call — install the SDK, create the config in LaunchDarkly with a fallback that mirrors the hardcoded values, and rewrite the call site to fetch the config fresh on every request.
- Move the tools — extract each tool's JSON schema, attach it to the config, and swap every call site that references the old tool list.
- Add tracking — wire the per-request tracker (duration, tokens, success/error) around the provider call.
- Attach evaluators — either offline evals via the Playground + Datasets, or online judges that score sampled traffic automatically.
⚠️ Three first-run failure modes to avoid.
- Tracker in the wrong scope. For an agent with a loop, mint
create_tracker()once per user turn in asetup_runentry node — not insidecall_model. Per-iteration factory calls produce NrunIds and trip the at-most-once guards. See agent-mode-frameworks.md § CustomStateGraph.load_chat_modelwrapper reuse. Templates likelangchain-ai/react-agentship aload_chat_model(f"{provider}/{name}")helper that wrapsinit_chat_model(...)and silently drops every variation parameter. Delete it (don't just avoid using it) and replace call sites withcreate_langchain_model(ai_config).- Fallthrough not flipped after
/configs-create. A freshly-created config's fallthrough points at an auto-generated disabled variation, so the SDK returnsenabled=Falseuntil/configs-targetingruns. Flip it before Stage 2 verification.
Coverage — which shapes are well-trodden vs require extrapolation
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 · 573 lines · 96 tokens per session scan A d9f10d1d5553
migrate is a skill published in the GitHub repository Bilal140202/the-lord-of-the-skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 96 tokens to every session and 13,042 once invoked, about $0.0004 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 2026-09-06.
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