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 tushrv/local-llm-delegator --skill delegate-local-workergit clone --depth 1 https://github.com/tushrv/local-llm-delegatorWrote 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/tushrv/local-llm-delegator/delegate-local-worker)<a href="https://agentmods.dev/skills/tushrv/local-llm-delegator/delegate-local-worker"><img src="https://agentmods.dev/badge/skills/tushrv/local-llm-delegator/delegate-local-worker/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/tushrv/local-llm-delegator/delegate-local-worker"><img src="https://agentmods.dev/badge/skills/tushrv/local-llm-delegator/delegate-local-worker.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 | $0.00089 | $0.00674 |
| Opus 5 | $0.00044 | $0.00337 |
| Sonnet 5 | $0.00018 | $0.00135 |
| Haiku 4.5 | $0.00009 | $0.00067 |
Grade A, and why
delegate-local-worker 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 10d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Delegate to the local worker
Keep the primary model responsible for architecture, decomposition, scope,
security judgment, patch review, and final acceptance. Offload mechanical,
bounded implementation to local-llm-worker.
Decide before reading broadly
Inspect only enough repository structure, manifests, interfaces, or failing output to define the boundary. Do not load every implementation file into the primary context before delegating.
Delegate when all are true:
- The requested outcome and acceptance conditions are concrete.
- The change fits a narrow list of files or path globs.
- The returned diff can be reviewed completely.
- The project has
local-llm-worker.toml. - The
propose_patchandapply_patchMCP tools are available.
Keep work in the primary model when it determines architecture, changes trust or authentication boundaries, performs an ambiguous migration, spans many subsystems, handles secrets, or cannot be accepted from a bounded diff.
Delegate
- State the intended behavior and acceptance checks compactly.
- Select the narrowest useful
allowed_paths. Prefer exact files; use a small directory glob only when the target file is not yet known. - Call
propose_patchwith the absolute current repository path asworkspace_rootbefore independently implementing the change. Do not copy source files intosupporting_context; the worker reads allowed files itself. - Review every returned line, touched path, warning, and statistic. Reject unrelated behavior, unexplained changes, or an unexpectedly large proposal.
- If acceptable, call
apply_patchwith the returnedproposal_idand exactsha256. Never reconstruct or substitute the digest. - Review validation results and inspect the resulting workspace diff. The primary model remains accountable for correctness.
- On validation failure, either fix directly or request the one permitted repair using the failed proposal ID and identical path scope. Review the repair as a new proposal.
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.
- 10d ago First seen · 69 lines · 89 tokens per session scan A d34f0481961c
delegate-local-worker is a skill published in the GitHub repository tushrv/local-llm-delegator (0 stars, last pushed 1mo ago), licensed MIT. It adds 89 tokens to every session and 674 once invoked, about $0.0004 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.
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