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 wan-huiyan/agent-traffic-control --skill parallel-impl-agent-dies-mid-stream-verify-working-treegit clone --depth 1 https://github.com/wan-huiyan/agent-traffic-controlWrote 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/wan-huiyan/agent-traffic-control/parallel-impl-agent-dies-mid-stream-verify-working-tree)<a href="https://agentmods.dev/skills/wan-huiyan/agent-traffic-control/parallel-impl-agent-dies-mid-stream-verify-working-tree"><img src="https://agentmods.dev/badge/skills/wan-huiyan/agent-traffic-control/parallel-impl-agent-dies-mid-stream-verify-working-tree/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/wan-huiyan/agent-traffic-control/parallel-impl-agent-dies-mid-stream-verify-working-tree"><img src="https://agentmods.dev/badge/skills/wan-huiyan/agent-traffic-control/parallel-impl-agent-dies-mid-stream-verify-working-tree.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 | $0.00498 | $0.02481 |
| Opus 5 | $0.00249 | $0.01241 |
| Sonnet 5 | $0.00100 | $0.00496 |
| Haiku 4.5 | $0.00050 | $0.00248 |
Grade A, and why
parallel-impl-agent-dies-mid-stream-verify-working-tree 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Parallel impl agent dies mid-stream — verify the working tree, not "completed"
Problem
You dispatch N foreground implementation agents in parallel (disjoint files). One comes
back with API Error: Response stalled mid-stream (or an empty/truncated report), and the
harness may even emit a background " completed (exit code 0)" line. If you trust that
and integrate, you ship a hole: the agent wrote NOTHING — its target route is untouched, no
test file exists, the todos it created for itself are all still pending.
Context / Trigger Conditions
- 2+ parallel
Agent/Taskimpl agents editing code in one repo. - One returns a stall/timeout/empty final message;
subagent_tokens~0; a "completed" status. - You're about to run a combined
git add/commit or a whole-repo check across both outputs.
Solution
- Reconcile claimed-vs-actual before integrating. For each agent:
git status --shortand grep its target for the expected change (e.g.grep -n generateChineseText route.ts). A missing edit + no new test file = the agent died; "completed (exit 0)" was the harness reporting the shell wrapper exited, NOT the work landing. - Don't try to revive a dead foreground agent — finish its task yourself. Unlike a credit-stall suspension, a mid-stream API death leaves no resumable state. You have full context; do it in the main loop (or redispatch a fresh agent with the same brief).
- It degrades gracefully because of the orchestration guardrails: agents do NOT commit
and do NOT run whole-repo type-check (avoids git-index races + cross-agent
tscfalse-positives on half-written files); the orchestrator does path-scopedgit add <exact files>per unit + the full check at integration. So the survivor's work is clean and committable independent of the casualty.
Variant: the agent died but the work SURVIVED (checkpointed pipelines)
The headline case above is the shared-file orchestration, where agents deliberately don't
commit — so a death means zero durable output. The inverse case is just as common and the
recovery is completely different: a long, single-owner pipeline agent whose stages each
git commit && git push before moving on. When that agent dies mid-stream, the finished stages
are already on the remote. Treating it like the headline case — redoing the task from
scratch — duplicates work and can clobber pushed commits.
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 · 163 lines · 498 tokens per session scan A b0a028f94792
parallel-impl-agent-dies-mid-stream-verify-working-tree is a skill published in the GitHub repository wan-huiyan/agent-traffic-control (3 stars, last pushed 5d ago), licensed MIT. It adds 498 tokens to every session and 2,481 once invoked, about $0.0025 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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