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 DeepLink-org/probing --skill persistent_stragglergit clone --depth 1 https://github.com/DeepLink-org/probingWrote 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/deeplink-org/probing/persistent_straggler)<a href="https://agentmods.dev/skills/deeplink-org/probing/persistent_straggler"><img src="https://agentmods.dev/badge/skills/deeplink-org/probing/persistent_straggler/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/deeplink-org/probing/persistent_straggler"><img src="https://agentmods.dev/badge/skills/deeplink-org/probing/persistent_straggler.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00022 | $0.00426 |
| Opus 5.5 | $0.00009 | $0.00170 |
| Sonnet 5.5 | $0.00004 | $0.00085 |
| Haiku 4.5 | $0.00002 | $0.00043 |
Grade A, and why
persistent_straggler 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.
What it actually says
Persistent straggler (worst_fraction)
slow_rank 看 当前窗口里谁平均最慢；本 skill 看 谁在多少 step 上拿「最慢 rank」。
worst_fraction
对每个 rank 统计：在窗口内有多少 step 上，该 rank 的 collective 总耗时等于该 step 的最大值。
worst_fraction ≈ 1.0— 几乎每步都是最慢（ chronic straggler）worst_fraction ≈ 0.05— 偶发
Parameters
step_window(default300)worst_fraction_threshold(default0.25) —persistent_offenders步骤的过滤阈值use_global(defaulttrue)
用法
probing -t rank0:8080 skill run persistent_straggler --global
probing -t rank0:8080 skill run persistent_straggler --set worst_fraction_threshold=0.4 --set step_window=500
Related skills
- Job 整体变慢 →
job_health - 当前 step lag →
slow_rank - NCCL culprit/victim →
nccl_culprit_victim
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 46 lines · 22 tokens per session scan A 3e8d791714d8
persistent_straggler is a skill published in the GitHub repository DeepLink-org/probing (10 stars, last pushed 3d ago), licensed Apache-2.0. It adds 22 tokens to every session and 426 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
social-physics-filter
Unified boundary enforcement, interpersonal diagnostic, and relational audit engine. Absorbs 40 psychology + 2 social protocols and all relationship case studies.
cnsplots
Create, revise, and troubleshoot publication-ready scientific plots in Python with cnsplots, including distribution, regression, heatmap, genomics, survival, set, flow, and multi-panel figures. Use when a user asks for cnsplots code, Cell/Nature/Science-style visualization, precise physical figure dimensions…
pennylane
Builds and differentiates PennyLane quantum circuits, hybrid PyTorch or JAX models, molecular VQE and QAOA workflows. Use for variational quantum algorithms, quantum machine learning, simulator validation, and moving validated circuits to provider plugins. For hardware-specific compilation use qiskit or cirq; for…
typescript-testing
Select and run TypeScript SDK verification for packages, examples, type checks, linting, builds, Vitest suites, Effect v4 CLI tests, and runtime E2E tests. Use when adding tests, diagnosing TypeScript CI, choosing a focused test command, validating TypeScript package changes, or writing/porting CLI tests against…
cli-e2e
Write, modify, or debug Docker-based Composio CLI end-to-end tests under ts/e2e-tests/cli, including binary invocation, fixture isolation, output assertions, and package manifests. Use for CLI E2E test suites only; use cli-command for CLI source implementation.
pysr
Use when fitting equations to data with PySR or SymbolicRegression.jl, when a user wants an interpretable formula, symbolic model, scaling law, or empirical relation discovered from numeric data, or when debugging a PySR search that is slow, stuck, or giving poor equations.