Kubeshark Installer
kubeshark/kubeshark
Installs and configures Kubeshark on a Kubernetes cluster, choosing between the quick CLI path and a Helm install with custom values.
Materializes one evidence-backed proposal from a flexible knowledge-consult.md into a challenger-ready deploy-draft.yaml by applying only its selected DGD change to the current successful manifest.
$ npx skills add ai-dynamo/dynamo --skill create-optimization-hypothesis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ai-dynamo/dynamo create-optimization-hypothesis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ai-dynamo/dynamo.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/create-optimization-hypothesis .claude/skills/create-optimization-hypothesis && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "create-optimization-hypothesis" agent skill from https://github.com/ai-dynamo/dynamo/tree/main/.agents/skills/create-optimization-hypothesis into .claude/skills/create-optimization-hypothesis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-optimization-hypothesis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ai-dynamo/dynamo/tree/main/.agents/skills/create-optimization-hypothesisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ai-dynamo/dynamo --skill create-optimization-hypothesis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ai-dynamo/dynamo create-optimization-hypothesis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-dynamo/dynamo.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/create-optimization-hypothesis .agents/skills/create-optimization-hypothesis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "create-optimization-hypothesis" agent skill from https://github.com/ai-dynamo/dynamo/tree/main/.agents/skills/create-optimization-hypothesis into .agents/skills/create-optimization-hypothesis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-optimization-hypothesis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ai-dynamo/dynamo --skill create-optimization-hypothesis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ai-dynamo/dynamo create-optimization-hypothesis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-dynamo/dynamo.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/create-optimization-hypothesis .cursor/skills/create-optimization-hypothesis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "create-optimization-hypothesis" agent skill from https://github.com/ai-dynamo/dynamo/tree/main/.agents/skills/create-optimization-hypothesis into .cursor/skills/create-optimization-hypothesis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-optimization-hypothesis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ai-dynamo/dynamo.git --path .agents/skills/create-optimization-hypothesis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ai-dynamo/dynamo --skill create-optimization-hypothesis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ai-dynamo/dynamo create-optimization-hypothesis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-dynamo/dynamo.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/create-optimization-hypothesis .gemini/skills/create-optimization-hypothesis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "create-optimization-hypothesis" agent skill from https://github.com/ai-dynamo/dynamo/tree/main/.agents/skills/create-optimization-hypothesis into .gemini/skills/create-optimization-hypothesis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-optimization-hypothesis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ai-dynamo/dynamo create-optimization-hypothesisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ai-dynamo/dynamo --skill create-optimization-hypothesis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ai-dynamo/dynamo.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/create-optimization-hypothesis .github/skills/create-optimization-hypothesis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "create-optimization-hypothesis" agent skill from https://github.com/ai-dynamo/dynamo/tree/main/.agents/skills/create-optimization-hypothesis into .github/skills/create-optimization-hypothesis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-optimization-hypothesis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ai-dynamo/dynamo --skill create-optimization-hypothesis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ai-dynamo/dynamo create-optimization-hypothesis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-dynamo/dynamo.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/create-optimization-hypothesis .opencode/skills/create-optimization-hypothesis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "create-optimization-hypothesis" agent skill from https://github.com/ai-dynamo/dynamo/tree/main/.agents/skills/create-optimization-hypothesis into .opencode/skills/create-optimization-hypothesis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-optimization-hypothesis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
create-optimization-hypothesisMaterializes one evidence-backed proposal from a flexible knowledge-consult.md into a challenger-ready deploy-draft.yaml by applying only its selected DGD change to the current successful manifest.
Create Optimization Hypothesis is an agent skill from ai-dynamo/dynamo. Materializes one evidence-backed proposal from a flexible knowledge-consult.md into a challenger-ready deploy-draft.yaml by applying only its selected DGD change to the current successful manifest. Use after consult-perf-knowledge writes a proposed consultation in the current deployment iteration's next-candidate directory.
Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in DevOps & Cloud, covering Deployment. The repository describes itself as: A Datacenter Scale Distributed Inference Serving Framework. The licence is Apache-2.0.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 5e82beb. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
kubectlFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use kubectl, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Create Optimization Hypothesis loads about 1.8k tokens when it runs. Until then it costs about 89 tokens; SKILL.md has 855 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from ai-dynamo/dynamo at commit 5e82beb, republished under its Apache-2.0 licence (© ai-dynamo). 855 words, ~1,783 tokens.
.claude/skills/create-optimization-hypothesis/SKILL.md (or your agent's skills folder).<!--
SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
SPDX-License-Identifier: Apache-2.0
-->
Materialize an already-reasoned proposal. Treat knowledge-consult.md as a flexible reasoning record, not a rigid
schema. Do not select a different lever, broaden the proposal, deploy, benchmark, or approve it.
Require:
DEPLOY_ROOT;DEPLOY_ROOT/applied_manifests/deploy.yaml; andDEPLOY_ROOT/next-candidate/knowledge-consult.md written by consult-perf-knowledge.Use:
<EXP_ROOT>/artifacts/deploy-iter-<NNN>/next-candidate/as HYPOTHESIS_ROOT. The enclosing deploy-iter-<NNN> remains the analyzed source iteration. Do not create the next
deployment-iteration directory; recipe-deployer owns it after challenger approval.
Read the entire consultation. Keep its freedom of form: do not require a particular bullet order, table shape, or
subsection beyond the core Decision, Evidence, Proposed Change, and Materialization Handoff sections.
Inspect Decision first:
Status: no-proposal or Status: blocked, stop without creating deploy-draft.yaml.Status: proposed, continue only when the remaining content makes one candidate actionable.For a proposed candidate, require the consultation to communicate, anywhere in its relevant sections:
single-knob or coupled-bundle;Accept evidence and reasoning as concise prose or tables. Do not require the consultation to precompute YAML paths, current values, a source-to-draft diff, a separate validation plan, or a materialization-status field. Do not repeat the performance analysis or re-rank the selected lever. Count the evidence categories represented by the entries; do not rely only on the declared category count.
If the proposed target value, affected component, bundle membership, or intended mechanism is ambiguous, return the
consultation to consult-perf-knowledge. Do not choose a value, add a related optimization, or infer a broader
candidate.
Require the recorded source path to identify the current successful manifest. Recompute its SHA256 and require it to
match Source manifest SHA256 in Materialization Handoff. Then translate the selected proposal into the smallest
mechanical manifest edit:
DEPLOY_ROOT/applied_manifests/deploy.yaml.Use cited source or official documentation only to confirm the selected knob's syntax and placement. Do not use it to choose a different knob or target value. If the selected knob maps to multiple components or the requested state cannot be mapped unambiguously, stop and return the consultation.
Create ${HYPOTHESIS_ROOT}/deploy-draft.yaml from the exact successful source manifest:
knowledge-consult.md.Render and validate in a temporary file before replacing the final draft. If an existing deploy-draft.yaml already
has the same source hash and resolved semantic diff, validate and reuse it. If it differs, do not overwrite it; report
the conflict for review.
Before finalizing:
DynamoGraphDeployment resources;metadata.name;agent-docs/rules/optimization/one-variable.md;Perform local validation only. Do not mutate Kubernetes, run kubectl apply, use server-side dry run, launch a smoke
test, or run AIPerf.
After the final draft passes validation, update only the Materialization Handoff section of
knowledge-consult.md:
Draft manifest SHA256: pending with the final draft SHA256;Materialization result: created;Preserve the consultation's free-form reasoning and all evidence. Do not rewrite its Decision, Reasoning,
Evidence, or Proposed Change sections. Do not write separate hypothesis-ledger.md or hypothesis-ledger.json
files; knowledge-consult.md is the single reasoning and handoff record.
Return these two files to hypothesis-challenger:
${HYPOTHESIS_ROOT}/knowledge-consult.md;${HYPOTHESIS_ROOT}/deploy-draft.yaml.The draft is a proposal, not authorization to deploy.
© ai-dynamo, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .agents/skills/create-optimization-hypothesis of ai-dynamo/dynamo.
Open the folder on GitHubat commit 5e82beb
Create Optimization Hypothesis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Create Optimization Hypothesis this skillai-dynamo/dynamo | 8.2k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | |
| Kubeshark Installerkubeshark/kubeshark | 12k | — | ~3.6k | Automated safety check: Notes | Apache-2.0 | |
| GreptimeDB Dev Docker ImageGreptimeTeam/greptimedb | 6.7k | — | ~4k | Automated safety check: Notes | Apache-2.0 | |
| KubeSphere ServiceMesh Managerkubesphere/kubesphere | 17k | — | ~2.4k | Automated safety check: Pass | Custom licence | |
| Vercelremotion-dev/remotion | 62k | — | ~1.2k | Automated safety check: Pass | Custom licence | |
| AWS Cdk Developmentzxkane/aws-skills | 367 | 2 repos | ~2.5k | Automated safety check: Pass | MIT |
kubeshark/kubeshark
Installs and configures Kubeshark on a Kubernetes cluster, choosing between the quick CLI path and a Helm install with custom values.
GreptimeTeam/greptimedb
Packages a locally built GreptimeDB debug binary into a development-only Docker image for local-cluster testing, with an optional push to a dev registry.
kubesphere/kubesphere
Installs, checks and troubleshoots the KubeSphere ServiceMesh extension (Istio, Kiali, Jaeger), including grayscale release, sidecar injection, topology and tracing issues.
remotion-dev/remotion
Set up a Codex monitor for Vercel deployments and preview URLs.
zxkane/aws-skills
AWS Cloud Development Kit (CDK) expert for building cloud infrastructure with TypeScript/Python.
maslennikov-ig/claude-code-orchestrator-kit
Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup…
ai-dynamo/dynamo
Create self-contained interactive HTML code-review dashboards from GitHub or GitLab pull requests, checked-out branch diffs, or supplied unified diffs, with correctness and safe-to-merge scores…
ai-dynamo/dynamo
Knowledge of Fern's built-in MDX component library (accordions, callouts, cards, steps, tabs, code blocks, API-reference snippets, and more) for authoring docs pages.
ai-dynamo/dynamo
Knowledge of Fern's site-level navigation and structure configuration — how a docs site is organized in docs.yml (and product/version .yml files) using sections, pages, folders, tabs, tab variants…
ai-dynamo/dynamo
Drives persistent Claude Code, Codex, or OpenCode agent sessions through a Dynamo OpenAI/Anthropic-compatible endpoint over Agent Client Protocol (ACP).
ai-dynamo/dynamo
Benchmark and profile the Dynamo frontend (dynamo.frontend HTTP + tokenizer + KV router) against mock workers (dynamo.mocker).
ai-dynamo/dynamo
Selects and freezes a question-driven AIPerf workload, objective, load policy, and Kubernetes execution manifest for a successfully deployed Dynamo candidate.
Categories
Materializes one evidence-backed proposal from a flexible knowledge-consult.md into a challenger-ready deploy-draft.yaml by applying only its selected DGD change to the current successful manifest. Create Optimization Hypothesis is an agent skill from ai-dynamo/dynamo.yaml by applying only its selected DGD change to the current successful manifest.
Create Optimization Hypothesis fits situations like: tasks that involve Deployment.
Run `npx skills add ai-dynamo/dynamo --skill create-optimization-hypothesis -a claude-code`. Or copy the skill folder (.agents/skills/create-optimization-hypothesis in ai-dynamo/dynamo) into .claude/skills/create-optimization-hypothesis in your project. Claude Code loads it when a task matches its description.
Run `npx skills add ai-dynamo/dynamo --skill create-optimization-hypothesis -a codex`. Or copy the skill folder (.agents/skills/create-optimization-hypothesis in ai-dynamo/dynamo) into .agents/skills/create-optimization-hypothesis in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ai-dynamo/dynamo --skill create-optimization-hypothesis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/create-optimization-hypothesis, .gemini/skills/create-optimization-hypothesis, .github/skills/create-optimization-hypothesis and .opencode/skills/create-optimization-hypothesis in your project.
Going by SKILL.md and its folder, Create Optimization Hypothesis needs the command-line tools its instructions call (kubectl).
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Create Optimization Hypothesis is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Create Optimization Hypothesis: Kubeshark Installer (kubeshark/kubeshark, 12k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars), KubeSphere ServiceMesh Manager (kubesphere/kubesphere, 17k stars) and Vercel (remotion-dev/remotion, 62k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
ai-dynamo (a GitHub organization) maintains it in ai-dynamo/dynamo, which has 8,238 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on October 7, 2026.
Source: ai-dynamo/dynamo on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.