Agent Builder
shareAI-lab/learn-claude-code
Design and build AI agents for any domain. An agent skill from shareAI-lab/learn-claude-code.
A skill your agent uses to design, run, or review performance work with reproducible A/B baselines.
Install Performance Ab Benchmark Review
$ npx skills add bbartling/open-fdd --skill performance-ab-benchmark-review -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install bbartling/open-fdd performance-ab-benchmark-review --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/bbartling/open-fdd.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/performance-ab-benchmark-review .claude/skills/performance-ab-benchmark-review && 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 "performance-ab-benchmark-review" agent skill from https://github.com/bbartling/open-fdd/tree/master/.agents/skills/performance-ab-benchmark-review into .claude/skills/performance-ab-benchmark-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-ab-benchmark-review", 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/bbartling/open-fdd/tree/master/.agents/skills/performance-ab-benchmark-reviewType 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 bbartling/open-fdd --skill performance-ab-benchmark-review -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install bbartling/open-fdd performance-ab-benchmark-review --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/bbartling/open-fdd.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/performance-ab-benchmark-review .agents/skills/performance-ab-benchmark-review && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "performance-ab-benchmark-review" agent skill from https://github.com/bbartling/open-fdd/tree/master/.agents/skills/performance-ab-benchmark-review into .agents/skills/performance-ab-benchmark-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-ab-benchmark-review", 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 bbartling/open-fdd --skill performance-ab-benchmark-review -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install bbartling/open-fdd performance-ab-benchmark-review --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/bbartling/open-fdd.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/performance-ab-benchmark-review .cursor/skills/performance-ab-benchmark-review && 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 "performance-ab-benchmark-review" agent skill from https://github.com/bbartling/open-fdd/tree/master/.agents/skills/performance-ab-benchmark-review into .cursor/skills/performance-ab-benchmark-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-ab-benchmark-review", 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/bbartling/open-fdd.git --path .agents/skills/performance-ab-benchmark-review--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 bbartling/open-fdd --skill performance-ab-benchmark-review -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install bbartling/open-fdd performance-ab-benchmark-review --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/bbartling/open-fdd.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/performance-ab-benchmark-review .gemini/skills/performance-ab-benchmark-review && 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 "performance-ab-benchmark-review" agent skill from https://github.com/bbartling/open-fdd/tree/master/.agents/skills/performance-ab-benchmark-review into .gemini/skills/performance-ab-benchmark-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-ab-benchmark-review", 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 bbartling/open-fdd performance-ab-benchmark-reviewInstalls 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 bbartling/open-fdd --skill performance-ab-benchmark-review -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/bbartling/open-fdd.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/performance-ab-benchmark-review .github/skills/performance-ab-benchmark-review && 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 "performance-ab-benchmark-review" agent skill from https://github.com/bbartling/open-fdd/tree/master/.agents/skills/performance-ab-benchmark-review into .github/skills/performance-ab-benchmark-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-ab-benchmark-review", 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 bbartling/open-fdd --skill performance-ab-benchmark-review -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install bbartling/open-fdd performance-ab-benchmark-review --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/bbartling/open-fdd.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/performance-ab-benchmark-review .opencode/skills/performance-ab-benchmark-review && 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 "performance-ab-benchmark-review" agent skill from https://github.com/bbartling/open-fdd/tree/master/.agents/skills/performance-ab-benchmark-review into .opencode/skills/performance-ab-benchmark-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-ab-benchmark-review", 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.
Facts
- Skill name
performance-ab-benchmark-review- GitHub stars
- 173
- Token cost
- ~1.4k tokens
- SKILL.md length
- 580 words
- Files
- 3 (incl. references)
- Skills in repo
- 23
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
A skill your agent uses to design, run, or review performance work with reproducible A/B baselines.
- Works in 5 steps: Objective: one sentence describing the… → Scope: files, folders, PR diff,… → Constraints: read-only vs write,… → …
- Review performance work with reproducible A/B baselines
- SKILL.md covers Trigger, Non-goals, Operating principles and Subagent orchestration rules, plus 8 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Performance Ab Benchmark Review is an agent skill from bbartling/open-fdd. Use to design, run, or review performance work with reproducible A/B baselines. Delegates benchmark inventory, profiling, correctness guardrails, and result interpretation to subagents.
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/output-contracts.md` and `references/severity-rubric.md`).
It sits in AI & LLM Engineering, covering Subagents. The repository describes itself as: Fault Detection Diagnostics (FDD) for HVAC datasets.
When your agent uses it
- Review performance work with reproducible A/B baselines
- Tasks that involve Subagents
Example prompts
- “/performance-ab-benchmark-review”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Objective: one sentence describing the question to answer.
- Scope: files, folders, PR diff, services, packages, or docs to inspect.
- Constraints: read-only vs write, commands allowed, network/doc lookup allowed, and timeout.
- Required evidence: exact files/symbols/commands/sources to cite.
- Output schema: use the schema requested by the skill.
What it can do on your machine
Read from SKILL.md and the folder at commit 45b362a. It shows what the files ask for, not the result of running them.
Tool permissions
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.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Performance Ab Benchmark Review loads about 1.4k tokens when it runs, and up to ~1.9k if it reads all its reference files. Until then it costs about 54 tokens; SKILL.md has 580 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.
Safety
Auto-check passed
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.
SKILL.md
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 580 words (~1,384 tokens).
“When the user asks about optimization, benchmarking, latency, throughput, memory, profiling, regression baselines, A/B comparison, or performance PR review.”
- name
- performance-ab-benchmark-review
Files
SKILL.md and 2 other files (references) in .agents/skills/performance-ab-benchmark-review of bbartling/open-fdd.
- SKILL.md
- references/output-contracts.md
- references/severity-rubric.md
Open the folder on GitHubat commit 45b362a
Compare with similar skills
Performance Ab Benchmark Review 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 |
|---|---|---|---|---|---|---|
| Performance Ab Benchmark Review this skillbbartling/open-fdd | 173 | — | ~1.4k | Automated safety check: Pass | Custom licence | |
| Agent BuildershareAI-lab/learn-claude-code | 78k | 5 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Prompt Template Authoringnicobailon/pi-prompt-template-model | 321 | — | ~1.3k | Automated safety check: Pass | MIT | |
| AutobahnLilMGenius/paperthin | 1.1k | — | ~2.1k | Automated safety check: Pass | MIT | |
| Langgraph Agent Patternssoba-labs/langchain-agent-skills | 107 | — | ~3.6k | Automated safety check: Pass | MIT | |
| Analyze Runget-convex/convex-evals | 130 | — | ~2.1k | Automated safety check: Pass | Apache-2.0 |
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Carve guardrail-adjacent items out of scope with safe alternatives before risk-adjacent work starts, then run the safe remainder at full strength in a fresh subagent that only ever sees the carved…
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Implement multi-agent coordination patterns (supervisor-subagent, router, orchestrator-worker, handoffs) for LangGraph applications.
Analyze Run
get-convex/convex-evals
Analyze all failures in a convex-evals run, spawning parallel sub-agents to investigate each failure and producing a report with classifications and recommendations.
Instruction Tuning
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Use sub-agents as test subjects to iteratively improve .claude/ instruction files.
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Related
Categories
Questions about Performance Ab Benchmark Review
What does Performance Ab Benchmark Review do?
A skill your agent uses to design, run, or review performance work with reproducible A/B baselines. Performance Ab Benchmark Review is an agent skill from bbartling/open-fdd. Use to design, run, or review performance work with reproducible A/B baselines.
When should I use Performance Ab Benchmark Review?
Performance Ab Benchmark Review fits situations like: review performance work with reproducible A/B baselines; tasks that involve Subagents.
How do I install Performance Ab Benchmark Review in Claude Code?
Run `npx skills add bbartling/open-fdd --skill performance-ab-benchmark-review -a claude-code`. Or copy the skill folder (.agents/skills/performance-ab-benchmark-review in bbartling/open-fdd) into .claude/skills/performance-ab-benchmark-review in your project. Claude Code loads it when a task matches its description.
How do I install Performance Ab Benchmark Review in Codex?
Run `npx skills add bbartling/open-fdd --skill performance-ab-benchmark-review -a codex`. Or copy the skill folder (.agents/skills/performance-ab-benchmark-review in bbartling/open-fdd) into .agents/skills/performance-ab-benchmark-review in your project. Codex loads it when a task matches its description.
Can I use Performance Ab Benchmark Review in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add bbartling/open-fdd --skill performance-ab-benchmark-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/performance-ab-benchmark-review, .gemini/skills/performance-ab-benchmark-review, .github/skills/performance-ab-benchmark-review and .opencode/skills/performance-ab-benchmark-review in your project.
What does Performance Ab Benchmark Review need to run?
SKILL.md names no scripts, command-line tools or credentials: Performance Ab Benchmark Review is instructions for the agent only.
Does Performance Ab Benchmark Review access the network?
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.
Is Performance Ab Benchmark Review safe to install?
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.
What licence does Performance Ab Benchmark Review use?
Performance Ab Benchmark Review has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Performance Ab Benchmark Review use?
About 1.4k tokens (SKILL.md is roughly 5.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 473 tokens, read only when the agent opens those files.
What are the alternatives to Performance Ab Benchmark Review?
Skills that share tags, products or a category with Performance Ab Benchmark Review: Agent Builder (shareAI-lab/learn-claude-code, 78k stars), Prompt Template Authoring (nicobailon/pi-prompt-template-model, 321 stars), Autobahn (LilMGenius/paperthin, 1.1k stars) and Langgraph Agent Patterns (soba-labs/langchain-agent-skills, 107 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Performance Ab Benchmark Review?
bbartling (a GitHub user) maintains it in bbartling/open-fdd, which has 173 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on October 8, 2026.
Source: bbartling/open-fdd on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.