MCP Server Builder
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
Benchmark Signet memory with MemoryBench: regression-check Dreaming and recall changes, compare models, diagnose score drops, and record results; NOT for the prompt-submit latency benchmark.
Install Benchmarking
$ npx skills add Signet-AI/signetai --skill benchmarking -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Signet-AI/signetai benchmarking --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/Signet-AI/signetai.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/benchmarking .claude/skills/benchmarking && 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 "benchmarking" agent skill from https://github.com/Signet-AI/signetai/tree/main/.agents/skills/benchmarking into .claude/skills/benchmarking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchmarking", 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/Signet-AI/signetai/tree/main/.agents/skills/benchmarkingType 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 Signet-AI/signetai --skill benchmarking -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Signet-AI/signetai benchmarking --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Signet-AI/signetai.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/benchmarking .agents/skills/benchmarking && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "benchmarking" agent skill from https://github.com/Signet-AI/signetai/tree/main/.agents/skills/benchmarking into .agents/skills/benchmarking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchmarking", 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 Signet-AI/signetai --skill benchmarking -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Signet-AI/signetai benchmarking --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Signet-AI/signetai.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/benchmarking .cursor/skills/benchmarking && 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 "benchmarking" agent skill from https://github.com/Signet-AI/signetai/tree/main/.agents/skills/benchmarking into .cursor/skills/benchmarking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchmarking", 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/Signet-AI/signetai.git --path .agents/skills/benchmarking--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 Signet-AI/signetai --skill benchmarking -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Signet-AI/signetai benchmarking --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Signet-AI/signetai.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/benchmarking .gemini/skills/benchmarking && 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 "benchmarking" agent skill from https://github.com/Signet-AI/signetai/tree/main/.agents/skills/benchmarking into .gemini/skills/benchmarking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchmarking", 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 Signet-AI/signetai benchmarkingInstalls 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 Signet-AI/signetai --skill benchmarking -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Signet-AI/signetai.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/benchmarking .github/skills/benchmarking && 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 "benchmarking" agent skill from https://github.com/Signet-AI/signetai/tree/main/.agents/skills/benchmarking into .github/skills/benchmarking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchmarking", 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 Signet-AI/signetai --skill benchmarking -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Signet-AI/signetai benchmarking --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Signet-AI/signetai.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/benchmarking .opencode/skills/benchmarking && 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 "benchmarking" agent skill from https://github.com/Signet-AI/signetai/tree/main/.agents/skills/benchmarking into .opencode/skills/benchmarking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchmarking", 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
benchmarking- GitHub stars
- 304
- Token cost
- ~1.5k tokens
- SKILL.md length
- 786 words
- Files
- 14 (incl. scripts, references)
- Skills in repo
- 9
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Benchmark Signet memory with MemoryBench: regression-check Dreaming and recall changes, compare models, diagnose score drops, and record results; NOT for the prompt-submit latency benchmark.
- Agent Workflows work in your project
- SKILL.md covers When to Use, Workflows, Tools and Results ledger, plus 1 more section
- Runs TypeScript scripts from its folder; calls bun
What it does
Benchmarking is an agent skill from Signet-AI/signetai. Benchmark Signet memory with MemoryBench: regression-check Dreaming and recall changes, compare models, diagnose score drops, and record results; NOT for the prompt-submit latency benchmark.
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 17 other files, including scripts and reference files (for example `references/diagnosing-results.md`, `references/full-runs.md` and `references/model-portability.md`).
It sits in Agent Workflows. The repository describes itself as: Sync and store memories, shared identity files (AGENTS.md, CLAUDE.md), session transcripts, institutional knowledge, and secrets between all of your favorite harnesses and models.
When your agent uses it
- Agent Workflows work in your project
Example prompts
- “/benchmarking”
Requirements
- Node.js
What it can do on your machine
Read from SKILL.md and the folder at commit aa4c499. 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
Ships 6 files in scripts/ (TypeScript), which the agent can run.
Shell commands in SKILL.md call:
bun
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
Benchmarking loads about 1.5k tokens when it runs, and up to ~5.2k if it reads all its reference files. Until then it costs about 51 tokens; SKILL.md has 786 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: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NoteMentions a .env fileSKILL.md:46
Keys live in the gitignored `memorybench/.env`, which the bench loads itself; do not read it aloud or copy it elsewhere.
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); the scripts in this folder 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 786 words (~1,462 tokens).
“Signet's memory quality is measured with MemoryBench (memorybench/) running against an isolated Signet daemon. This skill covers the workflows for running and interpreting those benchmarks. web/docs/src/content/docs/benchmarking.md and memorybench/README.md own the command, flag, and benchmark documentation; read them rather than relying…”
- name
- benchmarking
Files
SKILL.md and 13 other files (scripts, references) in .agents/skills/benchmarking of Signet-AI/signetai.
- SKILL.md
- references/diagnosing-results.md
- references/full-runs.md
- references/model-portability.md
- references/regression-check.md
- results/ledger.jsonl
- results/samples/longmemeval-50-seed-1.txt
- results/samples/longmemeval-6-smoke.txt
- scripts/lib.ts
- scripts/pass-inspect.ts
- scripts/recall-eval.ts
- scripts/run-summary.ts
- scripts/sample-questions.test.ts
- scripts/sample-questions.ts
Open the folder on GitHubat commit aa4c499
Compare with similar skills
Benchmarking 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 |
|---|---|---|---|---|---|---|
| Benchmarking this skillSignet-AI/signetai | 304 | — | ~1.5k | Automated safety check: Notes | Custom licence | |
| MCP Server Builderanthropics/skills | 180k | 63 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Hook Development for Claude Code Pluginsanthropics/claude-plugins-official | 38k | 10 repos | ~4.1k | Automated safety check: Notes | Apache-2.0 | |
| Using Superpowersfarm-fe/farm | 5.6k | 35 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Executing Plans Inlineobra/superpowers | 297k | 2 repos | ~5.1k | Automated safety check: Pass | MIT | |
| Skill CreatorAzure/azqr | 795 | 89 repos | ~8.2k | Automated safety check: Pass | Apache-2.0 |
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Hook Development for Claude Code Plugins
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Explains how to write Claude Code plugin hooks, both prompt-based checks and bash commands, for events such as PreToolUse, Stop and SessionStart.
Using Superpowers
farm-fe/farm
A skill your agent uses when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
Executing Plans Inline
obra/superpowers
Has the agent carry out an implementation plan itself, task by task in the current session, keeping a ledger, proving each step with a test and ending with one whole-branch review.
- Official
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Create new skills, modify and improve existing skills, and measure skill performance.
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Explains how to write agents for Claude Code plugins: the markdown file with YAML frontmatter, trigger descriptions, model and color settings, and system prompt design.
More from Signet-AI/signetai
All 9 skills in this repoDreaming Development
Signet-AI/signetai
A skill your agent uses for Signet Dreaming development: inspect existing source, semantic-memory, retrieval, and inference architecture before changing it; prevent duplicate modules and ad-hoc…
Onboarding
Signet-AI/signetai
Interactive interview to set up your Signet workspace (~5-10 minutes).
Agents Md Sync
Signet-AI/signetai
Prune and route AGENTS.md trees for durable, high-signal context.
Benchmark Context
Signet-AI/signetai
Automatically benchmark your custom memory implementation against established systems like Supermemory.
Dreaming
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Maintain Signet's living ontology and memory substrate from transcripts, memory artifacts, source artifacts, notes, summaries, and imported records.
Provider SDK Upgrades
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Upgrade provider SDKs and refresh bundled model presets; NOT for unrelated provider architecture.
Related
Categories
Questions about Benchmarking
What does Benchmarking do?
Benchmark Signet memory with MemoryBench: regression-check Dreaming and recall changes, compare models, diagnose score drops, and record results; NOT for the prompt-submit latency benchmark. Benchmarking is an agent skill from Signet-AI/signetai. Benchmark Signet memory with MemoryBench: regression-check Dreaming and recall changes, compare models, diagnose score drops, and record results; NOT for the prompt-submit latency benchmark.
When should I use Benchmarking?
Benchmarking fits situations like: agent Workflows work in your project.
How do I install Benchmarking in Claude Code?
Run `npx skills add Signet-AI/signetai --skill benchmarking -a claude-code`. Or copy the skill folder (.agents/skills/benchmarking in Signet-AI/signetai) into .claude/skills/benchmarking in your project. Claude Code loads it when a task matches its description.
How do I install Benchmarking in Codex?
Run `npx skills add Signet-AI/signetai --skill benchmarking -a codex`. Or copy the skill folder (.agents/skills/benchmarking in Signet-AI/signetai) into .agents/skills/benchmarking in your project. Codex loads it when a task matches its description.
Can I use Benchmarking 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 Signet-AI/signetai --skill benchmarking -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/benchmarking, .gemini/skills/benchmarking, .github/skills/benchmarking and .opencode/skills/benchmarking in your project.
What does Benchmarking need to run?
Going by SKILL.md and its folder, Benchmarking needs TypeScript for the scripts in its folder and the command-line tools its instructions call (bun). Our summary lists: Node.js.
Does Benchmarking 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 Benchmarking safe to install?
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Benchmarking use?
Benchmarking 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 Benchmarking use?
About 1.5k tokens (SKILL.md is roughly 5.8k 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 3.7k tokens, read only when the agent opens those files.
What are the alternatives to Benchmarking?
Skills that share tags, products or a category with Benchmarking: MCP Server Builder (anthropics/skills, 180k stars), Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Executing Plans Inline (obra/superpowers, 297k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Benchmarking?
Signet-AI (a GitHub organization) maintains it in Signet-AI/signetai, which has 304 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on October 8, 2026.
Source: Signet-AI/signetai on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.