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Agent skill

Archestra Dev Bench Analysis

by archestra-ai in archestra-ai/archestra

Map-reduce a finished archestra-bench run into a Tier-1/Tier-2 improvement report using Claude subagents (same analysis as the Rust analyzer, no API key).

Custom licenceAuto-check passedAgent Workflows

Install Archestra Dev Bench Analysis

skills CLI
$ npx skills add archestra-ai/archestra --skill archestra-dev-bench-analysis -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install archestra-ai/archestra archestra-dev-bench-analysis --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/archestra-ai/archestra.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/archestra-dev-bench-analysis .claude/skills/archestra-dev-bench-analysis && rm -rf skills-src

Use ~/.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/

Facts

Skill name
archestra-dev-bench-analysis
GitHub stars
4.4k
Token cost
~1.4k tokens
SKILL.md length
670 words
Files
7
Skills in repo
23
Repo updated
First seen
Licence
Custom licence

At a glance

Map-reduce a finished archestra-bench run into a Tier-1/Tier-2 improvement report using Claude subagents (same analysis as the Rust analyzer, no API key).

  • Works in 5 steps: Prepare (deterministic: dir resolution +… → Map — one triage workflow → Validate + assemble (deterministic, in… → …
  • Tasks that involve Subagents
  • SKILL.md covers 1. Prepare (deterministic: dir…, 2. Map — one triage workflow, 3. Validate + assemble… and 4. Reduce — repo-grounded report, plus 1 more section
  • Runs JavaScript and Shell scripts from its folder; calls node and jq

What it does

Archestra Dev Bench Analysis is an agent skill from archestra-ai/archestra. Map-reduce a finished archestra-bench run into a Tier-1/Tier-2 improvement report using Claude subagents (same analysis as the Rust analyzer, no API key).

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files (for example `bin/prepare.sh` and `reference/prompts.md`).

It sits in Agent Workflows, covering Subagents. It works with Rust. The repository describes itself as: Enterprise AI Platform with guardrails, MCP registry, gateway & orchestrator.

When your agent uses it

  • Tasks that involve Subagents

Example prompts

  • “/archestra-dev-bench-analysis”

Requirements

  • Node.js
  • A Bash shell

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Prepare (deterministic: dir resolution + Rust prepare + arg shaping)
  2. Map — one triage workflow
  3. Validate + assemble (deterministic, in this loop)
  4. Reduce — repo-grounded report
  5. Report

What it can do on your machine

Read from SKILL.md and the folder at commit c2c44de. 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 script files (JavaScript and Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • node
    • jq

    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

Archestra Dev Bench Analysis loads about 1.4k tokens when it runs. Until then it costs about 46 tokens; SKILL.md has 670 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~46
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

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 670 words (~1,442 tokens).

“Map-reduce a finished archestra-bench run into a recommendations report, using Claude subagents for the judgment. The deterministic half (render + metrics + manifest) is done by the Rust archestra-bench prepare subcommand, so this skill reuses the analyzer's exact rendering, metrics…”

— opening of SKILL.md by archestra-ai, Custom licence
name
archestra-dev-bench-analysis
argument-hint
[run dir]

Read the full SKILL.md on GitHub

Files

SKILL.md and 6 other files in .agents/skills/archestra-dev-bench-analysis of archestra-ai/archestra.

  • SKILL.md
  • bin/prepare.sh
  • bin/render-triage.mjs
  • bin/render-triage.test.mjs
  • reference/prompts.md
  • workflows/crawl.mjs
  • workflows/map.mjs

Open the folder on GitHubat commit c2c44de

Compare with similar skills

Archestra Dev Bench Analysis 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.

Archestra Dev Bench Analysis compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Archestra Dev Bench Analysis this skillarchestra-ai/archestra4.4k—~1.4kAutomated safety check: PassCustom licence
Project Healthjezweb/claude-skills1.1k—~3kAutomated safety check: PassMIT
Rust Build Hygienenubjs/nub4.4k—~2.2kAutomated safety check: PassMIT
SDK Seamgridaco/grida2.7k—~5kAutomated safety check: PassApache-2.0
Orchestratornubjs/nub4.4k—~4.4kAutomated safety check: PassMIT
Golem Parallel Workers Rustgolemcloud/golem1.5k—~2.4kAutomated safety check: PassCustom licence

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  • Archestra Dev E2E

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Works with

Categories

Questions about Archestra Dev Bench Analysis

What does Archestra Dev Bench Analysis do?

Map-reduce a finished archestra-bench run into a Tier-1/Tier-2 improvement report using Claude subagents (same analysis as the Rust analyzer, no API key). Archestra Dev Bench Analysis is an agent skill from archestra-ai/archestra. Map-reduce a finished archestra-bench run into a Tier-1/Tier-2 improvement report using Claude subagents (same analysis as the Rust analyzer, no API key).

When should I use Archestra Dev Bench Analysis?

Archestra Dev Bench Analysis fits situations like: tasks that involve Subagents.

How do I install Archestra Dev Bench Analysis in Claude Code?

Run `npx skills add archestra-ai/archestra --skill archestra-dev-bench-analysis -a claude-code`. Or copy the skill folder (.agents/skills/archestra-dev-bench-analysis in archestra-ai/archestra) into .claude/skills/archestra-dev-bench-analysis in your project. Claude Code loads it when a task matches its description.

How do I install Archestra Dev Bench Analysis in Codex?

Run `npx skills add archestra-ai/archestra --skill archestra-dev-bench-analysis -a codex`. Or copy the skill folder (.agents/skills/archestra-dev-bench-analysis in archestra-ai/archestra) into .agents/skills/archestra-dev-bench-analysis in your project. Codex loads it when a task matches its description.

Can I use Archestra Dev Bench Analysis 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 archestra-ai/archestra --skill archestra-dev-bench-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/archestra-dev-bench-analysis, .gemini/skills/archestra-dev-bench-analysis, .github/skills/archestra-dev-bench-analysis and .opencode/skills/archestra-dev-bench-analysis in your project.

What does Archestra Dev Bench Analysis need to run?

Going by SKILL.md and its folder, Archestra Dev Bench Analysis needs JavaScript and a shell for the scripts in its folder and the command-line tools its instructions call (node and jq). Our summary lists: Node.js; A Bash shell.

Does Archestra Dev Bench Analysis 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 Archestra Dev Bench Analysis 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 Archestra Dev Bench Analysis use?

Archestra Dev Bench Analysis 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 Archestra Dev Bench Analysis use?

About 1.4k 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.

What are the alternatives to Archestra Dev Bench Analysis?

Skills that share tags, products or a category with Archestra Dev Bench Analysis: Project Health (jezweb/claude-skills, 1.1k stars), Rust Build Hygiene (nubjs/nub, 4.4k stars), SDK Seam (gridaco/grida, 2.7k stars) and Orchestrator (nubjs/nub, 4.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Archestra Dev Bench Analysis?

archestra-ai (a GitHub organization) maintains it in archestra-ai/archestra, which has 4,359 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on October 9, 2026.

Source: archestra-ai/archestra on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.