Agent Skills › theStrangeAdventurer/capstan › aider-polyglot-evals

aider-polyglot-evals

GitHub

运行和校准基于Aider Polyglot语料的编码代理评估，支持多模型对比、性能测量及公平基准测试，确保结果可复现。

.agents/skills/aider-polyglot-evals/SKILL.md theStrangeAdventurer/capstan

触发场景

需要比较不同编码代理或模型的性能运行标准化的代码能力基准测试检查评估结果的复现性和完整性

安装

npx skills add theStrangeAdventurer/capstan --skill aider-polyglot-evals -g -y

更多选项

非标准路径

npx skills add https://github.com/theStrangeAdventurer/capstan/tree/main/.agents/skills/aider-polyglot-evals -g -y

不安装直接使用

npx skills use theStrangeAdventurer/capstan@aider-polyglot-evals

指定 Agent (Claude Code)

npx skills add theStrangeAdventurer/capstan --skill aider-polyglot-evals -a claude-code -g -y

安装 repo 全部 skill

npx skills add theStrangeAdventurer/capstan --all -g -y

预览 repo 内 skill

npx skills add theStrangeAdventurer/capstan --list

SKILL.md

Frontmatter

{
    "name": "aider-polyglot-evals",
    "description": "Run, calibrate, compare, or inspect reproducible coding-agent evaluations using the open-source Aider Polyglot corpus. Use for a 12-task Capstan or OpenCode comparison, per-task upstream-test results, agent CPU\/RSS measurement, or a fair model\/agent benchmark without task-specific instructions."
}

Aider Polyglot evaluations

Use benchmarks/polyglot/scripts/run_eval.py as the canonical harness. Keep the corpus commit, mini-v2 task list, public prompt construction, timeouts, and upstream scorer unchanged while comparing configurations.

Prepare

From the repository root, run:
```
./benchmarks/polyglot/bootstrap.sh
./build.sh
```
Bootstrap clones Aider-AI/polyglot-benchmark into benchmarks/work/polyglot-benchmark, checks all required language toolchains, and checks out the pinned corpus revision.
Before spending model calls, run git status --short in both the Capstan repository and corpus. Refuse a dirty corpus. Record a dirty Capstan worktree as non-reproducible exploratory work, not a publishable result.
Put provider credentials in the environment, never in a committed file.
Confirm an agent's authentication with one neutral request before a full suite. Use fresh output directories outside the corpus.

Canonical comparison

For the published-style local comparison, use direct DeepSeek V4 Pro, medium reasoning, 240-second agent timeout, and sequential full suites:

Capstan: --provider deepseek --model deepseek-v4-pro
OpenCode: --model deepseek/deepseek-v4-pro --variant medium

First run the documented Capstan or OpenCode command in benchmarks/polyglot/README.md with --dry-run. Only remove --dry-run after checking corpus revision, task matrix, output directory, command, and model.

Run each complete 12-task suite three times in fresh r1, r2, and r3 output directories. Run suites sequentially; do not reuse partial output, selectively rerun failed tasks, or run comparison configurations concurrently.

Evaluation integrity

Give agents only the public exercise prompt. Never add solution paths, implementation hints, task-specific instructions, or agent-specific help.
Do not expose .meta or .docs to the agent workspace.
Score only upstream tests in the clean scoring copy. Agent exit status or self-reported success is not a pass.
Keep test timeout and task selection fixed. A changed task list, corpus, timeout, model, or harness is a new benchmark configuration.
Treat agent_timeout, agent_error, test_failure, and harness_error as distinct outcomes.
If the harness is defective, fix it and invalidate affected runs. Never edit CSV or summary results manually.

Results

Report score, grouped failure modes, per-task and aggregate wall time, CPU, peak RSS, corpus commit, clean revisions, agent versions, machine details, provider/model/reasoning settings, and paths to raw output. State that results are workload- and environment-specific; they are not a universal ranking.

Use benchmarks/polyglot/promptfoo/ only when an HTML report is requested. Promptfoo is an optional orchestration layer; run_eval.py owns task isolation and scoring. Read its README before use and keep a filled local config only at its ignored benchmarks/polyglot/promptfoo/config.local.yaml path.