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evaluate-agent-framework

pjt222
업데이트됨 2 days ago
5 조회
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디자인aidesign

정보

이 스킬은 커뮤니티 건강도, 대체 위험성, 아키텍처, 거버넌스를 분석하여 오픈소스 AI 에이전트 프레임워크의 투자 적합성을 평가합니다. 엔지니어링 자원 할당을 안내하기 위해 4단계 분류(투자, 추가 평가, 신중한 기여, 회피)를 출력합니다. 상당한 개발 노력을 투입하기 전에 프레임워크의 장기적 생존 가능성을 평가하는 데 사용하세요.

빠른 설치

Claude Code

추천
기본
npx skills add pjt222/agent-almanac -a claude-code
플러그인 명령대체
/plugin add https://github.com/pjt222/agent-almanac
Git 클론대체
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/evaluate-agent-framework

Claude Code에서 이 명령을 복사하여 붙여넣어 스킬을 설치하세요

문서

Evaluate Agent Framework

Score OSS agent framework → invest? Steps 2-3 novel: survival rate + supersession. Tier → INVEST / EVALUATE-FURTHER / CONTRIBUTE-CAUTIOUSLY / AVOID. Calibrate effort pre-commit.

Use When

  • Adopt framework prod? → check
  • Dep risk on framework → assess
  • Send eng effort to ext proj? → decide
  • Build-vs-adopt cmp → rank
  • Post-release / post-gov-change / post-acq re-eval

In

  • Req: framework_url — GitHub repo URL
  • Opt:
    • comparison_frameworks — alt framework URLs, bench
    • use_case — intended use (e.g., "multi-agent orchestration", "tool-use pipelines") → arch fit
    • contribution_budget — planned eng hrs → tier calib

Do

Step 1: Census

Size, activity, landscape → before deeper probe.

  1. Read README.md, CONTRIBUTING.md, LICENSE, arch docs (docs/, ARCHITECTURE.md)
  2. Quant metrics:
    • Stars/forks/issues/PRs → gh repo view <repo> --json stargazerCount,forkCount,issues,pullRequests
    • Dependents → GitHub "Used by" or gh api repos/<owner>/<repo>/dependents
    • Release cadence → gh release list --limit 10 — freq + semver?
  3. Bus factor → top 5 contribs last 12mo by commit. Top >60% → crit low
  4. Landscape:
    • Pioneer: first mover → defines cat (high infl, high supersession risk to followers)
    • Fast-follower: <6mo post-pioneer → iterate
    • Late entrant: post-stabilization → cmp on feat/gov
  5. comparison_frameworks given → same metrics each alt

→ Census tbl: stars, forks, deps, cadence, bus factor, landscape (+cmps).

If err: private/rate-limited → manual README. No metrics (self-hosted GitLab) → note gap, qual only.

Step 2: Community Health

Welcome/support/retain externals?

  1. External survival rate:
    • Last 50 closed PRs → gh pr list --state closed --limit 50 --json author,mergedAt,closedAt,labels
    • Author internal (org) vs external
    • survival_rate = merged_external_PRs / total_external_PRs
    • Healthy >50%; concern <30%
  2. Responsiveness:
    • Issue first-response: median issue-open → first maintainer comment
    • PR merge latency: median ext PR open → merge
    • Healthy <7d resp, <30d merge; concern >30d resp
  3. Contributor diversity:
    • Ext/int ratio last 6mo
    • Unique externals w/ >=2 merged PRs (repeat → healthy eco)
  4. Gov artifacts:
    • CONTRIBUTING.md exists + actionable (not just "submit a PR")
    • CODE_OF_CONDUCT.md exists
    • Gov docs → decision process
    • Issue/PR templates guide contribs

→ Scorecard: survival, resp times, diversity, gov checklist.

If err: PR data thin (<20 closed) → note sample, weight others. Non-GitHub → adapt queries to platform API.

Step 3: Supersession Risk

Ext contribs → obsoleted by internal dev? Biggest risk.

  1. Sample last 50-100 merged ext PRs (or all if fewer)
  2. Each merged ext PR, later:
    • Reverted: explicit revert ref PR
    • Rewritten: same file/module changed <90d by internal
    • Obsoleted: feat removed/replaced next release
  3. supersession_rate = (reverted + rewritten + obsoleted) / total_merged_external
  4. Roadmap vs ext-active areas:
    • High overlap → high supersession (int builds over ext)
    • Low overlap → lower risk (ext fill gaps int won't)
  5. "Contrib traps": look friendly, scheduled for int rewrite
  6. Bench: NemoClaw → 71% ext PRs superseded <6mo. Calib pt.

→ Supersession % + breakdown (reverted/rewritten/obsoleted). Roadmap overlap.

If err: shallow/squash-merged (attrib lost) → est by ext PR paths vs files changed next releases. Lower confidence.

Step 4: Architecture Alignment

Arch supports use case w/o lock-in?

  1. Extension pts:
    • Plugin API → documented?
    • Config surface → customize no-fork?
    • Hook/callback → intercept behavior?
  2. Lock-in:
    • Rewrite cost: migrate-away est (d/wk/mo)
    • Data portability: export std fmt?
    • Std compliance: agentskills.io, MCP, A2A vs proprietary?
  3. API stability:
    • Breaking changes/major (CHANGELOG, migration guides)
    • Deprecation policy (advance warn)
    • Semver compliance (breaking → major only)
  4. Use case fit:
    • use_case given → arch natural fit?
    • Arch mismatches → workarounds req?
  5. Interop:
    • agentskills.io compat (skill model)
    • MCP (tool integration)
    • A2A (agent-to-agent)

→ Arch report: ext pts, lock-in (low/med/high), API stability, use-case fit.

If err: sparse docs → derive from code + public API. Too young for stability hist → note, weight gov more.

Step 5: Governance + Sustainability

Gov model → long-term viable? Fair to externals?

  1. Gov model:
    • BDFL: single decider → fast, bus factor risk
    • Committee/Core team: distributed → slower, resilient
    • Foundation-backed: Apache, Linux Foundation, CNCF → most sustainable
    • Corporate-controlled: one co → rug-pull risk
  2. Funding:
    • VC, corp, grants, community, unfunded
    • Full-time maintainers >=2 healthy; 0 red flag
    • Revenue → how sustain?
  3. Contributor protections:
    • License: permissive (MIT, Apache-2.0) vs copyleft (GPL) vs custom
    • CLA → rights transfer that disadvantage?
    • Recog → credited in releases/changelogs/docs?
  4. Security:
    • SECURITY.md or equiv
    • Median CVE → patch time
    • Dep update (Dependabot, Renovate, manual)
  5. Trajectory:
    • Gov evolving (→ foundation)?
    • Recent leadership/acq/relicense?
    • Public maintainer-contributor conflicts?

→ Gov assess: model, sustainability (sustainable/at-risk/critical), protections, security.

If err: gov undocumented → absence = yellow flag. Check implicit: who merges, who closes, who releases.

Step 6: Classify

Synth → 4-tier + justifications + recs.

  1. Score each (1-5):
    • Community health: survival, resp, diversity
    • Supersession risk: rate, roadmap, traps (invert: low better)
    • Arch alignment: ext pts, lock-in, stability, fit
    • Gov sustainability: model, funding, protections, sec
  2. Thresholds:
    • INVEST (all >=4): healthy, low supersession (<20%), aligned, sustainable gov → safe adopt + contrib
    • EVALUATE-FURTHER (mixed, none <2): mixed signals → specific follow-ups, re-eval date
    • CONTRIBUTE-CAUTIOUSLY (any 2, none <2): high supersession (>40%) or gov concerns → limit to requested work, maintainer-approved scope, plugin/ext decoupled from core
    • AVOID (any 1): crit red flags — abandoned, hostile (<15% survival), bad license, rug-pull → no eng effort
  3. Write report:
    • Tier + 1-sentence rationale up front
    • Each dim score + evidence
    • contribution_budget given → how alloc hrs per tier
    • EVALUATE-FURTHER → specific Qs + timeline
    • CONTRIBUTE-CAUTIOUSLY → safe (plugins, docs, tests) vs risky (core)
  4. comparison_frameworks evaluated → cmp matrix, rank all

→ Classification report: tier, scores, evidence, actionable recs.

If err: data gaps block confident call → default EVALUATE-FURTHER, doc missing data + how to get. Never default INVEST when unsure.

Chk

  • Census: stars, forks, deps, cadence, bus factor, landscape
  • Community: survival, resp times, diversity, gov artifacts
  • Supersession: rate + breakdown (reverted/rewritten/obsoleted)
  • Arch: ext pts, lock-in, API stability, fit
  • Gov: model, funding, protections, security
  • Tier: INVEST / EVALUATE-FURTHER / CONTRIBUTE-CAUTIOUSLY / AVOID
  • Each score → specific evidence
  • Recs actionable + calib to budget (if given)
  • Data gaps + confidence limits doc'd

Traps

  • Popularity ≠ health: 50k stars + 1 maintainer < 2k stars + 15 active contribs. SPoF.
  • Skip supersession: most common ext-contrib failure. Welcoming community worthless if int overwrites ext.
  • Arch-only, ignore gov: pretty design fails w/ unsustainable or hostile gov.
  • EVALUATE-FURTHER ≠ AVOID: mixed = investigate, not reject. Set re-eval date + specific Qs.
  • Snapshot bias: metrics point-in-time. Declining proj w/ great current > improving proj w/ mediocre. Check 6-12mo trend.
  • CLA complacency: some CLAs transfer copyright → your work = their asset. Read text, not checkbox.
  • Single-framework anchor: no cmp → anything looks great/terrible. Bench at least 1 alt, even informal.

See

GitHub 저장소

pjt222/agent-almanac
경로: i18n/caveman-ultra/skills/evaluate-agent-framework
0
agentsagentskillsai-assisted-developmentclaude-codeskillsteams

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