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agent-architecture-analysis

agent-architecture-analysis

github.com/existential-birdsAgent workflows85213 installsUpdated 11w ago
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About agent-architecture-analysis

A codebase review skill for assessing agent architectures against the 12-Factor Agents principles. It guides evidence-based scoring across 13 factors and produces findings, gaps, and improvement recommendations.

Key features

  1. 01Assess 13 agent architecture factors
  2. 02Search code and documentation for evidence
  3. 03Score compliance as Strong, Partial, or Weak
  4. 04Document gaps and actionable recommendations
  5. 05Use hard gates before assigning scores

Use cases

  1. 01Review an existing LLM-powered system
  2. 02Audit a production agent application
  3. 03Evaluate architecture choices for a new system
  4. 04Plan improvements to an agent codebase

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/existential-birds/beagle --skill agent-architecture-analysis

After installing, type/agent-architecture-analysisin Claude Code to confirm it loaded.

Bundled filesreferences/factors.md

Details

From the project README

12-Factor Agents Compliance Analysis

Reference: 12-Factor Agents

Input Parameters

ParameterDescriptionRequired
docs_pathPath to documentation directory (for existing analyses)Optional
codebase_pathRoot path of the codebase to analyzeRequired

Analysis Framework

The full per-factor rubric — principle, search patterns, file patterns, compliance criteria (Strong/Partial/Weak), and anti-patterns for each of the 13 factors — lives in references/factors.md. During the Analysis Workflow, read the relevant factor sections there for the search patterns to run and the criteria to score against.

#FactorFocus
1Natural Language to Tool CallsSchema-validated structured outputs from LLM
2Own Your PromptsPrompts as first-class, versioned, templated code
3Own Your Context WindowCustom formatting of history/state/tool results
4Tools Are Structured OutputsValidated JSON triggers deterministic code
5Unify Execution StateSingle state object merging execution + business state
6Launch/Pause/ResumeAPIs to launch, pause anywhere, resume
7Contact Humans with ToolsHuman contact as a structured tool call
8Own Your Control FlowCustom routing/retries, not framework defaults
9Compact Errors into ContextErrors fed back for self-healing + escalation
10Small, Focused AgentsNarrow responsibility, 3-10 steps each
11Trigger from AnywhereCLI/REST/WebSocket/chat/webhook entry points
12Stateless ReducerPure (state, input) -> (state, output) agents
13Pre-fetch ContextFetch likely-needed data upfront

See references/factors.md for the complete rubric for every factor above.


Output Format

Gate order: Do not assign Strong / Partial / Weak or treat recommendations as observed facts until Hard gates (after Analysis Workflow) are satisfied for the factors in scope.

Executive Summary Table
| Factor | Status | Notes |
|--------|--------|-------|
| 1. Natural Language -> Tool Calls | **Strong/Partial/Weak** | [Key finding] |
| 2. Own Your Prompts | **Strong/Partial/Weak** | [Key finding] |
| ... | ... | ... |
| 13. Pre-fetch Context | **Strong/Partial/Weak** | [Key finding] |

**Overall**: X Strong, Y Partial, Z Weak
Per-Factor Analysis

For each factor, provide:

  1. Current Implementation

    • Evidence with file:line references
    • Code snippets showing patterns
  2. Compliance Level

    • Strong/Partial/Weak with justification
  3. Gaps

    • What's missing vs. 12-Factor ideal
  4. Recommendations

    • Actionable improvements with code examples

Analysis Workflow

  1. Initial Scan

    • Run search patterns for all factors
    • Identify key files for each factor
    • Note any existing compliance documentation
  2. Deep Dive (per factor)

    • Read identified files
    • Evaluate against compliance criteria
    • Document evidence with file paths
  3. Gap Analysis

    • Compare current vs. 12-Factor ideal
    • Identify anti-patterns present
    • Prioritize by impact
  4. Recommendations

    • Provide actionable improvements
    • Include before/after code examples
    • Reference roadmap if exists
  5. Summary

    • Compile executive summary table
    • Highlight strengths and critical gaps
    • Suggest priority order for improvements

Hard gates (evidence before scores)

Run these in order. Do not skip ahead: each Pass is an objective condition you can check (paths on disk, citations present), not internal certainty.

  1. Scan gate — After the initial scan (workflow step 1), Pass: for every factor (1–13) you have either (a) ≥1 repo-relative path or glob hit to inspect, or (b) a one-line note with rationale (e.g. search command/output, or “no matches — codebase may omit this concern”). Empty hand-waving (“looks fine”) fails this gate.
  2. Evidence gate (per factor) — Before writing Strong / Partial / Weak for that factor, Pass: “Current Implementation” includes ≥1 citation with file path plus line range or short quoted snippet from codebase_path, or an explicit no evidence located statement after targeted reads. If evidence is missing after search, default that factor to Weak unless the criterion is clearly N/A (say why).
  3. Synthesis gate — Executive summary table and per-factor analysis sections, Pass: only after gates 1–2 are satisfied for the factors in scope. Recommendations may name new files or patterns only as proposals; they must not be presented as observed facts without matching citations from step 2.

Quick Reference: Compliance Scoring

ScoreMeaningAction
StrongFully implements principleMaintain, minor optimizations
PartialSome implementation, significant gapsPlanned improvements
WeakMinimal or no implementationHigh priority for roadmap

When to Use This Skill

  • Evaluating new LLM-powered systems
  • Reviewing agent architecture decisions
  • Auditing production agentic applications
  • Planning improvements to existing agents
  • Comparing frameworks or implementations

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