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/atlas

@965f4f9
by shingo imotasimota/agent-skills85 stars
15

Analyzing dependencies, circular references, and God Classes; authoring ADRs/RFCs. Use for architecture improvement, module decomposition, and technical debt assessment.

Use this Skill: https://skilld.dev/gh/simota/agent-skills/atlas

This session only. Nothing lands on disk.

referencecoupling-metrics.md

≈958 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Coupling and Architecture Health

Load for coupling, architecture health, or fitness-function design. Record module boundaries, graph scope, tool/version and evidence before scoring; raw import-line frequency is not a count of distinct dependent modules. Apply targets by role, not by globally minimizing a metric.

Core Metrics

Metric Definition Interpretation
Ca Count of distinct modules depending on this module Fan-in; a legitimate foundation may be high.
Ce Count of distinct modules this module depends on Fan-out.
I Ce / (Ca + Ce) Use 0 for an isolated node as this report's calculation convention; label it isolated rather than inferring stability from reuse.
A Abstract types / total types Bind abstract-type counting to the actual language. With no countable types, report N/A rather than inventing a fraction.
D abs(A + I - 1) Distance from A + I = 1; N/A when A is unavailable.
Classification Criterion Proposed action
Main Sequence D < 0.3 Preserve.
Acceptable drift 0.3 ≤ D < 0.5 Monitor.
Outside band D ≥ 0.5 Investigate against role and change evidence.
Zone of Pain A < 0.2 and I < 0.2 Stable abstraction / public-API boundary; check actual downstream impact.
Zone of Uselessness A > 0.8 and I > 0.8 Verify consumers; propose deletion via Void or connect a real consumer.
Unstable foundation I > 0.7 and Ca > 5 Reduce Ce or separate stable core from unstable extension.
Over-abstract A > 0.6 and Ca < 2 Check whether a real variant warrants the abstraction; otherwise route to Void.
Module role Target I Target A
Domain model/entities 0.0–0.2 0.6–0.9
Shared library/SDK 0.0–0.2 0.7–0.9
Service/application 0.3–0.6 0.3–0.5
Adapter/infrastructure 0.6–1.0 0.0–0.3
Entry point/CLI/UI 0.8–1.0 0.0–0.2

Small modules can have volatile ratios; declare the minimum sample size/exclusions. Do not classify a zone from I alone or treat every high-Ca foundation as defective.

Architecture Health / Fitness Targets

Use these existing Atlas review targets unless a justified project-specific target is declared. Distinguish warning/reporting targets from authorized blocking CI policy.

Metric Target
Ca / Ce per module Ca <20; Ce <10, interpreted with the role table
Instability bands 0.0–0.3 (stable) or 0.7–1.0 (flexible), subject to role
Distance D <0.3
Lines / functions per file <500 lines; <20 functions
Cyclomatic complexity <10 per function
Dependency depth <5 levels
Circular dependencies 0

Use the repository's configured module graph, AST counters and architecture rules. Confirm installed tool support rather than copying commands for another language. A function-length rule does not count functions per file; a suppressed analyzer error is not a passing fitness function. Define each new check's expected failure and test it against a known violation without overwriting existing CI/configuration.

Report

Required evidence: date/scope/tool, per-module Ca/Ce/I/A/D and role, zone distribution and named offenders, complexity actual/target/status, layer violations, debt categories and priority actions. For each proposal include the evidence, target, effort, handoff and fitness-function baseline/acceptance condition. Report unmeasured values as unmeasured; do not reuse fictional example counts or derive a zone from a metric the tool never computed.

Language-specific graph/API evidence: reference/module-boundary-evaluation.md. Cycle treatment: reference/circular-dependency-remediation.md.

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub13d

    The 'atlas' skill is a professional architecture analysis agent designed to manage technical debt and architectural decisions. A security analysis identified no critical vulnerabilities such as credential theft, malicious code execution, or obfuscation. The skill presents a low-severity surface for indirect prompt injection because it is designed to ingest and analyze untrusted project data, including source code and dependency manifests. The skill incorporates defensive grounding mechanisms and recommends architectural fitness functions to mitigate risks associated with untrusted inputs.

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  • Snyk13d

    Risk: LOW · No issues

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    1/13 files flagged

  • ZeroLeaks5mo

    Score: 93/100 · 2 sections analyzed

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Last checked against GitHub 2 days ago.

Activeupdated 2 weeks ago

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