Agent skill

Architectural Analysis

by testdouble in testdouble/han

Performs deep architectural analysis of a specified module, directory, or feature area by examining structural coupling, data flow, concurrency patterns, risk, and SOLID alignment.

MITAuto-check passedDevelopment

Install Architectural Analysis

skills CLI
$ npx skills add testdouble/han --skill architectural-analysis -a claude-code

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

GitHub CLI
$ gh skill install testdouble/han architectural-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/testdouble/han.git skills-src && mkdir -p .claude/skills && cp -r skills-src/han-coding/skills/architectural-analysis .claude/skills/architectural-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
architectural-analysis
GitHub stars
279
Token cost
~6.4k tokens
SKILL.md length
2,872 words
Files
2 (incl. references)
Skills in repo
54
Repo updated
First seen
Licence
MIT

At a glance

Performs deep architectural analysis of a specified module, directory, or feature area by examining structural coupling, data flow, concurrency patterns, risk, and SOLID alignment.

  • Works in 11 steps: Validate the Focus Area and Resolve… → Detect Signals and Classify Size → Build the Roster and Announce It → …
  • The user wants to assess
  • SKILL.md covers Project Context, Operating Principles, Step 1: Validate the Focus… and Step 2: Detect Signals and…, plus 9 more sections
  • Calls bash and git

What it does

Architectural Analysis is an agent skill from testdouble/han. Performs deep architectural analysis of a specified module, directory, or feature area by examining structural coupling, data flow, concurrency patterns, risk, and SOLID alignment. Use when the user wants to assess, evaluate, or review the architecture, design quality, dependency structure, coupling, cohesion, or technical debt of an existing part of the codebase. Not for investigating specific bugs, runtime errors, or failures — use investigate. Not for test planning — use automated-test-planning. Not for…

Its SKILL.md is about 6.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/architectural-analysis-report-template.md`).

It sits in Development, covering Domain-driven design, Test strategy and Technical debt. The repository describes itself as: Han: AI skills and agents for "Solo" product engineers and small teams. The licence is MIT.

When your agent uses it

  • The user wants to assess
  • Review the architecture
  • Dependency structure
  • Technical debt of an existing part of the codebase

Example prompts

  • “Use the architectural-analysis skill to perform deep architectural analysis of a specified module, directory, or feature area by examining…”
  • “/architectural-analysis”

Requirements

  • Pre-approved tools (allowed-tools): Read, Glob, Grep, Agent, Bash(find *), Bash(bash "${CLAUDE_PLUGIN_ROOT}/scripts/han-config-dir.sh")

Workflow steps

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

  1. Validate the Focus Area and Resolve Project Context
  2. Detect Signals and Classify Size
  3. Build the Roster and Announce It
  4. Dispatch the Discovery Wave in Parallel
  5. Compile the Discovery Findings
  6. Dispatch the Risk Analyst
  7. Dispatch the Synthesis Architects
  8. Render the Report
  9. Rewrite the Report for Readability
  10. Run the Readability Self-Check
  11. Present the Report

What it can do on your machine

Read from SKILL.md and the folder at commit abba73a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Glob
    • Grep
    • Agent
    • Bash(find *)
    • Bash(bash "${CLAUDE_PLUGIN_ROOT}/scripts/han-config-dir.sh")

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • bash
    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    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

Architectural Analysis loads about 6.4k tokens when it runs, and up to ~8.8k if it reads all its reference files. Until then it costs about 250 tokens; SKILL.md has 2,872 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~250
When it runs · the whole SKILL.md, loaded when a task matches
~6.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~8.8k

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

The full file from testdouble/han at commit abba73a, republished under its MIT licence (© testdouble). 2,872 words, ~6,392 tokens.

Download SKILL.mdSave it as .claude/skills/architectural-analysis/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
architectural-analysis
description
Performs deep architectural analysis of a specified module, directory, or feature area by examining structural coupling, data flow, concurrency patterns, risk, and SOLID alignment. Use when the user wants to assess, evaluate, or review the architecture, design quality, dependency structure, coupling, cohesion, or technical debt of an existing part of the codebase. Not for investigating specific bugs, runtime errors, or failures — use investigate. Not for test planning — use automated-test-planning. Not for file-level code review — use code-review. Not for researching open-ended options, prior art, or how something works — use research. Not for designing a new interface or contract — use design-an-api. Not for planning the change its findings imply — use plan-a-change. Not for discovering bounded contexts, ubiquitous language, or where code boundaries diverge from domain boundaries — use ddd-analysis. Not for writing documentation or architectural decision records.
allowed-tools
Read, Glob, Grep, Agent, Bash(find *), Bash(bash "${CLAUDE_PLUGIN_ROOT}/scripts/han-config-dir.sh")
arguments
size
argument-hint
[size: small | medium | large | dynamic] [focus area: module, directory, or feature to analyze]

Project Context

  • git installed: !which git 2>/dev/null || echo "not installed"
  • CLAUDE.md: !find . -maxdepth 1 -name "CLAUDE.md" -type f
  • project-discovery.md: !find . -maxdepth 3 -name "project-discovery.md" -type f
  • personal config directory: !bash "${CLAUDE_PLUGIN_ROOT}/scripts/han-config-dir.sh" 2>/dev/null || echo "$HOME/.claude"
  • project .han/config.md: !cat .han/config.md 2>/dev/null || echo ""

As your first action, use the Read tool on .han/config.md inside the personal config directory path above. A read that returns no file is no personal configuration: continue silently. When that file or the project .han/config.md probe supplies content, apply it per config-rule.md, which governs precedence between the two files, relative-path resolution, and what to do with a file that reads but cannot be used.

Operating Principles

Read these before dispatching anything. They constrain every step below.

  • A focus area is required. This skill analyzes a specific module, directory, or feature. "Analyze the whole codebase" is not a valid input. If no focus area resolves to real files, stop and ask the user to name one.
  • The agents own the judgment; the skill orchestrates. The skill validates the focus area, classifies size, selects the roster, fans agents out and in, and renders the report. It does not produce findings itself.
  • The discovery roster is signal-selected; the synthesis spine always runs. han-core:structural-analyst, han-core:behavioral-analyst, han-core:risk-analyst, and han-core:software-architect run at every size BECAUSE structure, runtime behavior, risk-of-inaction, and SOLID synthesis are the irreducible core of an architectural read. Every other specialist is added only when the focus area's signals warrant it and the size band allows it, BECAUSE dispatching an agent whose domain the code does not touch burns tokens and dilutes the report with low-signal findings.
  • Default to small. Start classification at small and escalate only when a higher-band signal is clearly present. Borderline signals stay at the smaller band. Under-dispatching is recoverable by re-running at a larger size; over-dispatching is not.
  • Recommendations, not refactors. The skill never modifies code. han-core:software-architect (and han-core:system-architect when dispatched) produce pseudocode sketches for proposed boundaries. Implementation is a separate, later step.
  • Negative results are valuable. When a dimension is genuinely clean (no concurrency in a pure-functional module, sound boundaries), the report says so. Agents must not fabricate findings to fill a section.
  • Single pass, no iteration round. This skill is a fan-out / fan-in, not an iterative loop. If a band proves too small, the user re-runs at a larger size — the skill does not self-escalate mid-run.
  • System-altitude work is deferred by default. han-core:software-architect defers cross-service / bounded-context / trust-boundary findings rather than absorbing them. han-core:system-architect is added to the roster only at large size and only when a boundary-crossing seam is actually present. When it is not dispatched, those deferrals are surfaced in the report so the user can dispatch han-core:system-architect separately.
  • The report template lives at references/architectural-analysis-report-template.md. The skill renders that template by filling placeholders and removing the sections whose agent was not dispatched. It does not invent a structure inline.
  • The synthesized report is written for a named reader. As the skill writes the final report's synthesized prose, it sources the shared standard by invoking han-communication:readability-guidance and applies it, holding one audience above the writing: the engineer weighing the module's design and deciding whether to change it. Scope that frame per section so the technical specifics that reader needs — file paths, finding IDs, exact conditions, pseudocode — are preserved, never simplified away.

Run an Architectural Analysis

Step 1: Validate the Focus Area and Resolve Project Context

Bind $size. If the user passed small, medium, large, or dynamic as the first positional argument, bind $size to it. Anything else is part of the focus-area context, not a size; bind $size to the literal none provided.

Resolve the focus area. Take the remaining argument and conversation context as the focus area. Confirm it resolves to real files using Glob and Read. Identify the boundary: which files and directories the focus area includes, and one layer of neighbors in each direction (what it imports, what imports it). If the focus area does not resolve to actual files, stop and ask the user to clarify it before going further. If no focus area was supplied at all, ask the user to name one — do not proceed against the whole codebase.

Resolve project context. If CLAUDE.md is present (see Project Context), read its ## Project Discovery section for conventions. Fall back to project-discovery.md if present. These resolve language, framework, and convention questions so the agents infer less. If neither exists, the agents fall back to surrounding-code inference — note this in the agent briefs.

Note git availability. Read the git installed value from Project Context. If it is empty or reads not installed, git is unavailable: the analysts will skip churn- and recency-based reasoning and the report must state this. If it shows a path, the analysts may use git history for churn and likelihood evidence.

State the driving concern, if any. If the user named a concern ("I suspect a race in the retry queue", "we want to split this module"), capture it. It biases every agent's attention without narrowing scope. Pass it into every brief.

Step 2: Detect Signals and Classify Size

Run targeted Grep and Glob over the focus area to detect which domains the code actually touches. These signals drive both the size band and the roster:

  • Concurrency signal: async/await, Promises, threads, goroutines, workers, channels, mutexes/locks, semaphores, queues, Promise.all, WaitGroup, thread pools, atomic types.
  • Security signal: authentication, authorization, sessions, tokens, passwords, secrets, crypto calls, PII fields, deserialization of untrusted input, SQL/command construction from input.
  • Data signal: schema or migration files, ORM models/repositories, hand-written SQL, query builders, data-pipeline or stream/event-contract code, document-store access.
  • DevOps signal: Dockerfiles, IaC (Terraform, CloudFormation, k8s manifests), CI/CD pipeline definitions, observability/metrics/tracing wiring, retry/timeout/scaling configuration.
  • System-seam signal: the focus area crosses a deployable unit or bounded-context boundary — RPC/HTTP clients to sibling services, message brokers, shared databases across services, cross-context model imports, contested data ownership.
  • Unfamiliar-area signal: the focus area is large or its internal structure is not legible from a first read, so the discovery analysts would benefit from a map first.

Classify the size. Default to small. Escalate only when a band's signal is clearly present; when a signal is borderline, stay at the smaller band.

  • Small (default) — a single module or directory, contained surface, no cross-cutting concerns: no security signal, no data signal, no DevOps signal, no system-seam signal. The concurrency signal may be present or absent.
  • Medium — two or three adjacent subsystems, OR exactly one cross-cutting concern present (one of: security, data, or DevOps signal — a single auth surface, a single data-contract, a single operational surface).
  • Large — more than roughly a dozen files across multiple subsystems, OR two or more cross-cutting concerns present together, OR a system-seam signal is present, OR $size is large.

Apply the size override. If $size is not none provided, use it: a band value is the band and skips the signal-based classification above, while dynamic forces the signal-based classification even when the project config sets a default band. If $size is none provided and the project config supplies a band via default-swarm-size (per the config rule in ../../references/config-rule.md), use that band, skip the signal-based classification, and announce the config as the source. In every case still select specialists by signal (a large band does not dispatch agents whose domain the code never touches). A conversational override ("run this large") is equivalent to $size.

Step 3: Build the Roster and Announce It

Synthesis spine — dispatched at every size:

  • han-core:structural-analyst — static structure: module boundaries, coupling, dependency direction, abstractions, duplication. Emits S# findings.
  • han-core:behavioral-analyst — runtime behavior: data flow, error propagation, state management, integration boundaries. Emits B# findings.
  • han-core:risk-analyst — scores the S/B/C findings for risk of inaction (likelihood, severity, blast radius, reversibility). Emits R# items. Runs after the discovery wave.
  • han-core:software-architect — synthesizes all upstream findings into intra-codebase recommendations grounded in cohesion, coupling, and SOLID, with pseudocode sketches. Emits A# items. Runs last.

Signal-selected discovery specialists — added when the signal is present and the band allows:

SpecialistAdd whenMin band
han-core:concurrency-analyst (C#)Concurrency signal presentSmall
han-core:adversarial-security-analyst (SEC-###)Security signal presentMedium
han-core:data-engineerData signal presentMedium
han-core:devops-engineer (DOR-###)DevOps signal presentMedium
han-core:on-call-engineer (OCE-###)On-call resilience signal present: application source in the focus area has outbound calls, retry logic, queue/buffer handling, async/await code, error-handling on a production path, fan-out loops, idempotency surfaces, or new production code paths whose failure would page someoneMedium
han-core:codebase-explorerUnfamiliar-area signal presentLarge
han-core:system-architect (SA#)System-seam signal presentLarge

Roster caps by band: small runs the spine plus han-core:concurrency-analyst only (3–4 agents); medium adds one or two of {han-core:adversarial-security-analyst, han-core:data-engineer, han-core:devops-engineer, han-core:on-call-engineer} by signal (4–6 agents); large adds the remaining signalled specialists, han-core:codebase-explorer if the area is unfamiliar, and han-core:system-architect if a system-seam signal is present (6–9 agents). If more than the cap's worth of specialists are signalled, keep the band's count and prefer the specialists covering the strongest signals; note the omitted domains in the executive summary so the user can re-run larger. When both han-core:devops-engineer and han-core:on-call-engineer are signalled, prefer han-core:on-call-engineer if the focus area is application source and han-core:devops-engineer if it is infrastructure or pipelines; include both at large size only.

Extra agents named in the project config's ## Extra Agents list join the signal-selected specialist pool and compete under the same signals and band caps, per ../../references/config-rule.md: add one only when a signal in the focus area matches its stated specialty, count it against the band's cap, and skip an entry that does not resolve to a dispatchable agent with a one-line note.

han-core:system-architect is the only specialist that changes han-core:software-architect's behavior: when han-core:system-architect is on the roster, han-core:software-architect still defers boundary-crossing findings but the report carries han-core:system-architect's recommendations for them instead of only listing them as deferred.

Announce the decision in one line before dispatching, with per-specialist justification — for example:

Size: medium. Focus area src/auth/ spans the session and token subsystems; one security signal detected (token handling). Roster (5): han-core:structural-analyst, han-core:behavioral-analyst (spine), han-core:concurrency-analyst (async token refresh detected), han-core:adversarial-security-analyst (token + session handling), then han-core:risk-analyst and han-core:software-architect.

State git availability in the same message if git is absent ("git unavailable — churn and recency evidence will be skipped"). Proceed without a blocking confirmation; this analysis is read-only and re-runnable, so a gate here would gate a reversible operation. If the user objects to the roster, honor the adjustment.

Show full SKILL.md (1,171 more words)Show less

Step 4: Dispatch the Discovery Wave in Parallel

Launch every discovery agent on the roster in a single message with one Agent call per agent so they run concurrently: han-core:structural-analyst, han-core:behavioral-analyst, and whichever of han-core:concurrency-analyst, han-core:adversarial-security-analyst, han-core:data-engineer, han-core:devops-engineer, han-core:on-call-engineer, han-core:codebase-explorer are on the roster. Do not launch han-core:risk-analyst, han-core:software-architect, or han-core:system-architect here — they are the synthesis layer (Steps 6 and 7).

Each brief must contain:

  • The resolved focus area and its boundary (the file/directory list from Step 1), plus the instruction to trace one layer outward.
  • The driving concern from Step 1, if any.
  • The resolved project-context conventions, or a note that none were found and surrounding-code inference applies.
  • Git availability, so the agent knows whether churn/recency evidence is in scope.
  • A calibration directive scaled to the band: at small, escalate only the clearest high-impact findings and let lower-confidence observations default down; at medium, surface high- and medium-impact findings; at large, surface the full finding set. This scales the brief to the size the same way the roster does.
  • For han-core:adversarial-security-analyst, han-core:data-engineer, han-core:devops-engineer, and han-core:on-call-engineer: scope the brief to the focus area and direct findings at architectural concerns within it (its domain's structural and behavioral risk), not a general audit of the whole repository. For han-core:on-call-engineer, the brief must restrict findings to application source files only — infrastructure, pipelines, and IaC are out of scope.

Wait for the entire wave to return before proceeding.

Step 5: Compile the Discovery Findings

Collect the full verbatim output from every discovery agent. Preserve every numbered item and its prefix exactly: S# (structural), B# (behavioral), C# (concurrency), SEC-### (security), DOR-### (devops), and han-core:data-engineer's own finding IDs. Do not renumber, summarize, or drop items — the verbatim output is what the report carries and what the synthesis layer cross-references.

If han-core:concurrency-analyst reported "no concurrency patterns found", keep that statement verbatim — it is a valid negative result, not a missing section.

Step 6: Dispatch the Risk Analyst

Launch han-core:risk-analyst with one Agent call. Pass it the full verbatim S#, B#, and C# findings (its documented input contract). Do not pass it the security, data, or devops findings — those specialists already carry their own severity and impact framing, and han-core:risk-analyst's rubric is built for the structural/behavioral/concurrency findings that lack inherent severity. The agent emits R# items cross-referencing the upstream S/B/C findings with likelihood, severity, blast radius, and reversibility. Wait for it to return.

Step 7: Dispatch the Synthesis Architects

Launch the synthesis layer with one Agent call per architect, in a single message when both are on the roster:

  • han-core:software-architect — always. Pass it the full verbatim discovery output (S/B/C plus any SEC-###, DOR-###, and han-core:data-engineer findings) AND the han-core:risk-analyst R# items. It produces A# intra-codebase recommendations with pseudocode sketches, each cross-referencing upstream findings and naming the SOLID/cohesion/coupling concern. It defers boundary-crossing findings rather than absorbing them.
  • han-core:system-architect — only when it is on the roster (large size, system-seam signal). Pass it the same verbatim discovery output and R# items, plus the DOR-### and han-core:data-engineer findings explicitly (its documented optional inputs). It produces SA# cross-service / bounded-context recommendations and a context-map sketch.

Wait for the synthesis layer to return.

Step 8: Render the Report

Read references/architectural-analysis-report-template.md. Render it into the report draft; you present it after the readability pass in Step 11. Render rules:

  1. Fill the front matter and "How to Read" frame. Set the focus area, the chosen size with its one-line justification, the dispatched roster, and git availability.
  2. Carry agent output verbatim. Each analysis section is the corresponding agent's full output, unedited. The skill writes only the Executive Summary and the section prefaces.
  3. Remove sections for agents that were not dispatched. Drop the section, remove its line from sections_included in the front matter, and replace its promise in the "How to Read" frame with a single line stating it was not part of this run (the same way gap-analysis handles optional sections). A small run with no concurrency signal has no Concurrency section; a run with no security signal has no Security section.
  4. Handle the concurrency negative result. If han-core:concurrency-analyst ran but found nothing, keep the section and carry its "no concurrency patterns found" statement — this is a reported result, not an omission.
  5. Resolve system-altitude content. If han-core:system-architect was dispatched, render its SA# recommendations in the System-Architecture Recommendations section. If it was not, omit that section and instead render han-core:software-architect's deferred boundary-crossing findings under "System-level concerns deferred", with the one-line note that the user can dispatch han-core:system-architect separately for recommendations at that altitude.
  6. Write the Executive Summary last, after every other section is filled: the focus area and size, the 3–5 most critical findings across all dispatched dimensions, the highest-impact recommendations, and an explicit note on any dimension that was clean or any signalled domain omitted by the band cap.

Readability. Invoke han-communication:readability-guidance to surface the shared readability standard into your context. As you write the report's synthesized prose — the Executive Summary, the "How to Read" frame, and the section prefaces — apply that standard: main point first, descriptive headings, one idea per paragraph with the first sentence carrying it, numbered lists for steps and bullets for non-sequential items, and progressive disclosure. Finding IDs and file:line references are citation identifiers; they survive any rewrite and self-check unchanged.

Step 9: Rewrite the Report for Readability

Dispatch han-communication:readability-editor with one Agent call to audit and rewrite the report draft against the shared readability standard. Pass it the draft report text and the named audience: the engineer weighing the module's design and deciding whether to change it; the editor reads han-communication's own canonical rule, so pass no rule path. It preserves every fact and edits prose regions only — never inside code fences, pseudocode sketches, Mermaid or other diagram bodies, or finding-ID and file:line citation identifiers. Scope its rewrite to the report's synthesized prose (the Executive Summary, the "How to Read" frame, and the section prefaces); leave every analysis section's verbatim agent output unchanged. Apply its rewrite. This pass does not touch the discovery, risk, or architect agent spine (Steps 4–7).

Step 10: Run the Readability Self-Check

Run the standardized readability self-check (the shared standard is in your context from han-communication:readability-guidance) over the report's prose regions only — never inside code fences, pseudocode sketches, diagram bodies, or finding-ID / file:line citation identifiers. Confirm each criterion and fix any failure before presenting:

Run the readability rule's standardized self-check, which is already in your context from the readability-guidance invocation above. Correct every failure before presenting. Its fidelity criterion is not optional: the standard governs how the content is said, and drops a required fact only when the reader asked for less and losing it would not change what they do next.

Step 11: Present the Report

Present the rendered report directly in the conversation. Close by telling the user, in a short message: the size class and roster used (and why), git availability, the count of findings by dimension, and any open items — boundary-crossing concerns deferred to han-core:system-architect, or signalled domains the band cap omitted that would justify a re-run at a larger size.

© testdouble, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in han-coding/skills/architectural-analysis of testdouble/han.

  • SKILL.md
  • references/architectural-analysis-report-template.md

Open the folder on GitHubat commit abba73a

Compare with similar skills

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Design Smell DetectorArabelaTso/Skills-4-SE253—~3.2kAutomated safety check: PassApache-2.0
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  • Update PR Description

    testdouble/han

    Generate a PR description from the current branch's changes against a GitHub PR, using the gh CLI.

    279 GitHub starsUsed in 1 repo~4.7k tokens
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  • Plan Implementation

    testdouble/han

    Builds a feature implementation plan from an existing feature specification (or equivalent context) through a facilitated team conversation.

    279 GitHub stars~9.5k tokensUpdated 7 days ago
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Categories

Questions about Architectural Analysis

What does Architectural Analysis do?

Performs deep architectural analysis of a specified module, directory, or feature area by examining structural coupling, data flow, concurrency patterns, risk, and SOLID alignment. Architectural Analysis is an agent skill from testdouble/han. Performs deep architectural analysis of a specified module, directory, or feature area by examining structural coupling, data flow, concurrency patterns, risk, and SOLID alignment.

When should I use Architectural Analysis?

Architectural Analysis fits situations like: the user wants to assess; review the architecture; dependency structure; technical debt of an existing part of the codebase.

How do I install Architectural Analysis in Claude Code?

Run `npx skills add testdouble/han --skill architectural-analysis -a claude-code`. Or copy the skill folder (han-coding/skills/architectural-analysis in testdouble/han) into .claude/skills/architectural-analysis in your project. Claude Code loads it when a task matches its description.

How do I install Architectural Analysis in Codex?

Run `npx skills add testdouble/han --skill architectural-analysis -a codex`. Or copy the skill folder (han-coding/skills/architectural-analysis in testdouble/han) into .agents/skills/architectural-analysis in your project. Codex loads it when a task matches its description.

Can I use Architectural 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 testdouble/han --skill architectural-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/architectural-analysis, .gemini/skills/architectural-analysis, .github/skills/architectural-analysis and .opencode/skills/architectural-analysis in your project.

What does Architectural Analysis need to run?

Going by SKILL.md and its folder, Architectural Analysis needs the command-line tools its instructions call (bash and git). Its frontmatter pre-approves these tools: Read, Glob, Grep, Agent, Bash(find *), Bash(bash "${CLAUDE_PLUGIN_ROOT}/scripts/han-config-dir.sh").

Does Architectural Analysis access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Architectural 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 Architectural Analysis use?

Architectural Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Architectural Analysis use?

About 6.4k tokens (SKILL.md is roughly 26k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.4k tokens, read only when the agent opens those files.

What are the alternatives to Architectural Analysis?

Skills that share tags, products or a category with Architectural Analysis: Software Design Philosophy (luoling8192/software-design-philosophy-skill, 346 stars), Moai Workflow Ddd (modu-ai/moai-adk, 1.2k stars), Design Smell Detector (ArabelaTso/Skills-4-SE, 253 stars) and Design Code Architecture (wondelai/skills, 2.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Architectural Analysis?

testdouble (a GitHub organization) maintains it in testdouble/han, which has 279 GitHub stars. The repository holds 54 skills in this directory. The repository was last updated on October 1, 2026.

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