architect-clarify

architect-clarify is a skill for Claude Code from tikalk/adlc-team-skills. It costs 39 tokens per session (4,231 once invoked), scanned A, original, MIT.

A review tool for Architecture Decision Records (ADRs), which document important technical choices and their reasoning.

In plain words
What is it for?
Use it to improve existing ADRs, resolve architecture disagreements, and approve decisions for documentation generation.
Why use it?
It finds missing details, conflicting decisions, unclear alternatives, and consequences before the records are used to describe the system.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Good fit Use it to improve existing ADRs, resolve architecture disagreements, and approve decisions for documentation generation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tikalk/adlc-team-skills/architect-clarify
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add tikalk/adlc-team-skills --skill architect-clarify
Clone the repo
git clone --depth 1 https://github.com/tikalk/adlc-team-skills

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for architect-clarify

README.md
[![agentmods](https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/architect-clarify/github.svg)](https://agentmods.dev/skills/tikalk/adlc-team-skills/architect-clarify)
Your own site
<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/architect-clarify"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/architect-clarify/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for architect-clarify

Your own site · 80×15
<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/architect-clarify"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/architect-clarify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,231 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Memory Poisoning · line 59
    Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.
    Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
  • high Memory Poisoning · line 218
    Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.
    Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00039 $0.04231
Opus 5 $0.00019 $0.02116
Sonnet 5 $0.00008 $0.00846
Haiku 4.5 $0.00004 $0.00423

Measured 10d ago against content hash 17bf69fbaf42, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

architect-clarify scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

The scan reads SKILL.md. This mod also ships 7 executable files (scripts/bash/ascii-generator.sh, scripts/bash/common.sh, scripts/bash/mermaid-generator.sh, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/architect/architect-clarify/SKILL.md · 555 lines

How it starts

The opening of the file, as written. The whole thing — 555 lines — stays where its author put it; the contents beside it link to each section on GitHub.

architect-clarify

What this skill does

Identify underspecified areas in existing ADRs and refine them through targeted clarification questions. Ensure ADRs are complete, consistent, and ready for architecture generation.

You act as an Architecture Reviewer ensuring ADR quality by:

  • Validating ADR completeness against MADR standards
  • Identifying gaps in consequences or alternatives
  • Detecting conflicts between ADRs or with constitution
  • Refining decisions through targeted clarification

When to use

Use this skill:

  • After /architect-init: Refine initial ADRs before architecture generation
  • ADR Review: Validate ADRs before major milestones
  • New Team Member: Ensure ADRs make sense to fresh eyes
  • Conflict Resolution: Resolve identified inconsistencies

Do not use this skill when:

  • No ADRs exist: Use /architect-init first to create ADRs
  • Brownfield projects: Use /architect-init to reverse-engineer ADRs from code

Process

User Input

$ARGUMENTS

You MUST consider the user input before proceeding (if not empty).

Examples of User Input:

  • "Focus on data architecture decisions - we're reconsidering database choice"
  • "Security ADRs need more detail for compliance review"
  • "ADR-003 consequences seem incomplete"
  • Empty input: Review all ADRs for completeness

Goal

Identify underspecified areas in existing ADRs and refine them through targeted clarification questions. Ensure ADRs are complete, consistent, and ready for architecture generation.

ADR Quality Checklist

Each ADR should have:

  • Clear context explaining the problem/opportunity
  • Explicit decision statement
  • Positive AND negative consequences
  • Common Alternatives documented (neutral trade-offs, not "Rejected because")
  • Risks identified with mitigation strategies
  • Status is accurate (Proposed/Accepted/Deprecated/Superseded/Discovered)
  • No conflicts with other ADRs
  • Alignment with constitution principles
  • No fabricated rejection rationale for reverse-engineered ADRs

Read the full file on GitHub · 555 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 555 lines · 39 tokens per session scan A 17bf69fbaf42

Subscribe to this mod's changes

architect-clarify is a skill published in the GitHub repository tikalk/adlc-team-skills (133 stars, last pushed 3d ago), licensed MIT. It adds 39 tokens to every session and 4,231 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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