clarify

clarify is a skill for Claude Code, Codex from ZaxbyHub/opencode-swarm. It costs 25 tokens per session (1,561 once invoked), scanned A, original, MIT.

A structured process for handling unclear requests before work begins. It reviews uncertainties and decides which questions, if any, the user needs to answer.

In plain words
What is it for?
Use it when a coding request is ambiguous and needs a careful clarification step before discovery or execution.
Why use it?
It helps avoid interrupting users with unnecessary questions while still checking issues that could affect scope, safety, compatibility, cost, or implementation.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/zaxbyhub/opencode-swarm/clarify
Any agent
npx skills add ZaxbyHub/opencode-swarm --skill clarify
Clone the repo
git clone --depth 1 https://github.com/ZaxbyHub/opencode-swarm

Made for: Claude Code, Codex.

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 clarify

README.md
[![agentmods](https://agentmods.dev/badge/skills/zaxbyhub/opencode-swarm/clarify.svg)](https://agentmods.dev/skills/zaxbyhub/opencode-swarm/clarify)
Your own site
<a href="https://agentmods.dev/skills/zaxbyhub/opencode-swarm/clarify"><img src="https://agentmods.dev/badge/skills/zaxbyhub/opencode-swarm/clarify.svg" alt="Measured on agentmods" height="20"></a>
Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,561 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00025 $0.01561
Opus 5 $0.00013 $0.00781
Sonnet 5 $0.00005 $0.00312
Haiku 4.5 $0.00003 $0.00156

Measured 5d ago against content hash 1302026cffe2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

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 5d ago.

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.

.claude/skills/clarify/SKILL.md · 111 lines

How it starts

The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Clarify Protocol

This protocol is loaded on demand by the architect runtime. The architect prompt keeps only activation, action, and hard safety constraints; the full execution details live here.

MODE: CLARIFY

Ambiguous request → Run the clarification funnel Clear request → MODE: DISCOVER

Clarification Funnel

Before surfacing any clarification question to the user, the architect MUST run this four-stage funnel. The goal is to limit unnecessary user interruption, not planning completeness.

Stage 1: Inventory All Material Uncertainties

Identify ALL uncertainties that could affect:

  • Scope boundaries
  • User-visible behavior
  • Destructive behavior or data loss
  • Security/privacy posture
  • Backward compatibility
  • Migrations or rollout strategy
  • Cost/performance tradeoffs
  • Operational complexity
  • QA gate selection or enforcement strictness
  • Architecture choice among materially different paths
  • Dependency or platform assumptions

There is NO hard cap on the internal inventory. Record every material uncertainty found.

Stage 2: Classify Each Uncertainty

Classify each item as exactly one of:

  • self_resolved: answered from the user request, spec, plan, codebase reality check, .swarm/context.md, repo conventions, or an informed default. If the default is not directly supported by user request, spec, or recorded context, classify as user_decision rather than self_resolved.
  • critic_resolved: sent to Critic Sounding Board and resolved by the critic.
  • research_needed: needs SME/explorer/domain lookup before user escalation. Important: If research is ongoing, apply a fixed 5-minute protocol budget to research_needed. If research does not complete before the budget expires, automatically reclassify the item to user_decision with a note that research was incomplete, then surface it to the user. This prevents the clarification funnel from stalling while waiting for external research.
  • user_decision: only the user can decide because it affects product scope, risk tolerance, policy, budget, UX, rollout, or destructive behavior.
  • deferred_nonblocking: useful follow-up detail that does not block a correct initial plan and can be explicitly recorded as an assumption or follow-up.

Read the full file on GitHub · 111 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. 5d ago First seen · 111 lines · 25 tokens per session scan A 1302026cffe2

Subscribe to this mod's changes

clarify is a skill published in the GitHub repository ZaxbyHub/opencode-swarm (464 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 1,561 once invoked, about $0.0001 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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