focus

A single-task workflow that guides an agent through planning, doing, checking, and closing one piece of work.

In plain words
What is it for?
Use it for a specific issue, TODO, tracker item, or implementation task that needs a clear completion check.
Why use it?
It keeps work focused and records enough context to continue after a new session or handoff.

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/sjarmak/coding-agent-workflows/focus
Any agent
npx skills add sjarmak/coding-agent-workflows --skill focus
Clone the repo
git clone --depth 1 https://github.com/sjarmak/coding-agent-workflows

Made for: Claude Code, Codex.

Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 606 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 $0.00036 $0.00606
Opus 5 $0.00018 $0.00303
Sonnet 5 $0.00007 $0.00121
Haiku 4.5 $0.00004 $0.00061

Measured 2d ago against content hash 21d4f773805b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

focus 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 2d 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.

source/skills/focus/SKILL.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Focus: Single-Task Execution Loop

Enforces the discipline of plan → execute → verify → close on exactly one unit of work. The original is coupled to a specific task tracker; this version is tracker-agnostic: "the task" can be an issue, a tracker ID, a TODO entry, or a written description.

When to activate

  • You have a concrete, scoped unit of work to implement.
  • You're resuming work and need to pick up exactly where the last session left off.
  • A workflow (e.g. implement-review) delegates the implementation phase here.

Arguments

[task | "description"] [--no-close]

  • A task ID → work on that task.
  • A description → treat it as a new task.
  • No argument → list ready work and pick one.
  • --no-close → run plan/execute/verify but leave finalization to the caller (used when a wrapping workflow writes its own completion record or routes to an external reviewer). Manual use rarely needs this.

Phase 0: Load context

Read the task: description, acceptance criteria, linked context, and any prior rejection reason. If resuming, reconstruct where the last session stopped from the task's notes and the working tree. Do not start coding until you can state what "done" looks like.

Phase 1: Plan

Produce a short, concrete plan: the files you'll touch, the order, and how you'll verify each piece. Keep it proportional to the task; a one-file fix gets a two-line plan.

Phase 2: Execute

Implement the plan step by step. Commit in logical units. If context fills up, write progress to the task and hand off to a fresh session rather than continuing in a degraded window; a clean context that re-reads the plan beats a full one that's lost the thread.

Phase 3: Verify

Check the work against the acceptance criteria using the actual diff, not your memory of what you implemented. Run the project's tests. Fix and re-verify until the criteria are demonstrably met.

Phase 4: Close (skip if --no-close)

Record what was done, key decisions, and a diff summary on the task. Mark it complete.

Read the full file on GitHub · 69 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. 2d ago First seen · 69 lines · 36 tokens per session scan A 21d4f773805b

Subscribe to this mod's changes

focus is a skill published in the GitHub repository sjarmak/coding-agent-workflows (2 stars, last pushed 1mo ago), licensed MIT. It adds 36 tokens to every session and 606 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 2026-08-31.

Related

Other skills, from other repositories

browser-trace

Capture a full DevTools-protocol trace of any browser automation — CDP firehose, screenshots, and DOM dumps — then bisect the stream into per-page searchable buckets. Use when the user wants to debug a failed run, audit network/console/DOM activity, attach a trace to an in-progress session, or feed structured per-page…

mxyhi/ok-skills · 88 tokens

planning-with-files

Manus-style persistent file-based planning for AI coding agents: keeps taskplan.md, findings.md, and progress.md on disk so work survives context loss and /clear. Use when asked to plan out, break down, or organize a multi-step project, research task, or any work requiring 5+ tool calls. Supports automatic session…

mxyhi/ok-skills · 76 tokens

ai-elements

Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.

mxyhi/ok-skills · 46 tokens

exa-search

Use Exa MCP for current web, code/docs, company, people, and page-fetch research. Prefer current hosted tool schemas and note deprecated tools.

mxyhi/ok-skills · 33 tokens

ontoly-software-graph

Use Ontoly's deterministic Software Graph and MCP capabilities for repository architecture, request tracing, dependency analysis, configuration lookup, and impact analysis before falling back to source search.

mxyhi/ok-skills · 40 tokens

product-decision-agent

中文产品决策 Agent。用于中国大陆互联网产品、运营、增长、商业化、数据、项目推进和组织协作场景:产品规划、需求分析、PRD、需求优先级、排期、版本规划、Roadmap、MVP、灰度、上线、迭代、增长停滞、拉新、投放、渠道、裂变、CAC、LTV、ROI、留存、转化、DAU/MAU、GMV、漏斗、社区运营、内容供给、创作者、用户运营、活动运营、私域、会员、定价、指标异常、数据口径、埋点、A/B…

mxyhi/ok-skills · 265 tokens