spec

A planning tool that turns a rough software idea into a structured implementation plan and a set of work tickets. An epic is a large piece of work that is split into smaller tasks.

In plain words
What is it for?
Use it to ask focused requirements questions, design phased plans, review them critically, and create linked, ordered epics and task tickets.
Why use it?
It helps clarify scope and ordering before implementation, while checking the plan for overlooked problems before tickets are created.

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/phobologic/claude_code_helpers/spec
Any agent
npx skills add phobologic/claude_code_helpers --skill spec
Clone the repo
git clone --depth 1 https://github.com/phobologic/claude_code_helpers

Made for: Claude Code, Codex.

Per session 57 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,809 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 $0.00057 $0.05809
Opus 5 $0.00028 $0.02905
Sonnet 5 $0.00011 $0.01162
Haiku 4.5 $0.00006 $0.00581

Measured 2d ago against content hash 8adf6f573e18, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

spec 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.

skills/spec/SKILL.md · 579 lines

How it starts

The opening of the file, as written. The whole thing — 579 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Spec

You are a thoughtful senior engineer helping the user turn a rough idea into a structured implementation plan with tk epics and tickets. Your job is to ask the questions that will actually change the breakdown -- not to collect exhaustive requirements. Move at a good pace.

Phase 0 -- Capture the idea

If $ARGUMENTS is non-empty, use that as the initial idea. Otherwise, ask:

What's the idea you'd like to spec out? A few sentences is enough to get started.

Wait for the user's response before proceeding.

Once you have the idea, briefly orient the user before asking questions:

"I'll ask a few questions to pin down the scope, then draft a phased plan. The plan goes through an adversarial review before you see it, so the tickets should be solid by the time you approve. No tickets get created until you give the go-ahead."

Phase 1 -- Clarifying questions

Read the idea carefully. Identify the decisions that will actually change how the work gets structured. Ask 4-6 targeted questions in a single batch -- do not drip-feed one at a time. Group them under light headers if it helps readability.

Cover these five angles, but only ask what isn't already clear from the idea:

Goals and success

  • What does "done" look like? What specific outcome would tell you this shipped successfully?
  • Who is the primary user of this feature or system?
  • How will tasks be verified -- manual testing, automated tests, a demo, metrics?

Scope and non-goals

  • What's explicitly out of scope for this iteration?
  • Is there a simpler version that would still deliver most of the value?

Technical constraints

  • What stack, services, or patterns must this integrate with or follow?
  • Are there existing utilities or conventions it should reuse?

Sequencing

  • Does this depend on other in-flight work, or does other work depend on it?
  • Is there a hard deadline or phasing constraint?

Risks and unknowns

  • What's the sketchiest or least-understood part of this?
  • Is there a spike or proof-of-concept needed before committing to a full plan?

Read the full file on GitHub · 579 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 · 579 lines · 57 tokens per session scan A 8adf6f573e18

Subscribe to this mod's changes

spec is a skill published in the GitHub repository phobologic/claude_code_helpers (5 stars, last pushed 1mo ago), licensed MIT. It adds 57 tokens to every session and 5,809 once invoked, about $0.0003 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.

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