requirement-forge-refiner

requirement-forge-refiner is a skill for Claude Code, Codex from techygarg/lattice. It costs 121 tokens per session (2,635 once invoked), scanned A, original, MIT.

A guided process for defining how a project writes and organizes requirements. Requirements describe what a product should do, including features, examples, acceptance checks, priorities, statuses, and naming rules.

In plain words
What is it for?
Use it to create or update a project requirement-standards document in either overlay mode, which changes selected defaults, or override mode, which replaces them.
Why use it?
It gives a team a shared format for expressing requirements and lets the project use those choices when checking requirement quality.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Part of the lattice plugin — 33 skills, 1 agent shipped together

Good fit Use it to create or update a project requirement-standards document in either overlay mode, which changes selected defaults, or override mode, which replaces them.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/techygarg/lattice/requirement-forge-refiner
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 techygarg/lattice --skill requirement-forge-refiner
Clone the repo
git clone --depth 1 https://github.com/techygarg/lattice

Made for: Claude Code, Codex.

Or install lattice, the plugin that ships this one along with the rest of its 33 skills, 1 agent.

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 requirement-forge-refiner

README.md
[![agentmods](https://agentmods.dev/badge/skills/techygarg/lattice/requirement-forge-refiner/github.svg)](https://agentmods.dev/skills/techygarg/lattice/requirement-forge-refiner)
Your own site
<a href="https://agentmods.dev/skills/techygarg/lattice/requirement-forge-refiner"><img src="https://agentmods.dev/badge/skills/techygarg/lattice/requirement-forge-refiner/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 requirement-forge-refiner

Your own site · 80×15
<a href="https://agentmods.dev/skills/techygarg/lattice/requirement-forge-refiner"><img src="https://agentmods.dev/badge/skills/techygarg/lattice/requirement-forge-refiner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 121 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,635 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 pass 7 Sept 2026
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 $0.00121 $0.02635
Opus 5 $0.00060 $0.01318
Sonnet 5 $0.00024 $0.00527
Haiku 4.5 $0.00012 $0.00264

Measured 9d ago against content hash 75302dbf154b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

requirement-forge-refiner 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 9d 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/requirement-forge-refiner/SKILL.md · 215 lines

How it starts

The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Requirement Forge Refiner

What This Produces

  • Output: .lattice/standards/requirement-standards.md (or custom path from .lattice/config.yamlpaths.requirement_standards)
  • Two modes:
    • Overlay (mode: overlay): A slim document containing only sections that differ from the built-in defaults. The requirement-quality atom reads its embedded defaults.md first, then applies this document's sections on top. This is the expected common case.
    • Override (mode: override): A comprehensive standalone document that fully replaces the atom's embedded defaults. For teams whose product process differs fundamentally from the defaults.
  • Default mode: Overlay — produces only what the team wants to change
  • Config key: paths.requirement_standards in .lattice/config.yaml
  • Consumed by: requirement-quality atom (via config resolution) → requirement-forge molecule (composes the atom)
  • Template: Read ./assets/template.md for the full document structure, default content, and interview guidance comments

Scope Clarification

This refiner defines how requirements are structured and expressed for this project. It does not define:

  • What to build (that is the requirement-forge molecule's job)
  • Architecture or technical design (that is the architecture-refiner's job)
  • Domain modeling patterns (that is the ddd-refiner's job)

The standards produced here answer: what is an epic, what is a feature, what is a scenario, how are ACs written, how are features named and prioritized. These are the rules the requirement-quality atom enforces — the molecule composes the atom and inherits those rules automatically.

Before You Begin

Check for an existing standards document

  1. Read .lattice/config.yaml — check paths.requirement_standards.
  2. If the path exists, read that file. Ask the user:
    • "You already have a requirement standards document. Would you like to revise it (update specific sections), start fresh (new interview), or add to it (add new sections)?"
    • Revise: load the existing document, walk through only the sections the user wants to change, update in place.
    • Start fresh: proceed with the full interview flow below.
    • Add to it: skip to the "New Sections" part of the interview.
  3. If no config or no existing document, proceed with the full interview.

Read the full file on GitHub · 215 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 9d ago First seen · 215 lines · 121 tokens per session scan A 75302dbf154b

Subscribe to this mod's changes

requirement-forge-refiner is a skill published in the GitHub repository techygarg/lattice (186 stars, last pushed yesterday), licensed MIT. It adds 121 tokens to every session and 2,635 once invoked, about $0.0006 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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