validate

A quality-check workflow for a task, feature, epic, or whole product. It runs the relevant checks and returns a verdict.

In plain words
What is it for?
Use it to check whether an individual task, feature, epic, or product meets its specification and tests.
Why use it?
It provides a review step after planning or coding, including a fresh review for larger pieces of work.

Skill for Claude CodeCodex

Part of the agn plugin — 9 skills, 2 agents shipped together

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/agenturehq/agenture-loop/validate
Any agent
npx skills add AgentureHQ/agenture-loop --skill validate
Clone the repo
git clone --depth 1 https://github.com/AgentureHQ/agenture-loop

Made for: Claude Code, Codex.

Or install agn, the plugin that ships this one along with the rest of its 9 skills, 2 agents.

Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,379 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 $0.00032 $0.02379
Opus 5 $0.00016 $0.01189
Sonnet 5 $0.00006 $0.00476
Haiku 4.5 $0.00003 $0.00238

Measured 2d ago against content hash 9b704cd8d443, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

validate 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.

plugins/agn/skills/validate/SKILL.md · 168 lines

How it starts

The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Validate (/agn:validate <level>)

Arguments

Position Variable Value
$0 level task, feature, epic, or product
$1 id Optional task path (for task) or scope hint (for feature / epic)

Argument validation

If $0 is missing, stop and ask:

"What level — task, feature, epic, or product?"

If $0 is not one of task, feature, epic, product, stop and list the valid set.

Dispatch

Read $0. Run exactly one of the branches below.

Validation via the QA sub-agent

For feature, epic, and product levels, validation runs in the QA sub-agent (plugins/agn/agents/qa.md). The sub-agent loads rules/qa.md, reads the spec and the implementation, runs tests, and returns a verdict. Fresh context is the point — the agent that wrote the code has already collapsed the design space in their head; a fresh reader sees gaps that closed space hid.

The task branch does not invoke the QA sub-agent — the task's own ## Quality gates are narrow and the parent session has the right context to run them.

When a workflow below says "delegate to QA", invoke it via the Agent tool with subagent_type: qa and a brief containing:

  • levelfeature | epic | product
  • scope — slug (feature/epic) or "whole product"
  • spec_paths — paths to relevant documents (docs/vision.md, docs/spec.md, docs/requirements.md, docs/architecture.md, parent epic/feature file, linked spec)
  • implementation_paths — files, test commands, dev-server URLs, sample data locations
  • regression_scope (optional) — adjacent features/areas to re-check

QA returns a structured response (## Verdict, ## Per-requirement results, ## Issues by severity, ## What I fixed, ## What I escalated, ## Report path, ## Next steps). Surface the verdict to the user. On not ready, present the issues and stop — do not silently advance the lifecycle (e.g., do not auto-close a feature whose QA verdict was not ready).

Read the full file on GitHub · 168 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 · 168 lines · 32 tokens per session scan A 9b704cd8d443

Subscribe to this mod's changes

validate is a skill published in the GitHub repository AgentureHQ/agenture-loop (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 32 tokens to every session and 2,379 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.

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