analiz-human-review-gate

analiz-human-review-gate is a skill for Claude Code, Codex from makifbaysal/tasktrooper. It costs 33 tokens per session (1,978 once invoked), scanned A, original, Apache-2.0.

An analysis human-review gate is an approval checkpoint between writing an analysis report and creating implementation tasks. A human reviews the report and its plan before any developer work is opened.

In plain words
What is it for?
Use it to submit the report, wait in the analysis-review stage, respond to every human comment, and create tasks only after approval.
Why use it?
It prevents an incorrect design from being copied into multiple tasks and gives the reviewer a chance to answer comments or request changes first.

Skill for Claude CodeCodex

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

Good fit Use it to submit the report, wait in the analysis-review stage, respond to every human comment, and create tasks only after approval.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/makifbaysal/tasktrooper/analiz-human-review-gate
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 makifbaysal/tasktrooper --skill analiz-human-review-gate
Clone the repo
git clone --depth 1 https://github.com/makifbaysal/tasktrooper

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 analiz-human-review-gate

README.md
[![agentmods](https://agentmods.dev/badge/skills/makifbaysal/tasktrooper/analiz-human-review-gate/github.svg)](https://agentmods.dev/skills/makifbaysal/tasktrooper/analiz-human-review-gate)
Your own site
<a href="https://agentmods.dev/skills/makifbaysal/tasktrooper/analiz-human-review-gate"><img src="https://agentmods.dev/badge/skills/makifbaysal/tasktrooper/analiz-human-review-gate/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 analiz-human-review-gate

Your own site · 80×15
<a href="https://agentmods.dev/skills/makifbaysal/tasktrooper/analiz-human-review-gate"><img src="https://agentmods.dev/badge/skills/makifbaysal/tasktrooper/analiz-human-review-gate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,978 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.
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 $0.00033 $0.01978
Opus 5.5 $0.00013 $0.00791
Sonnet 5.5 $0.00007 $0.00396
Haiku 4.5 $0.00003 $0.00198

Measured 8d ago against content hash a00805838a93, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

analiz-human-review-gate 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 8d 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.

catalog/agents/system-architect/skills/analiz-human-review-gate/SKILL.md · 95 lines

How it starts

The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Analiz Human Review Gate

Overview

Your analysis output — the ONE analysis report, with the spec and the implementation plan as its sections — is not self-approved. A human reviews it BEFORE any implementation task exists. This is the only human gate in the system: the human does not review individual dev tasks, but they DO review your plan, because a wrong plan multiplies into wrong tasks across every project.

The human reviews the report passage by passage: they select text in it, comment on it, and send all their comments back at once. Each comment is anchored to the words it is about, so it is precise — and every one of them needs an answer.

Core principle: No implementation task is created from an unapproved plan. You stop, the task waits at analiz_review, and you create nothing until the human approves.

This reverses the old flow. You no longer create tasks and then close the analiz. You present the plan, wait for approval, and only THEN create tasks.

The Gate

digraph gate {
    "Report written\n& self-reviewed" [shape=box];
    "Summary comment, STOP\n(system moves -> analiz_review)" [shape=box];
    "Human decision" [shape=diamond];
    "Human moves -> done\n(approved)" [shape=box];
    "Human sends comments\n-> need_revision (rejected)" [shape=box];
    "Create per-project impl tasks\n+ list them" [shape=box];
    "Move analiz -> released" [shape=doublecircle];
    "Fix every comment at root\nin the SAME report, resolve each\n(system moves -> analiz_review)" [shape=box];

    "Report written\n& self-reviewed" -> "Summary comment, STOP\n(system moves -> analiz_review)";
    "Summary comment, STOP\n(system moves -> analiz_review)" -> "Human decision";
    "Human decision" -> "Human moves -> done\n(approved)" [label="approve"];
    "Human decision" -> "Human sends comments\n-> need_revision (rejected)" [label="request changes"];
    "Human moves -> done\n(approved)" -> "Create per-project impl tasks\n+ list them";
    "Create per-project impl tasks\n+ list them" -> "Move analiz -> released";
    "Human sends comments\n-> need_revision (rejected)" -> "Fix every comment at root\nin the SAME report, resolve each\n(system moves -> analiz_review)";
    "Fix every comment at root\nin the SAME report, resolve each\n(system moves -> analiz_review)" -> "Human decision";
}

Read the full file on GitHub · 95 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. 8d ago First seen · 95 lines · 33 tokens per session scan A a00805838a93

Subscribe to this mod's changes

analiz-human-review-gate is a skill published in the GitHub repository makifbaysal/tasktrooper (113 stars, last pushed yesterday), licensed Apache-2.0. It adds 33 tokens to every session and 1,978 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-10-05.

Related

Other skills, from other repositories

github-multi-repo

Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration.

ruvnet/ruflo · 21 tokens

paperclip

Use for Paperclip-managed tasks and heartbeats: reading task context, delivering task documents or files, updating completion or blockers, coordinating or delegating work, and following company governance. Includes control plane API operations for assignments, comments, approvals, and routines.

paperclipai/paperclip · 54 tokens

paperclip

Interact with the Paperclip control plane API for task coordination and governance. Use when checking assignments, updating issue status, posting comments, delegating work, managing routines, or calling Paperclip API endpoints.

paperclipai/paperclip · 43 tokens

paperclip-board

Manage a Paperclip company as a board member via chat. Use when the user wants onboarding, company or agent management, approvals, task monitoring, cost oversight, or work product review in the Paperclip control plane.

paperclipai/paperclip · 47 tokens

paperclip-distill

Use when an operation issue is a Paperclip cursor-window, distill, or backfill. Turn source-bundled Paperclip activity into wiki-insightful project standups, durable project pages, decisions, and history without asset dereferencing.

paperclipai/paperclip · 54 tokens

summarize-status

Write a short, colloquial summary for a Paperclip summary slot: open with the 1–3 specific, concrete actions the reader needs to take right now to unblock the work, then a brief plain-language status, streaming progress as it works.

paperclipai/paperclip · 0 tokens