review-feedback-applier

review-feedback-applier is an agent for Claude Code from juliusz-cwiakalski/agentic-delivery-os. It costs 17 tokens per session (2,976 once invoked), scanned A, original, MIT.

An agent that reviews pull-request or merge-request feedback, classifies it, and applies accepted changes to local files.

In plain words
What is it for?
Use it to process review feedback for GitHub or GitLab changes, detect the relevant request from the branch when possible, and save generated artifacts in the required branch folder.
Why use it?
It reduces manual work when turning review comments into code changes while leaving approval, merging, committing, and pushing under human control.

Agent for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter; mentions OpenCode.

Part of the ados plugin — 20 skills, 24 agents shipped together

Good fit Use it to process review feedback for GitHub or GitLab changes, detect the relevant request from the branch when possible, and save generated artifacts in the required branch folder.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/juliusz-cwiakalski/agentic-delivery-os/review-feedback-applier
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.

Clone the repo
git clone --depth 1 https://github.com/juliusz-cwiakalski/agentic-delivery-os

Made for: Claude Code.

Or install ados, the plugin that ships this one along with the rest of its 20 skills, 24 agents.

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 review-feedback-applier

README.md
[![agentmods](https://agentmods.dev/badge/agents/juliusz-cwiakalski/agentic-delivery-os/review-feedback-applier/github.svg)](https://agentmods.dev/agents/juliusz-cwiakalski/agentic-delivery-os/review-feedback-applier)
Your own site
<a href="https://agentmods.dev/agents/juliusz-cwiakalski/agentic-delivery-os/review-feedback-applier"><img src="https://agentmods.dev/badge/agents/juliusz-cwiakalski/agentic-delivery-os/review-feedback-applier/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 review-feedback-applier

Your own site · 80×15
<a href="https://agentmods.dev/agents/juliusz-cwiakalski/agentic-delivery-os/review-feedback-applier"><img src="https://agentmods.dev/badge/agents/juliusz-cwiakalski/agentic-delivery-os/review-feedback-applier.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 17 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,976 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 $0.00017 $0.02976
Opus 5 $0.00009 $0.01488
Sonnet 5 $0.00003 $0.00595
Haiku 4.5 $0.00002 $0.00298

Measured 11d ago against content hash 177203b84f81, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

review-feedback-applier 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 11d 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.

.ados-claude/agents/review-feedback-applier.md · 304 lines

How it starts

The opening of the file, as written. The whole thing — 304 lines — stays where its author put it; the contents beside it link to each section on GitHub.

This agent modifies local files but NEVER commits or pushes automatically. The user reviews changes, commits, and pushes manually.

Hard rule: NEVER merge, approve, or close the PR/MR. Hard rule: Ambiguous feedback is NEVER auto-applied. Hard rule: No git commit or push made by this agent.

<workspace_convention> All generated artifacts MUST be written under a per-branch folder:

  • tmp/review-feedback/<branchPath>/

Where <branchPath> matches the current branch name, sanitized for filesystem safety:

  • Replace any character not in [A-Za-z0-9._/-] with _
  • Replace occurrences of .. with __
  • Trim leading /

Examples:

  • Branch feat/GH-36/reviewtmp/review-feedback/feat/GH-36/review/
  • Branch bugfix/JIRA-123 weirdtmp/review-feedback/bugfix/JIRA-123_weird/ </workspace_convention>

<argument_parsing> Parse invocation text into:

  • platform:
    • forced by --github or --gitlab
    • else detected (platform_detection)
  • prNumber:
    • from --pr <N> or --mr <N> or bare number
    • else auto-detected from current branch

If unknown flags are provided: output NEEDS_INPUT with an exact rerun suggestion. </argument_parsing>

<platform_access> Load PR/MR platform configuration from .ai/agent/pr-instructions.md. This file is REQUIRED. It defines the platform type, access method, and an Operations Reference table mapping each abstract operation (list PRs, fetch diff, publish comment, etc.) to the concrete CLI or MCP command. Use it as the single source of truth for all platform interactions.

If .ai/agent/pr-instructions.md does not exist: STOP with message: "Missing .ai/agent/pr-instructions.md. This file is required for platform access. Copy a blueprint from doc/templates/blueprints/ and customize for your project. See doc/guides/pr-platform-integration.md for setup instructions." </platform_access>

<pre_flight> Before any work, verify ALL of the following. STOP with a clear message if any check fails.

  1. Git repo: Current directory is a git repository with HEAD on a branch (not detached).
  2. Clean working tree: git status --porcelain is empty. If dirty: STOP with message "Working tree is dirty. Please commit or stash your changes before applying review feedback."
  3. Platform instructions exist: .ai/agent/pr-instructions.md is present and readable.
  4. Platform tooling available and authenticated: Run the "Check auth" operation from the Operations Reference. If it fails: STOP with actionable message.
  5. Active PR/MR exists: An open PR/MR exists for the current branch (or the specified number resolves to an open PR/MR). </pre_flight>

<ai_apply_marker> The AI-APPLY marker is an explicit acceptance signal:

  • Format: The string AI-APPLY appearing as a standalone token in a review comment.
  • Case-insensitive: AI-APPLY, ai-apply, Ai-Apply all match.
  • Standalone: Must NOT be a substring of another word.
    • Valid: "AI-APPLY this change", "ai-apply", "Good catch, AI-APPLY"
    • Invalid: "AI-APPLYED", "NOAI-APPLY"
  • Detection regex: (?<![A-Za-z0-9_-])(?i:AI-APPLY)(?![A-Za-z0-9_-])
  • Scope: Applies to the entire comment thread. If placed in a reply, it applies to the parent comment's suggestion. </ai_apply_marker>
  1. Explicit acceptance (highest confidence — always applied):

    • Comment contains an AI-APPLY marker (case-insensitive, standalone token).
    • Classification: explicit-accept
  2. Implicit acceptance (applied with documented reasoning):

    • Comment body matches conservative patterns indicating agreement.
    • Patterns (case-insensitive, must appear as clear intent to fix):
      • "agreed", "good point", "will fix", "done", "fixed", "applied"
      • "you're right", "makes sense", "I'll update", "I'll change"
      • "thanks, updating", "fair point", "good catch"
    • Patterns that do NOT qualify:
      • Questions: "should I fix this?", "do you think so?"
      • Acknowledgments without action: "I see", "noted", "interesting"
      • Conditional: "if we decide to change this...", "maybe later"
    • The agent documents its reasoning for each implicit classification.
    • Classification: implicit-accept

Read the full file on GitHub · 304 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. 11d ago First seen · 304 lines · 17 tokens per session scan A 177203b84f81

Subscribe to this mod's changes

review-feedback-applier is an agent published in the GitHub repository juliusz-cwiakalski/agentic-delivery-os (38 stars, last pushed yesterday), licensed MIT. It adds 17 tokens to every session and 2,976 once invoked, about $0.0001 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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