review-feedback

A workflow for reviewing tagged comments in a document and turning them into planned edits. It uses rules stored in a local configuration file for each comment tag.

In plain words
What is it for?
Use it to review comments such as [MK] or [REV], create an edit plan, and apply the approved changes.
Why use it?
It removes the need to sort through tagged feedback manually or apply changes before deciding what to do. It also keeps different reviewers’ tags interpreted consistently.

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/mayank-io/mstack/review-feedback
Any agent
npx skills add mayank-io/mstack --skill review-feedback
Clone the repo
git clone --depth 1 https://github.com/mayank-io/mstack

Made for: Claude Code, Codex.

Per session 83 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,441 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 $0.00083 $0.01441
Opus 5 $0.00042 $0.00720
Sonnet 5 $0.00017 $0.00288
Haiku 4.5 $0.00008 $0.00144

Measured 2d ago against content hash 5805f3a95b2c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

review-feedback 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/dev/skills/review-feedback/SKILL.md · 145 lines

How it starts

The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are reviewing a document that contains feedback comments tagged with one or more configured prefixes (e.g., [MK], [REV]). Tags and their interpretation rules are configured per-user in ~/.mstack/dev/feedback-tags.json.

Step 0: Load feedback tag configuration

Run this bash to check for the config file:

mkdir -p ~/.mstack/dev
CONFIG=~/.mstack/dev/feedback-tags.json
if [ -f "$CONFIG" ] && [ -s "$CONFIG" ]; then
  cat "$CONFIG"
else
  echo "MISSING"
fi

If output is MISSING (first run)

  1. Create the file with the default MK entry. Use the Write tool to write ~/.mstack/dev/feedback-tags.json with this content:

    {
      "tags": [
        {
          "tag": "MK",
          "from": "Document author (initials = MK for Mayank)",
          "content": "Direct edit instructions, factual corrections, rephrasing requests, structural changes",
          "action": "Apply edits as written; treat as imperative; only push back if ambiguous"
        }
      ]
    }
    
  2. Tell the user verbatim:

    Saved your feedback tag config to ~/.mstack/dev/feedback-tags.json. Pre-seeded with MK as the default. Edit this file directly to add, modify, or delete tags later.

  3. Use AskUserQuestion: "Want to add another tag now? You can also add more later by editing the file." with options:

    • A) No, continue with MK
    • B) Yes, add another tag
  4. If the user picks B, ask 4 questions in sequence (one AskUserQuestion call each, free-text answers):

    • "What tag prefix? (short uppercase letters only — e.g., REV, FB, TODO. Will be matched case-insensitively in documents.)"
    • "Who are these comments from? (e.g., 'External reviewer')"
    • "What do these comments typically contain? (e.g., 'Suggestions and open questions')"
    • "What action should I take with these comments? (e.g., 'Treat as suggestions; flag for discussion before applying')"

    Read the current config, append the new tag object to the tags array, write the updated file. Then ask "Add another?" again — loop until user says no.

Read the full file on GitHub · 145 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 · 145 lines · 83 tokens per session scan A 5805f3a95b2c

Subscribe to this mod's changes

review-feedback is a skill published in the GitHub repository mayank-io/mstack (5 stars, last pushed 8d ago), licensed MIT. It adds 83 tokens to every session and 1,441 once invoked, about $0.0004 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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