apply-feedback

apply-feedback is a skill for Claude Code from mayank-io/mstack. It costs 78 tokens per session (1,224 once invoked), scanned A, original, MIT.

A feedback-application skill that reads tagged review comments and applies them to the current document. Tags such as [MK] identify different reviewers or instructions.

In plain words
What is it for?
It is for applying tagged comments such as [MK] or [REV] and maintaining the configuration that explains each tag.
Why use it?
It turns marked-up review notes into document edits while following the interpretation rules saved for each tag.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: names the AskUserQuestion tool.

Part of the dev plugin — 12 skills shipped together

Good fit It is for applying tagged comments such as [MK] or [REV] and maintaining the configuration that explains each tag.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mayank-io/mstack/apply-feedback
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 mayank-io/mstack --skill apply-feedback
Clone the repo
git clone --depth 1 https://github.com/mayank-io/mstack

Made for: Claude Code.

Or install dev, the plugin that ships this one along with the rest of its 12 skills.

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 apply-feedback

README.md
[![agentmods](https://agentmods.dev/badge/skills/mayank-io/mstack/apply-feedback/github.svg)](https://agentmods.dev/skills/mayank-io/mstack/apply-feedback)
Your own site
<a href="https://agentmods.dev/skills/mayank-io/mstack/apply-feedback"><img src="https://agentmods.dev/badge/skills/mayank-io/mstack/apply-feedback/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 apply-feedback

Your own site · 80×15
<a href="https://agentmods.dev/skills/mayank-io/mstack/apply-feedback"><img src="https://agentmods.dev/badge/skills/mayank-io/mstack/apply-feedback.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 78 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,224 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 $0.00078 $0.01224
Opus 5.5 $0.00031 $0.00490
Sonnet 5.5 $0.00016 $0.00245
Haiku 4.5 $0.00008 $0.00122

Measured 2mo ago against content hash dc4b8b9026d7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

apply-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 2mo 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/apply-feedback/SKILL.md · 112 lines

How it starts

The opening of the file, as written. The whole thing — 112 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 · 112 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. 2mo ago First seen · 112 lines · 78 tokens per session scan A dc4b8b9026d7

Subscribe to this mod's changes

apply-feedback is a skill published in the GitHub repository mayank-io/mstack (6 stars, last pushed 3d ago), licensed MIT. It adds 78 tokens to every session and 1,224 once invoked, about $0.0003 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 2026-08-31.

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