Official agent skill

Report Feedback

Retrieve negative feedback on AI-generated APIView comments.

OfficialMITAuto-check passed

Install Report Feedback

skills CLI

$ npx skills add Azure/azure-sdk-tools --skill report-feedback -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install Azure/azure-sdk-tools report-feedback --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/Azure/azure-sdk-tools.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/python-packages/apiview-copilot/.github/skills/report-feedback .claude/skills/report-feedback && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "report-feedback" agent skill from https://github.com/Azure/azure-sdk-tools/tree/main/packages/python-packages/apiview-copilot/.github/skills/report-feedback into .claude/skills/report-feedback/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "report-feedback", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/Azure/azure-sdk-tools/tree/main/packages/python-packages/apiview-copilot/.github/skills/report-feedback

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add Azure/azure-sdk-tools --skill report-feedback -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install Azure/azure-sdk-tools report-feedback --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Azure/azure-sdk-tools.git skills-src && mkdir -p .agents/skills && cp -r skills-src/packages/python-packages/apiview-copilot/.github/skills/report-feedback .agents/skills/report-feedback && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "report-feedback" agent skill from https://github.com/Azure/azure-sdk-tools/tree/main/packages/python-packages/apiview-copilot/.github/skills/report-feedback into .agents/skills/report-feedback/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "report-feedback", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add Azure/azure-sdk-tools --skill report-feedback -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install Azure/azure-sdk-tools report-feedback --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Azure/azure-sdk-tools.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/packages/python-packages/apiview-copilot/.github/skills/report-feedback .cursor/skills/report-feedback && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "report-feedback" agent skill from https://github.com/Azure/azure-sdk-tools/tree/main/packages/python-packages/apiview-copilot/.github/skills/report-feedback into .cursor/skills/report-feedback/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "report-feedback", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/Azure/azure-sdk-tools.git --path packages/python-packages/apiview-copilot/.github/skills/report-feedback

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add Azure/azure-sdk-tools --skill report-feedback -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install Azure/azure-sdk-tools report-feedback --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Azure/azure-sdk-tools.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/packages/python-packages/apiview-copilot/.github/skills/report-feedback .gemini/skills/report-feedback && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "report-feedback" agent skill from https://github.com/Azure/azure-sdk-tools/tree/main/packages/python-packages/apiview-copilot/.github/skills/report-feedback into .gemini/skills/report-feedback/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "report-feedback", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install Azure/azure-sdk-tools report-feedback

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add Azure/azure-sdk-tools --skill report-feedback -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/Azure/azure-sdk-tools.git skills-src && mkdir -p .github/skills && cp -r skills-src/packages/python-packages/apiview-copilot/.github/skills/report-feedback .github/skills/report-feedback && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "report-feedback" agent skill from https://github.com/Azure/azure-sdk-tools/tree/main/packages/python-packages/apiview-copilot/.github/skills/report-feedback into .github/skills/report-feedback/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "report-feedback", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add Azure/azure-sdk-tools --skill report-feedback -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install Azure/azure-sdk-tools report-feedback --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Azure/azure-sdk-tools.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/packages/python-packages/apiview-copilot/.github/skills/report-feedback .opencode/skills/report-feedback && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "report-feedback" agent skill from https://github.com/Azure/azure-sdk-tools/tree/main/packages/python-packages/apiview-copilot/.github/skills/report-feedback into .opencode/skills/report-feedback/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "report-feedback", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: report-feedback
GitHub stars: 134
Token cost: ~1.8k tokens
SKILL.md length: 765 words
Files: 1
Skills in repo: 35
Repo updated: Oct 6, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Retrieve negative feedback on AI-generated APIView comments.

Works in 2 steps: Run the Command → Answer Follow-up Questions
: feedback report
SKILL.md covers When to Use, Understanding Feedback, Defaults and Implicit Bad Comments, plus 4 more sections
Calls python

What it does

Report Feedback is an agent skill from Azure/azure-sdk-tools, published by the product's own GitHub organization. Retrieve negative feedback on AI-generated APIView comments. Use for: feedback report, comment feedback, show feedback, feedback for March, what feedback, downvotes, deleted comments, bad comments.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Tools repository leveraged by the Azure SDK team. The licence is MIT.

When your agent uses it

: feedback report
Comment feedback
Feedback for March
Deleted comments

Example prompts

“/report-feedback”

Requirements

Python 3

Workflow steps

2 steps, taken from the step headings in SKILL.md.

Run the Command
Answer Follow-up Questions

What it can do on your machine

Read from SKILL.md and the folder at commit 69f4006. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Report Feedback loads about 1.8k tokens when it runs. Until then it costs about 53 tokens; SKILL.md has 765 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~53
When it runs · the whole SKILL.md, loaded when a task matches: ~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Azure/azure-sdk-tools at commit 69f4006, republished under its MIT licence (© Azure). 765 words, ~1,777 tokens.

Download SKILL.mdSave it as .claude/skills/report-feedback/SKILL.md (or your agent's skills folder).

name: report-feedback
description: Retrieve negative feedback on AI-generated APIView comments. Use for: feedback report, comment feedback, show feedback, feedback for March, what feedback, downvotes, deleted comments, bad comments.
argument-hint: Month name (e.g. 'March') or language + month (e.g. 'Python for March')

Report Feedback

When to Use

Reviewing negative feedback (downvotes, deletions) on AI-generated comments
Investigating comment quality issues for a specific language
Understanding why AI comments were marked bad or deleted during a period

Understanding Feedback

Feedback describes why a bad AI comment is bad. Each feedback entry includes a reason (e.g., FactuallyIncorrect, AcceptedSDKPattern, RenderingBug) and an optional free-text comment. There are no upvotes in the feedback data — upvotes on comments exist in APIView but are not surfaced through this report. All feedback returned by this command is negative.

Do NOT state that feedback is "100% bad" or highlight that all feedback is negative in your summary. This is always the case by design — the report only surfaces negative feedback. Treat it as a given and focus the summary on the count, reasons, themes, and actionable insights.

Defaults

Unless the user says otherwise, always apply these defaults:

Environment: production
Language: All languages (do not pass --language unless user specifies one)
Exclude: Do not pass --exclude unless user asks to filter out certain feedback types
Include implicit: Always pass --include-implicit by default. Only omit it if the user explicitly asks to exclude implicit bad comments.
Format: JSON (do not pass --format)

Implicit Bad Comments

The --include-implicit flag also returns implicit bad comments: AI comments on approved revisions that were never upvoted, downvoted, resolved, and have no Feedback entries. The inference is that the reviewer ignored them and approved anyway, suggesting they were unhelpful.

Date semantics differ: Explicit feedback is filtered by feedback submission time (Feedback[].SubmittedOn / ChangeHistory[].ChangedOn), but implicit bad is filtered by comment creation time (CreatedOn). A comment created in January with no interaction will appear in January's implicit bad results, not March's.

This skill always passes --include-implicit (the CLI flag defaults to off, but the skill includes it for completeness). It has a weaker signal than explicit feedback because there is no reason or confirmation — just silence. Only omit --include-implicit if the user explicitly asks to exclude them (e.g., "only explicit feedback", "exclude implicit bad").

The output will contain items with "FeedbackTypes": ["implicit_bad"].

Summarizing Implicit Bad

When presenting results, break out implicit bad themes separately from explicit feedback:

Explicit feedback — Summarize count, breakdown by reason, and themes for items that have explicit feedback types (e.g., bad, delete).
Implicit bad — Summarize separately: count, common comment topics/patterns, and any notable themes. Note that these lack a reason — group them by the comment content or guideline referenced instead.

This separation helps the user understand the strength of signal behind each theme.

Date Resolution

The user will typically specify a calendar month by name (e.g. "March", "January 2025"). Resolve to the full month date range:

User says	start_date	end_date
"March" (current year)	`YYYY-03-01`	`YYYY-03-31`
"January 2025"	`2025-01-01`	`2025-01-31`
"March 1 to March 15"	`YYYY-03-01`	`YYYY-03-15`

When only a month name is given without a year, use the current year. Be careful with month lengths (28/29/30/31 days).

Show full SKILL.md (282 more words)Show less

Running the Command

Step 1: Run the Command

Show the resolved command and run it immediately in a foreground terminal with a 120-second timeout (timeout: 120000). Redirect to a file since feedback output can be very large.

Full terminal command (cleanup + run):

powershell

New-Item -ItemType Directory -Path output -Force | Out-Null; if (Test-Path output/feedback_output.json) { Remove-Item output/feedback_output.json }; python cli.py report feedback -s <start_date> -e <end_date> --include-implicit | Out-File -Encoding UTF8 output/feedback_output.json

After the command completes, read the output file with read_file to get the JSON results. Summarize the findings for the user (total count, breakdown by feedback reason, common themes, etc.).

Step 2: Answer Follow-up Questions

For follow-up questions about the same data (filtering, counting, searching), read the output file with read_file instead of re-running the command. The file is at output/feedback_output.json.

Examples

powershell

# All feedback for March 2025 (implicit bad included by default)
python cli.py report feedback -s 2025-03-01 -e 2025-03-31 --include-implicit

# Python feedback only
python cli.py report feedback -s 2025-03-01 -e 2025-03-31 -l python --include-implicit

# Exclude implicit bad (only explicit feedback)
python cli.py report feedback -s 2025-03-01 -e 2025-03-31

# Exclude good feedback (show only bad and deleted)
python cli.py report feedback -s 2025-03-01 -e 2025-03-31 --include-implicit --exclude good

# YAML output
python cli.py report feedback -s 2025-03-01 -e 2025-03-31 --include-implicit --format yaml

# Staging environment
python cli.py report feedback -s 2025-03-01 -e 2025-03-31 --include-implicit --environment staging

Available Flags

Flag	Type	Default	Description
`--start-date` / `-s`	string	required	Start date (`YYYY-MM-DD`)
`--end-date` / `-e`	string	required	End date (`YYYY-MM-DD`)
`--language` / `-l`	string	all	Language to filter by (e.g., `python`, `Go`, `C#`)
`--environment`	string	`production`	`production` or `staging`
`--exclude`	list	none	Feedback types to exclude: `good`, `bad`, `delete`, `implicit_bad`
`--include-implicit`	flag	off	Include implicit bad comments (unresolved, unvoted on approved revisions)
`--format` / `-f`	string	`json`	Output format: `json` or `yaml`

Gotchas

Output can be large: Redirect to file and use read_file rather than relying on terminal output.
Date range semantics are mixed: Explicit feedback filters by feedback submission time (a comment created in January but downvoted in March appears in March). Implicit bad filters by comment creation time (a comment created in January with no interaction appears in January).
Use python cli.py not .\avc: The avc.bat script may resolve to system Python.
Do NOT use 2>&1: Merges stderr into stdout, corrupting JSON. Only redirect stdout.
Do NOT use >: Produces UTF-16 in PowerShell 5.1. Use | Out-File -Encoding UTF8.
Month end dates: February has 28/29 days, April/June/Sept/Nov have 30 days.

Files

Just SKILL.md in packages/python-packages/apiview-copilot/.github/skills/report-feedback of Azure/azure-sdk-tools.

Open the folder on GitHubat commit 69f4006

Compare with similar skills

Report Feedback next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Report Feedback compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Report Feedback this skillAzure/azure-sdk-tools	134	—	~1.8k	Automated safety check: Pass	MIT	today
Feedbackcodewhale-hq/Codewhale	41k	—	~272	Automated safety check: Pass	MIT	today
Comment Checkercode-yeongyu/oh-my-openagent	70k	—	~160	Automated safety check: Pass	Custom licence	today
Iterative Retrievalaffaan-m/ECC	274k	7 repos	~1.6k	Automated safety check: Pass	MIT	2 days ago
No Commentscursor/plugins	10k	7 repos	~640	Automated safety check: Pass	None	today
Commentsanthropics/claude-for-legal	9.6k	1 repos	~1k	Automated safety check: Pass	Apache-2.0	7 days ago

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Questions about Report Feedback

What does Report Feedback do?

Retrieve negative feedback on AI-generated APIView comments. Report Feedback is an agent skill from Azure/azure-sdk-tools, published by the product's own GitHub organization. Retrieve negative feedback on AI-generated APIView comments.

When should I use Report Feedback?

Report Feedback fits situations like: : feedback report; comment feedback; feedback for March; deleted comments.

How do I install Report Feedback in Claude Code?

Run `npx skills add Azure/azure-sdk-tools --skill report-feedback -a claude-code`. Or copy the skill folder (packages/python-packages/apiview-copilot/.github/skills/report-feedback in Azure/azure-sdk-tools) into .claude/skills/report-feedback in your project. Claude Code loads it when a task matches its description.

How do I install Report Feedback in Codex?

Run `npx skills add Azure/azure-sdk-tools --skill report-feedback -a codex`. Or copy the skill folder (packages/python-packages/apiview-copilot/.github/skills/report-feedback in Azure/azure-sdk-tools) into .agents/skills/report-feedback in your project. Codex loads it when a task matches its description.

Can I use Report Feedback in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Azure/azure-sdk-tools --skill report-feedback -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/report-feedback, .gemini/skills/report-feedback, .github/skills/report-feedback and .opencode/skills/report-feedback in your project.

What does Report Feedback need to run?

Going by SKILL.md and its folder, Report Feedback needs the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Report Feedback access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Report Feedback safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Report Feedback use?

Report Feedback is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Report Feedback use?

About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Report Feedback?

Skills that share tags, products or a category with Report Feedback: Feedback (codewhale-hq/Codewhale, 41k stars), Comment Checker (code-yeongyu/oh-my-openagent, 70k stars), Iterative Retrieval (affaan-m/ECC, 274k stars) and No Comments (cursor/plugins, 10k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Report Feedback?

Azure (a GitHub organization, an official publisher) maintains it in Azure/azure-sdk-tools, which has 134 GitHub stars. The repository holds 35 skills in this directory. The repository was last updated on October 6, 2026.

Source: Azure/azure-sdk-tools on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Report Feedback

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Report Feedback

When to Use

Understanding Feedback

Defaults

Implicit Bad Comments

Summarizing Implicit Bad

Date Resolution

Running the Command

Step 1: Run the Command

Step 2: Answer Follow-up Questions

Examples

Available Flags

Gotchas

Files

Compare with similar skills

Similar skills

More from Azure/azure-sdk-tools

Questions about Report Feedback