GitHub Agents Md Maintainer
OpenHands/extensions
Create an automation that keeps AGENTS.md current in one or more GitHub repositories.
Analyzes a finished pull request that involved an agent to find what slowed or helped it, and recommends specific changes to instruction files, skills and docs.
Install Learn From PR
$ npx skills add dotnet/maui --skill learn-from-pr -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install dotnet/maui learn-from-pr --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/dotnet/maui.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/learn-from-pr .claude/skills/learn-from-pr && rm -rf skills-srcUse ~/.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/
Install the "learn-from-pr" agent skill from https://github.com/dotnet/maui/tree/main/.github/skills/learn-from-pr into .claude/skills/learn-from-pr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "learn-from-pr", 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 install https://github.com/dotnet/maui/tree/main/.github/skills/learn-from-prType 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.
$ npx skills add dotnet/maui --skill learn-from-pr -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install dotnet/maui learn-from-pr --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/dotnet/maui.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.github/skills/learn-from-pr .agents/skills/learn-from-pr && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "learn-from-pr" agent skill from https://github.com/dotnet/maui/tree/main/.github/skills/learn-from-pr into .agents/skills/learn-from-pr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "learn-from-pr", 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.
$ npx skills add dotnet/maui --skill learn-from-pr -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install dotnet/maui learn-from-pr --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/dotnet/maui.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.github/skills/learn-from-pr .cursor/skills/learn-from-pr && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "learn-from-pr" agent skill from https://github.com/dotnet/maui/tree/main/.github/skills/learn-from-pr into .cursor/skills/learn-from-pr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "learn-from-pr", 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 https://github.com/dotnet/maui.git --path .github/skills/learn-from-pr--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add dotnet/maui --skill learn-from-pr -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install dotnet/maui learn-from-pr --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/dotnet/maui.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.github/skills/learn-from-pr .gemini/skills/learn-from-pr && rm -rf skills-srcUse ~/.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/
Install the "learn-from-pr" agent skill from https://github.com/dotnet/maui/tree/main/.github/skills/learn-from-pr into .gemini/skills/learn-from-pr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "learn-from-pr", 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.
$ gh skill install dotnet/maui learn-from-prInstalls 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).
$ npx skills add dotnet/maui --skill learn-from-pr -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/dotnet/maui.git skills-src && mkdir -p .github/skills && cp -r skills-src/.github/skills/learn-from-pr .github/skills/learn-from-pr && rm -rf skills-srcUse ~/.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/
Install the "learn-from-pr" agent skill from https://github.com/dotnet/maui/tree/main/.github/skills/learn-from-pr into .github/skills/learn-from-pr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "learn-from-pr", 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.
$ npx skills add dotnet/maui --skill learn-from-pr -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install dotnet/maui learn-from-pr --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/dotnet/maui.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.github/skills/learn-from-pr .opencode/skills/learn-from-pr && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "learn-from-pr" agent skill from https://github.com/dotnet/maui/tree/main/.github/skills/learn-from-pr into .opencode/skills/learn-from-pr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "learn-from-pr", 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
learn-from-pr- GitHub stars
- 23k
- Token cost
- ~2.5k tokens
- SKILL.md length
- 1,078 words
- Files
- 1
- Skills in repo
- 27
- Repo updated
- First seen
- Licence
- MIT
At a glance
Analyzes a finished pull request that involved an agent to find what slowed or helped it, and recommends specific changes to instruction files, skills and docs.
- Works in 6 steps: Gather Data → Fix Location Analysis → Analyze Outcome → …
- Reviewing a merged PR where the agent needed many attempts
- SKILL.md covers Inputs, Outputs, Completion Criteria and When to Use, plus 6 more sections
- Calls gh
What it does
Given a PR or issue number, the agent gathers the diff and metadata with the GitHub CLI, reads the discussion, commit history, code complexity and similar past issues, and asks what would have helped an agent find the fix faster. A key step compares the files the agent attempted with the files the final fix touched. Different files are flagged as a major learning opportunity, with questions about why the agent chose them and what search would have found the right one.
The outcome is then sorted into scenarios: the agent failed, succeeded slowly or succeeded quickly, each with patterns to look for. The output is a structured analysis covering what happened, fix location, failure modes and prioritized recommendations, each with a category, priority, location, specific change and reason. The skill counts as done once at least one concrete recommendation is presented. It is not meant for PRs that are not finalized, trivial PRs or PRs without agent involvement.
When your agent uses it
- Reviewing a merged PR where the agent needed many attempts
- Working out why an agent edited the wrong files before the real fix
- Studying a fast agent success to repeat what worked
- Turning PR lessons into updates for instruction files and docs
Example prompts
- “What can we learn from PR 33352? The agent took several attempts before the fix landed.”
- “Compare the files the agent changed with the files in the final fix for this issue.”
- “That agent fix landed on the first try, so work out which docs or instructions made that possible.”
- “Write recommendations for our skills and instruction files based on how the last bug fix went.”
Requirements
- The GitHub CLI (`gh`)
- Compatibility (from SKILL.md): Requires GitHub CLI (gh)
Workflow steps
6 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit b926f05. 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:
gh
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use gh, which can reach the network depending on how they are called.
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.
Compatibility
Requires GitHub CLI (gh)
From compatibility in the SKILL.md frontmatter.
Context cost
Learn From PR loads about 2.5k tokens when it runs. Until then it costs about 81 tokens; SKILL.md has 1,078 words of instructions outside code blocks.
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 dotnet/maui at commit b926f05, republished under its MIT licence (© dotnet). 1,078 words, ~2,463 tokens.
Download SKILL.mdSave it as
.claude/skills/learn-from-pr/SKILL.md (or your agent's skills folder).- name
- learn-from-pr
- description
- Analyzes a completed PR to extract lessons learned from agent behavior. Use after any PR with agent involvement - whether the agent failed, succeeded slowly, or succeeded quickly. Identifies patterns to reinforce or fix, and generates actionable recommendations for instruction files, skills, and documentation.
- compatibility
- Requires GitHub CLI (gh)
- metadata.author
- dotnet-maui
- metadata.version
- 1.0
Learn From PR
Extracts lessons learned from a completed PR to improve repository documentation and agent capabilities.
Inputs
| Input | Required | Source |
|---|---|---|
| PR number or Issue number | Yes | User provides (e.g., "PR #33352" or "issue 33352") |
Outputs
Learning Analysis - Structured markdown with:
- What happened (problem, attempts, solution)
- Fix location analysis (attempted vs actual)
- Failure modes identified
- Prioritized recommendations
Actionable Recommendations - Each with:
- Category, Priority, Location, Specific Change, Why It Helps
Completion Criteria
The skill is complete when you have:
- Gathered PR diff and metadata
- Analyzed fix location (attempted vs actual)
- Identified failure modes
- Generated at least one concrete recommendation
- Presented findings to user
When to Use
- After agent failed to find the right fix
- After agent succeeded but took many attempts
- After agent succeeded quickly (to understand what worked)
- When asked "what can we learn from PR #XXXXX?"
When NOT to Use
- Before PR is finalized (use
pr-finalizefirst) - For trivial PRs (typo fixes, simple changes)
- When no agent was involved (nothing to analyze)
Workflow
Step 1: Gather Data
# Required: Get PR info
gh pr view XXXXX --json title,body,files
gh pr diff XXXXXAnalyze the PR to extract learning:
- PR discussion - Comments reveal what was tried
- Commit history - Multiple commits may show iteration
- Code complexity - Non-obvious fixes suggest learning opportunities
- Similar past issues - Search for related bugs
Focus on: "What would have helped an agent find this fix faster?"
Step 2: Fix Location Analysis
Critical question: Did agent attempts target the same files as the final fix?
# Where did final fix go?
gh pr view XXXXX --json files --jq '.files[].path' | grep -v test| Scenario | Implication |
|---|---|
| Same files | Agent found right location |
| Different files | Major learning opportunity - document why |
If different files: Answer these questions:
- Why did agent think that was the right file?
- What search would have found the correct file?
Step 3: Analyze Outcome
Determine which scenario applies and look for the relevant patterns:
Scenario A: Agent Failed
| Pattern | Indicator |
|---|---|
| Wrong file entirely | All attempts in File A, fix in File B |
| Tunnel vision | Only looked at file mentioned in error |
| Trusted issue title | Issue said "crash in X" so only looked at X |
| Pattern not generalized | Fixed one instance, missed others |
| Didn't search codebase | Never found similar code patterns |
| Missing platform knowledge | Didn't know iOS/Android/Windows specifics |
| Wrong abstraction layer | Fixed handler when problem was in core |
| Misread error message | Error pointed to symptom, not cause |
| Incomplete context | Didn't read enough surrounding code |
| Over-engineered | Complex fix when simple one existed |
Scenario B: Agent Succeeded Slowly (many attempts)
| Pattern | Indicator |
|---|---|
| Correct file, wrong approach | Found right file but tried wrong fixes first |
| Needed multiple iterations | Each attempt got closer but wasn't quite right |
| Discovery was slow | Eventually found it but search was inefficient |
| Missing domain knowledge | Had to learn something that could be documented |
Key question: What would have gotten agent to the solution faster?
Scenario C: Agent Succeeded Quickly
| Pattern | Indicator |
|---|---|
| Good search strategy | Found right file immediately |
| Understood the pattern | Recognized similar issues from past |
| Documentation helped | Existing docs pointed to solution |
| Simple, minimal fix | Didn't over-engineer |
Key question: What made this work? Should we reinforce this pattern?
Step 4: Find Improvement Locations
# Discover where agent guidance lives
find .github/instructions -name "*.instructions.md" 2>/dev/null
find .github/skills -name "SKILL.md" 2>/dev/null
ls docs/design/ 2>/dev/null
ls .github/copilot-instructions.md 2>/dev/null| Location | When to Add Here |
|---|---|
.github/instructions/*.instructions.md | Domain-specific AI guidance (testing patterns, platform rules) |
.github/skills/*/SKILL.md | Skill needs new step, checklist, or improved workflow |
/docs/design/*.md | Detailed architectural documentation |
.github/copilot-instructions.md | General AI workflow guidance |
| Code comments | Non-obvious code behavior |
Step 5: Generate Recommendations
For each recommendation, provide:
- Category: Instruction file / Skill / Architecture doc / Inline comment / Linting issue
- Priority: High (prevents class of bugs) / Medium (helps discovery) / Low (nice to have)
- Location: Exact file path
- Specific Change: Exact text to add
- Why It Helps: Which failure mode it prevents
Prioritization factors:
- How common is this pattern?
- Would future agents definitely hit this again?
- How hard is it to implement?
Pattern-to-Improvement Mapping (Failures/Slow Success):
| Pattern | Likely Improvement |
|---|---|
| Wrong file entirely | Check /docs/design/ for component relationships |
| Tunnel vision | Instruction file: "Always search for pattern across codebase" |
| Missing platform knowledge | Platform-specific instruction file |
| Wrong abstraction layer | Reference /docs/design/HandlerResolution.md |
| Misread error message | Code comment explaining the real cause |
| Over-engineered | Skill enhancement: "Try simplest fix first" |
Pattern-to-Improvement Mapping (Quick Success - reinforce):
| Pattern | Improvement |
|---|---|
| Good search strategy | Document the search pattern that worked in skills |
| Documentation helped | Note which docs were valuable, ensure they stay updated |
| Recognized pattern | Add to instruction files as known pattern |
Show full SKILL.md (378 more words)Show less
Step 6: Present Findings
Present your analysis covering:
- What happened and what made it hard
- Where agent looked vs actual fix location
- Which patterns applied and evidence
- Prioritized recommendations with full details (category, priority, location, exact change, why it helps)
Error Handling
| Situation | Action |
|---|---|
| PR not found | Ask user to verify PR number |
| No agent involvement evident | Ask user if they still want analysis |
| Can't determine failure mode | State "insufficient data" and what's missing |
Constraints
- Analysis only - Don't apply changes (use learn-from-pr agent for that)
- Actionable recommendations - Every recommendation must have specific file path and text
- Don't duplicate - Check existing docs before recommending new ones
- Focus on high-value learning - Skip trivial observations
- Respect PR scope - Don't recommend improvements unrelated to the PR's learnings
Examples
Example: Wrong File Entirely
PR #33352 - TraitCollectionDidChange crash on MacCatalyst
What happened:
- Issue title: "ObjectDisposedException in ShellSectionRootRenderer"
- Agent made 11 attempts, ALL in
ShellSectionRootRenderer.cs - Actual fix was in
PageViewController.cs
Failure Mode: Trusted issue title instead of searching for pattern.
Recommendation:
- Category: Instruction File
- Location:
.github/instructions/ios-debugging.instructions.md - Change: "When fixing iOS crashes, search for the PATTERN across all files, not just the file named in the error"
- Why: Prevents tunnel vision on named file
Example: Slow Success
PR #34567 - CollectionView scroll position not preserved
What happened:
- Agent took 5 attempts to find fix
- First 3 attempts were in wrong layer (handler vs core)
- Eventually found it after reading more context
- Final fix was simple once the right layer was identified
Pattern: Wrong abstraction layer - fixed handler when problem was in core.
Recommendation:
- Category: Architecture Doc
- Location:
.github/architecture/handler-vs-core.md - Change: Document layer responsibilities - handlers map properties, core handles behavior
- Why: Helps agent identify correct layer faster
Example: Quick Success
PR #35678 - Button disabled state not updating
What happened:
- Agent found fix in 1 attempt
- Searched for "IsEnabled" pattern across codebase immediately
- Found similar past fix in another control and applied same approach
- Simple, minimal change
Pattern: Good search strategy - recognized pattern from similar code.
Recommendation:
- Category: Skill Enhancement
- Location:
.github/skills/try-fix/SKILL.md - Change: Add to search strategy: "Search for same property pattern in other controls"
- Why: Reinforces successful discovery technique
Integration
- pr-finalize → Use first to verify PR is ready
- learn-from-pr skill → Analysis only (this skill)
- learn-from-pr agent → Analysis + apply changes
For automated application of recommendations, use the learn-from-pr agent instead.
© dotnet, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in .github/skills/learn-from-pr of dotnet/maui.
Open the folder on GitHubat commit b926f05
Compare with similar skills
Learn From PR 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Learn From PR this skilldotnet/maui | 23k | — | ~2.5k | Automated safety check: Pass | MIT | |
| GitHub Agents Md MaintainerOpenHands/extensions | 158 | — | ~3k | Automated safety check: Pass | MIT | |
| Openiap Workflowshyodotdev/openiap | 154 | — | ~2k | Automated safety check: Pass | MIT | |
| Mariadb Operator PR Reviewmariadb-operator/mariadb-operator | 1k | — | ~3.3k | Automated safety check: Pass | Apache-2.0 | |
| Commit And PR389ds/389-ds-base | 294 | — | ~1k | Automated safety check: Pass | Custom licence | |
| Code Reviewsortie-ai/sortie | 196 | — | ~2.9k | Automated safety check: Pass | MIT |
Similar skills
Openiap Workflows
hyodotdev/openiap
A skill your agent uses for OpenIAP monorepo work that should follow the repository's shared agent workflows, including review-pr, audit-code, audit-security, audit-iapkit, compile-knowledge…
Mariadb Operator PR Review
mariadb-operator/mariadb-operator
Perform a structured maintainer-style PR review for the mariadb-operator repository.
Commit And PR
389ds/389-ds-base
Commit and open a PR the 389-ds-base way — "Issue NNNN - summary" subject, Bug Description/Fix Description body, Fixes:/Relates: trailer, AI-attribution trailer, and squash-merge etiquette.
Code Review
sortie-ai/sortie
Reviews pull requests in this repository for the defect classes a mechanical checklist misses: documentation that outlived the code it describes, reaction and retry state that leaks or clobbers a…
Review Changes
timothywarner-org/claude-code
Review uncommitted local changes in the current git working tree for bugs, smells, missing tests, and CLAUDE.md voice violations.
More from dotnet/maui
All 27 skills in this repo- Official
Copilot Session Failure Analysis
dotnet/maui
Mines local Copilot CLI session logs for dotnet/maui to rank costly or failing runs, tag recurring failure modes, propose repo edits and emit guard evals.
- Official
Evaluate PR Tests
dotnet/maui
Reviews the tests added in a pull request for fix coverage, quality, edge cases and test type, and recommends lighter test types where they would do.
- Official
.NET MAUI Release Readiness
dotnet/maui
Produces evidence-backed ship-readiness verdicts for .NET MAUI Servicing Releases and Previews, and drafts public-safe release handoff pages from the result.
- Official
MAUI PR Performance Analysis
dotnet/maui
Interprets pinned managed benchmark evidence for a dotnet/maui pull request and writes a narrative for the performance review workflow, without running or publishing anything.
- Official
PR Finalize
dotnet/maui
Checks that a pull request's title and description match its implementation and reviews the code for best practices before merge, without posting anything.
- Official
.NET MAUI Dependency Flow Guide
dotnet/maui
Adds MAUI-specific guardrails on top of the maestro-cli skill and Maestro MCP tools for darc, BAR, and channel or feed lookups in dotnet/maui.
Related
Works with
Categories
Questions about Learn From PR
What does Learn From PR do?
Analyzes a finished pull request that involved an agent to find what slowed or helped it, and recommends specific changes to instruction files, skills and docs. Given a PR or issue number, the agent gathers the diff and metadata with the GitHub CLI, reads the discussion, commit history, code complexity and similar past issues, and asks what would have helped an agent find the fix faster. A key step compares the files the agent attempted with the files the final fix touched.
When should I use Learn From PR?
Learn From PR fits situations like: reviewing a merged PR where the agent needed many attempts; working out why an agent edited the wrong files before the real fix; studying a fast agent success to repeat what worked; turning PR lessons into updates for instruction files and docs.
How do I install Learn From PR in Claude Code?
Run `npx skills add dotnet/maui --skill learn-from-pr -a claude-code`. Or copy the skill folder (.github/skills/learn-from-pr in dotnet/maui) into .claude/skills/learn-from-pr in your project. Claude Code loads it when a task matches its description.
How do I install Learn From PR in Codex?
Run `npx skills add dotnet/maui --skill learn-from-pr -a codex`. Or copy the skill folder (.github/skills/learn-from-pr in dotnet/maui) into .agents/skills/learn-from-pr in your project. Codex loads it when a task matches its description.
Can I use Learn From PR 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 dotnet/maui --skill learn-from-pr -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/learn-from-pr, .gemini/skills/learn-from-pr, .github/skills/learn-from-pr and .opencode/skills/learn-from-pr in your project.
What does Learn From PR need to run?
Going by SKILL.md and its folder, Learn From PR needs the command-line tools its instructions call (gh). Our summary lists: The GitHub CLI (`gh`). Compatibility (from SKILL.md): Requires GitHub CLI (gh).
Does Learn From PR access the network?
SKILL.md contains no URLs. Its commands use gh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Learn From PR 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 Learn From PR use?
Learn From PR 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 Learn From PR use?
About 2.5k tokens (SKILL.md is roughly 9.9k 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 Learn From PR?
Skills that share tags, products or a category with Learn From PR: GitHub Agents Md Maintainer (OpenHands/extensions, 158 stars), Openiap Workflows (hyodotdev/openiap, 154 stars), Mariadb Operator PR Review (mariadb-operator/mariadb-operator, 1k stars) and Commit And PR (389ds/389-ds-base, 294 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Learn From PR?
dotnet (a GitHub organization, an official publisher) maintains it in dotnet/maui, which has 23,321 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on October 8, 2026.
Source: dotnet/maui on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.