agentify-project
Make a project ready for AI agentic engineering by converging it toward a canonical agent-neutral structure — a lean AGENTS.md index with progressive…
Fetch all reviewer comments from a pull request URL (GitHub, Azure DevOps, …) and save them as a self-contained markdown PR-REVIEW file in the task's planning directory. Fetch only — no fixing or replying.
$ npx -y skills add eai-org/agent-toolkit --skill fetch-pr-review --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/fetch-pr-reviewContext preview
The summary Claude sees to decide when to auto-load this skill.
Fetch all reviewer comments from a pull request URL (GitHub, Azure DevOps, …) and save them as a self-contained markdown PR-REVIEW file in the task's planning directory. Fetch only — no fixing or replying.
name: fetch-pr-review description: Fetch all reviewer comments from a pull request URL (GitHub, Azure DevOps, …) and save them as a self-contained markdown PR-REVIEW file in the task's planning directory. Fetch only — no fixing or replying. license: MIT metadata: version: "1.7"
**Fetch only** — capture the review feedback left on a pull request; never fix code, reply, or judge the comments. Output is a self-contained `.PR-REVIEW.md` a fresh session can pick up and act on (e.g. via `/refine-pr-review`).
Identify the platform from the PR URL (host shape) and fetch through the matching MCP server or CLI — e.g. **GitHub MCP / `gh`** for GitHub PRs, **Azure DevOps MCP** for ADO pull requests. Use whichever equivalent tools are connected; tool name prefixes vary by config. If the input is ambiguous, or no matching MCP/CLI is available, ask the user / stop — don't guess.
Every uncertainty is confirmed with the user before proceeding: a thread's resolved status, the planning directory, the slug, anything ambiguous in between. A plausible guess is a question, not an answer.
1. **Resolve the input.** Accept a full PR URL; extract repo/project and PR id. If unrecognizable, ask. 2. **Fetch the PR metadata** — title, description, source/target branch, state, author, linked ticket/work item — and **all feedback**:
feedback. 3. **Determine each thread's status** (see Status flags). 4. **Decide the output directory** — the planning directory of the task the PR belongs to, following the project's/user's convention for where plans live (default: `.agents/plans/`). Guess the task's existing home from PR context (linked ticket id, branch name, PR title) — its `<id>-<slug>/` subdirectory, or the shared parent/group directory holding its `<id>-<slug>.TICKET.md` when the ticket lives flat there — and **confirm the guess with the user**; when not sure, always ask. If no matching exists, propose a new `<id>-<slug>` (ticket id prefix when bound to one, kebab-case slug from the PR title), confirm, and create it. 5. **Pick the file name** — `<slug>.PR-REVIEW.md`, where `<slug>` is the planning directory name — in a shared directory, the ticket's own `<id>-<slug>` instead (e.g. `1234-some-task.PR-REVIEW.md`). If it already exists and this is a new review round, write `<slug>.PR-REVIEW-2.md`, `-3`, … — **never overwrite**; history per round is kept on purpose. 6. **Write the document** (see structure below). 7. **Print the result** — project-relative paths and the next-step line.
Capture **every** comment, resolved or not, with its state from the platform's own signal (e.g. GitHub thread resolution, ADO thread status):
original status verbatim — `wontFix` is resolved but carries different intent than `fixed`.
into resolved: the code moved, but **the concern may still be valid** — say so in the document.
says "done" but the thread is still open) → **ask the user** how to mark it; never decide alone.
Must stand on its own: a fresh session with no access to the PR must be able to locate every spot in the code and understand every piece of feedback without re-fetching.
# PR review: <title>
> **Source** [<PR id>](<url>)
> **Branch** <source> → <target>
> **State** {open/merged/…}
> **Author** {display name}
> **Linked ticket** [<id>](<url>) — omit if none
> **Fetched** {today YYYY-MM-DD}
## Review verdicts — one per reviewer: verdict + summary text
## Inline threads — one ### per thread: `path:line` + the opening quote, quoted code
context/diff hunk, comments oldest first as <author> — <date>,
status flag
## General comments — non-inline human conversation, oldest first
## Bot comments — automated feedback, grouped by botOmit empty sections. Quote file paths, code, identifiers, and user-facing strings **verbatim** — never alter or translate them.
approvals, or edits.
State clearly when done, using **project-relative paths**. List any thread whose status needed a user decision and how it was marked. Then hand off the next phase as a **single copy-pasteable launch command** — session name and prompt combined, so one paste starts the session. Use the launch syntax of the agent tool in use (vendor-agnostic — `claude` below is only the example), naming the session `refine-pr-<slug>`:
claude --name refine-pr-<slug> "/refine-pr-review <output-dir>/<slug>.PR-REVIEW.md"
Then offer the alternative — clearing the current session instead (vendor-agnostic — `/clear` below is only the example; use the clear command of the agent tool in use):
OR /clear and run:
/refine-pr-review <output-dir>/<slug>.PR-REVIEW.md
A collection of generic agentic tools for common engineering tasks, designed to work with any AI agent on any kind of software project.
Make a project ready for AI agentic engineering by converging it toward a canonical agent-neutral structure — a lean AGENTS.md index with progressive…
Attach pasted images, files or URLs to a fetched ticket, saved beside its ticket file and referenced from it, or fill an attachment the fetch could not…
Check how much of a ticket is already implemented — split it into requirement blocks, judge each against the code, and save a human-readable TICKET-STATUS…
Draft, rewrite, or refine a doc for maximum token economy without losing any rule or intent. Use for docs kept in version control and regularly re-read by…
Author or refine a skill for maximum token economy without losing intent. Use when creating any new skill or editing an existing `SKILL.md`.
Audit what auto-loads into an agent session's context window and suggest lean, reversible fixes to cut startup tokens.