From blueprint-reviewer
Review a GitHub issue using the issue-phase rubric library. Runs core reviewers (devils_advocate_issue, spec_fidelity, acceptance_criteria_clarity) and LLM-picked conditional extras. Findings posted as a single issue comment with summary table + per-reviewer details.
How this skill is triggered — by the user, by Claude, or both
Slash command
/blueprint-reviewer:issue-reviewWhen to use
Use this skill when the user wants to: Direct invocation: - "review issue infiquetra/campps-mvp#42" - "review this issue: <github URL>" - "/issue-review infiquetra/mimir#418" Pre-Ready / pre-card-pickup: - "before I move this to Ready, review it" - "is this issue agent-ready?" - "are the ACs tight enough?" Targeted reviewer: - "is this issue right-sized?" - "does this issue have enough technical context?" - "does this descend from spec X?" Surveying: - "what reviewers fire on the issue phase?"
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Run the issue-phase reviewer panel against a GitHub issue, producing
Run the issue-phase reviewer panel against a GitHub issue, producing scored findings and posting them as a single issue comment with summary.
~/.claude/plugins/cache/infiquetra-plugins/blueprint-reviewer/0.1.0/scripts/lifecycle_review.py
(During development, also at:
~/workspace/infiquetra/infiquetra-claude-plugins/plugins/blueprint-reviewer/scripts/lifecycle_review.py)
If the user pointed at a <owner>/<repo>#<num> or a GitHub issue URL,
parse it. Otherwise ask: "which issue should I review?"
Fetch the issue body + metadata:
gh issue view <owner>/<repo>#<num> --json title,body,labels,state,assignees,projectItems
If gh returns "issue is closed," ask the user whether to proceed
(closed issues are usually NOT worth reviewing unless reopening
them is on the table).
The issue should descend from a spec. Look for:
Spec: link in the issue body (typical convention)*-blueprint repo's specs/<area>/<spec>.mdIf the spec is named, READ IT — spec_fidelity checks descent. If
no spec is named, that's already a spec_fidelity finding.
For repos in the working set (e.g. infiquetra/campps-mvp), the
parent spec typically lives in the corresponding blueprint repo
(e.g. infiquetra/campps-blueprint/specs/...).
Before reviewing, read any prior comments on the issue:
gh issue view <owner>/<repo>#<num> --comments
If a previous review-comment exists (the comment will have a summary table), don't repeat findings already raised — call out which findings persist and which are new.
Always: all issue-phase cores:
python3 <SCRIPT> rubrics list-cores --phase issue
Today returns: devils_advocate_issue, spec_fidelity,
acceptance_criteria_clarity.
Conditionally: pick 0-3 extras:
python3 <SCRIPT> rubrics list-extras --phase issue
Picking heuristics:
issue_sizingcontext_completenessprerequisite_mappingFor each reviewer:
python3 <SCRIPT> rubrics read --phase issue --slug <slug>
Apply the rubric to the issue. Score, verdict, findings.
Notes specific to issue-phase reviewers:
Format the entire review as a single GitHub comment with summary table and per-reviewer details. Don't post multiple comments — one consolidated comment is better for issue-page readability.
Comment template:
## Issue review — <date> UTC
| Reviewer | Score | Verdict | Headline |
|---|---|---|---|
| devils_advocate_issue | 8.0 | PROCEED | well-scoped; one minor scope smell |
| spec_fidelity | 9.0 | PROCEED | clean descent from spec X |
| acceptance_criteria_clarity | 7.5 | REVISE | AC #2 lacks methodology |
| issue_sizing (extra) | 8.5 | PROCEED | one PR; balanced ACs |
## Required changes
- **acceptance_criteria_clarity (REVISE):** AC #2 says "p99 < 200ms" —
needs methodology: under what load? from where? on what hardware?
## Optional improvements
- **devils_advocate_issue (PROCEED-with-nit):** consider whether the
refactor of `helper.dart` could be extracted to a separate issue
if it grows.
---
🤖 *Posted by `/issue-review` — see [blueprint-reviewer plugin](https://github.com/infiquetra/infiquetra-claude-plugins/tree/main/plugins/blueprint-reviewer) for rubric details.*
Post via:
gh issue comment <owner>/<repo>#<num> --body-file /tmp/review-comment.md
After posting:
Issue review is advisory:
Findings are posted; the human decides whether to address them and when to promote the issue to Ready.
/issue-review owner/repo#42 --reviewers spec_fidelity,acceptance_criteria_clarity
/issue-review owner/repo#42 --cores-only
/issue-review owner/repo#42 --dry-run # surface findings, don't post
/issue-review owner/repo#42 --no-post # print findings, don't post comment
This skill is the manual path — invoked by the user directly.
The automated path (Phase C, future) will trigger when an issue moves to the Backlog column on the Olympus project board, run the same rubrics, and post the same comment. The skill and the orchestrator share the rubric library so findings are consistent.
If the user asks "what's the difference between running this manually vs. auto?", the answer is: timing and scope of conditionals. The auto path runs only the cores plus a deterministic set of extras based on issue labels; the manual path lets you pick any extras you want.
Issues are concrete enough to expect tighter scores than specs:
These are advisory anchors; you (the human) decide whether to act.
npx claudepluginhub infiquetra/infiquetra-antigravity-plugins --plugin blueprint-reviewerProvides behavioral guidelines to reduce common LLM coding mistakes, focusing on simplicity, surgical changes, assumption surfacing, and verifiable success criteria.
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.
Creates, edits, and optimizes skills for Claude Code, including drafting, evaluating with test prompts, iterating on performance, and improving skill descriptions for better triggering accuracy.