review-work

SkillProductivity

Quality gate: verify each acceptance criterion of a completed task/work unit, run quality checks, and create follow-up tasks for gaps. Use before merging or to audit delivered work. Invoked as /agiflow:review-work <work-unit-or-task>. Uses get_work_unit, get_task, update_task, create_task, create_task_comment.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the review-work skill

What this skill tells your AI

The instructions your AI receives, as published by hashgraph-online/awesome-codex-plugins in plugins/AgiFlow/ai-plugin/skills/review-work/SKILL.md and read by ahel’s review.

Invoked as /agiflow:review-work. In hosts without slash-prompts, this skill is triggered by matching intent and drives AgiFlow via its MCP tools.

Usage:

  • /agiflow:review-work <work-unit-slug-or-id> - Review a specific work unit
  • /agiflow:review-work <task-slug-or-id> - Review a specific task
  • /agiflow:review-work - List completed items for review

Examples:

  • /agiflow:review-work DXX-WU-1 (review work unit by slug)
  • /agiflow:review-work DXX-3 (review task by slug)
  • /agiflow:review-work (interactive selection)

Purpose Verify that completed work actually meets its acceptance criteria, catches quality issues, and is ready to ship. AI code has 1.7x more defects than human-written code — review is the last line of defense before shipping.

Guardrails

  • Review what exists — do not implement fixes during review (create follow-up tasks instead).
  • Every acceptance criterion gets a pass/fail verdict with evidence.
  • Flag issues by severity: blocker (must fix), warning (should fix), note (nice to fix).
  • Be honest — a "pass" with gaps is worse than a clear "needs rework".

If a work unit or task slug/id is provided, load it with get_work_unit / get_task; otherwise list candidates with list_work_units / list_tasks for selection.


AgiFlow Project Management Guidelines

Follow the shared AgiFlow project-management guidelines in references/agiflow-agents.md — agent assignment, the task status workflow and transitions, work-unit best practices, and the tags strategy apply to this workflow.


Steps

1. Load the Work for Review

If work unit slug/id provided:

  1. Use get_work_unit MCP tool to load the work unit and its tasks.
  2. For each task in the work unit, use get_task to load full details (acceptance criteria, devInfo, comments).

If task slug/id provided: 3. Use get_task MCP tool to load the task with full details.

If nothing provided: 4. Use list_work_units with status: "completed" to show completed work units. 5. Use list_tasks with status: "Review" or status: "Done" to show completed tasks. 6. Ask user to select what to review.

2. Acceptance Criteria Audit

  1. For each task, evaluate EVERY acceptance criterion:
CriterionVerdictEvidence
[criterion text]PASS / FAIL / PARTIAL[what you observed]

Verdict rules:

  • PASS: Criterion is fully met with evidence (test results, devInfo notes, implementation confirmed)
  • FAIL: Criterion is not met or cannot be verified
  • PARTIAL: Criterion is partially met — document what's missing
  1. Check devInfo for implementation evidence:
    • Were files actually changed? (filesChanged in devInfo)
    • Did tests pass? (testResults in devInfo)
    • Is there a draft PR? (draftPr in devInfo)
    • Were acceptance criteria marked as checked?

3. Quality Checks

  1. Evaluate these quality dimensions:

Completeness:

  • Are ALL acceptance criteria addressed (not just the easy ones)?
  • Are there gaps between what was asked and what was delivered?
  • Were test cases included for critical paths?

Consistency:

  • Do the changes align with the task/work unit description?
  • Is the scope appropriate (no gold-plating, no missing pieces)?
  • Do devInfo notes match the actual changes?

Risk Assessment:

  • Are there edge cases that weren't covered?
  • Could the changes break existing functionality?
  • Are there security implications?
  • Are there performance concerns?

4. Review Comments

  1. For each task reviewed, use list_task_comments to check existing progress notes.
  2. Use create_task_comment to add your review findings:
**Review Summary**

Verdict: APPROVED / NEEDS REWORK / APPROVED WITH NOTES

**Acceptance Criteria:**
- [criterion 1]: PASS - [evidence]
- [criterion 2]: FAIL - [what's missing]

**Issues Found:**
- [BLOCKER] [description] — must fix before shipping
- [WARNING] [description] — should fix, creates tech debt
- [NOTE] [description] — minor improvement opportunity

**What's Good:**
- [positive observation]

**Next Steps:**
- [action needed, if any]

5. Verdict and Actions

  1. Based on findings, recommend one of:

APPROVED — All criteria pass, no blockers.

  • If work unit: use update_work_unit to confirm status "completed"
  • If task: use update_task to confirm status "Done"
  • Summarize what shipped and its value

APPROVED WITH NOTES — All criteria pass, minor issues.

  • Keep current status
  • Create follow-up tasks for noted improvements using batch_create_tasks
  • Document notes in task comment

NEEDS REWORK — One or more criteria fail or blockers found.

  • If work unit: use update_work_unit to set status back to "in_progress"
  • If task: use update_task to set status back to "In Progress"
  • Uncheck failed acceptance criteria
  • Document what needs to change in task comment
  • Be specific: "criterion X fails because Y, to fix do Z"

6. Work Unit Summary (if reviewing a work unit)

  1. After reviewing all tasks in the work unit, produce a rollup:
**Work Unit Review: [title]**

Tasks: [N passed] / [total] passed
Overall: APPROVED / NEEDS REWORK

| Task | Slug | Verdict | Issues |
|------|------|---------|--------|
| [title] | [slug] | PASS | 0 |
| [title] | [slug] | FAIL | 2 blockers |

[Summary of what the work unit delivers and whether it's ready]

Common Mistakes to Avoid

  • Rubber-stamping: marking PASS without checking evidence
  • Fixing issues during review instead of documenting them for rework
  • Ignoring devInfo (it contains the implementation trail)
  • Reviewing only the happy path and missing edge cases
  • Not creating follow-up tasks for issues found
  • Approving work with unchecked acceptance criteria

Signals

GitHub stars
985
Forks
276
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
review-work-hashgraph-online
Source
github.com/hashgraph-online/awesome-codex-plugins