Review a work item through multiple quality lenses and
Scanned 9/10/2026
Install to Claude Code
npx -y skills add atomicinnovation/accelerator --skill review-work-item --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Review Work Item?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/atomicinnovation-review-work-item)More formats (shields.io, HTML) on the badges page.
---
name: review-work-item
description: Review a work item through multiple quality lenses and
collaboratively iterate based on findings. Use when the user wants to
evaluate a work item before implementation or escalation.
argument-hint: "[path to work item file]"
allowed-tools:
- Bash(accelerator config *)
- Bash(accelerator work *)
- Bash(accelerator corpus metadata derive)
- Bash(accelerator corpus frontmatter validate *)
---
# Review Work Item
!`accelerator config context --skill review-work-item --fail-safe`
!`accelerator config agents --fail-safe`
If no "Agent Names" section appears above, use these defaults:
accelerator:reviewer, accelerator:codebase-locator,
accelerator:codebase-analyser, accelerator:codebase-pattern-finder,
accelerator:documents-locator, accelerator:documents-analyser,
accelerator:web-search-researcher.
!`accelerator config review work-item --fail-safe`
**Work items directory**: !`accelerator config path work --fail-safe`
**Work item reviews directory**: !`accelerator config path review_work --fail-safe`
## Work Item Review Template
The template below defines the frontmatter and body structure that every
work item review must carry. Read it now — use it to guide what information
you record in Steps 3-4 and what shape you persist in Step 4.8.
!`accelerator config template work-item-review --fail-safe`
You are tasked with reviewing a work item through quality lenses and then
collaboratively iterating the work item based on findings.
## Initial Response
When this command is invoked:
1. **Check if a work item path or ID was provided**: invoke the
resolver:
```
accelerator work resolve <argument>
```
The resolver respects `work.id_pattern` and accepts paths, full IDs
(`PROJ-0042`), and bare numbers.
- **Exit 0**: stdout is the absolute path. Read the work item
immediately and FULLY, then begin the review process.
- **Exit 1**: unrecognised input. Print the resolver's error and
offer to run `/list-work-items`.
- **Exit 2**: ambiguous match. The resolver lists candidates with
source-category tags. Ask the user to disambiguate by re-running
with a full ID or path.
- **Exit 3**: no match. Print the resolver's error and offer to run
`/list-work-items`.
- **Exit 6**: the argument names a real file outside the managed work
directory. Print the resolver's error and offer to run
`/list-work-items`.
- If optional focus arguments were provided (e.g., "focus on testability"),
note them for lens selection.
2. **If no work item path or number provided**, respond with:
```
I'll help you review a work item. Please provide:
1. The path to the work item file (e.g., `{work_dir}/0042-my-work-item.md`)
2. (Optional) A work item number shorthand (e.g., `/review-work-item 42`)
3. (Optional) Focus areas to emphasise (e.g., "focus on testability")
Tip: Use `/list-work-items` to find the work item you want to review.
```
Then wait for the user's input.
## Available Review Lenses
| Lens | Lens Skill | Focus |
|------------------|---------------------|-------------------------------------------------------------------------|
| **Clarity** | `clarity-lens` | Unambiguous referents, internal consistency, jargon handling |
| **Completeness** | `completeness-lens` | Section presence, content density, kind-appropriate content |
| **Dependency** | `dependency-lens` | Implied couplings not captured — blockers, consumers, external systems |
| **Scope** | `scope-lens` | Right-sized, single coherent unit of work; decomposition; orthogonality |
| **Testability** | `testability-lens` | Measurable criteria, verifiable outcomes, verification framing |
> Note: completeness flags an *absent* Dependencies section; dependency flags
> an *empty or underspecified* section whose contents fail to name every
> coupling the work item implies.
## Process Steps
### Step 1: Read and Understand the Work Item
1. **Read the work item file FULLY** — never use limit/offset
2. **Parse the frontmatter** to note `kind` (bug, story, spike, epic, etc.)
and `status`
3. **Read any documents referenced in the References section** — these provide
context the lenses may need; do not read source code
4. **Check for existing reviews**: Glob for review documents matching
`{work_reviews_dir}/{work-item-stem}-review-*.md`. If any are found:
- Read the most recent review document (highest review number)
- Note the previous verdict, review pass count, and key findings
- Inform the user: "I found {N} previous review(s) of this work item. The
most recent (review {N}, verdict: {verdict}) will be used as context."
- The agents do NOT receive the previous review — they review the work item
fresh. But the aggregation step (Step 4) should reference the previous
review when composing cross-cutting themes and the assessment.
- If the prior review file exists but cannot be parsed (malformed
frontmatter), warn the user and proceed as if no prior review exists.
The new review creates a **new file** with the next review number (e.g.,
`-review-2.md`). Previous review files are never modified.
### Step 2: Select Review Lenses
By default, run every lens registered in `BUILTIN_WORK_ITEM_LENSES` unless the
user has provided focus arguments or config restricts the selection. The five
work item lenses cover orthogonal concerns, so there is no relevance-based
auto-selection.
**If the user provided focus arguments:**
- Map the focus areas to the corresponding lenses
- Include any additional lenses that are clearly relevant
- Briefly explain which lenses you're running
**If no focus arguments were provided:**
Run all built-in work item lenses unless:
- A lens is listed in `disabled_lenses` — remove it from the active set
- The user's configured `core_lenses` has filtered this to a subset (see below)
When `core_lenses` is set in config, apply it as the *minimum required set*;
add any remaining non-disabled lenses up to `max_lenses`. This means users
who previously pinned `core_lenses` to the Phase 4 work item lenses
(`completeness`, `testability`, `clarity`) will also receive `scope` and
`dependency` on upgrade, unless they add those names to `disabled_lenses` or
set `max_lenses` to their subset size.
Present the selection briefly — enumerate the chosen lenses with a one-line
focus each — then use the `AskUserQuestion` tool with two options:
1. **Yes, use the proposed lenses** — run the review with the selected lenses
2. **No, specify which lenses to use** — adjust the selection before running
The confirmation gate is preserved even though the default always selects every
lens; the gate is useful when focus args or config have narrowed the set.
Example (default path, no focus args, no `core_lenses` restriction):
```
I'll review this work item through all work item lenses (clarity, completeness,
dependency, scope, testability).
```
Wait for the user's answer before spawning reviewers. If they choose option 2,
ask which lenses they want using a **plain-text question only** — do NOT use
`AskUserQuestion` for this follow-up (the lens list is too large for the
4-option limit). If any lens name is unrecognised, seek clarification. Once
confirmed, update the selection and re-present it using the same
`AskUserQuestion` proceed/adjust pattern. This loop is user-controlled with
no hard termination limit.
### Step 3: Spawn Review Agents
For each selected lens, spawn the {reviewer agent} agent with a prompt that
includes the paths to the lens skill and output format files. Do NOT read these
files yourself — the agent reads them in its own context.
Compose each agent's prompt following this template:
```
You are reviewing a work item through the [lens name] lens.
## Context
The work item is at [path]. Read it fully.
Also read any source documents listed in the work item's References section.
## Analysis Strategy
1. Read your lens skill and output format files (see paths below)
2. Read the work item file fully
3. Read referenced documents from the work item's References section if present
4. Evaluate the work item through your lens, applying each key question
5. Reference specific work item sections in your findings using the `location`
field (e.g., "Acceptance Criteria", "Requirements", "Frontmatter: kind")
IMPORTANT: Do not evaluate the codebase — work item content (and any documents
it explicitly references) is the sole artefact under review. Do not run
codebase exploration agents or read source files unless the work item's
References section explicitly links to them.
## Lens
Read the lens skill at the path listed in the Lens Catalogue table in the
review configuration above. If no review configuration is present, use:
${CLAUDE_PLUGIN_ROOT}/skills/review/lenses/[lens]-lens/SKILL.md
## Output Format
Read the output format at:
${CLAUDE_PLUGIN_ROOT}/skills/review/output-formats/work-item-review-output-format/SKILL.md
IMPORTANT: Return your analysis as a single JSON code block. Do not include
prose outside the JSON block.
```
Spawn all selected agents **in parallel** using the Task tool with
`subagent_type: "!`accelerator config agent reviewer --fail-safe`"`.
**IMPORTANT**: Wait for ALL review agents to complete before proceeding.
**Handling malformed agent output**:
If an agent's response is not a clean JSON block, apply this extraction
strategy:
1. Look for a JSON code block fenced with triple backticks (optionally with
a `json` language tag)
2. If found, extract and parse the content within the fences
3. If the extracted JSON is valid, use it normally
4. If no JSON code block is found, or the JSON within it is invalid, apply
the fallback: treat the agent's entire output as a single finding with
`"suggestion"` severity (marked `synthetic: true`), attributed to that
agent's lens
Note: `"suggestion"` severity is used here (not `"major"` as in
`review-plan`) so a single flaky agent cannot deterministically force a
REVISE verdict when `work_item_revise_severity` is `major` or higher.
When falling back, warn the user that the agent's output could not be parsed
and present the raw agent output so the user can see what the agent found.
Include remediation guidance: "Try re-running with a narrower lens selection,
or file a bug with the raw output above."
### Step 4: Aggregate and Curate Findings
Once all reviews are complete:
1. **Parse agent outputs**: Extract the JSON block from each agent's response
(see the extraction strategy in Step 3). Collect the `summary`, `strengths`,
and `findings` arrays from each.
2. **Aggregate across agents**:
- Combine all `findings` arrays into a single list
- Combine all `strengths` arrays into a single list
- Collect all `summary` strings
3. **Deduplicate findings**: Where multiple agents flag the same section with
similar concerns, consider merging — but only when the findings address the
same underlying concern from different lens perspectives. When in doubt,
keep findings separate.
When merging:
- Combine the bodies, attributing each part to its lens
- Use the highest severity among the merged findings
- Use the highest confidence among the merged findings
4. **Prioritise findings**:
- Sort by severity: critical > major > minor > suggestion
- Within the same severity, sort by confidence: high > medium > low
5. **Determine suggested verdict**:
If review configuration provides verdict overrides above, apply those
thresholds instead of the defaults below:
- If `work_item_revise_severity` is `none`, skip the severity-based REVISE
rule (major count rule still applies independently)
- If any findings at or above the work item revise severity
({work item revise severity}) exist → suggest `REVISE`
- If {work item revise major count} or more `"major"` findings exist
→ suggest `REVISE`
- If fewer major findings than the threshold, or only minor/suggestion
→ suggest `COMMENT`
- If no findings at all (only strengths) → suggest `APPROVE`
Verdict meanings:
- `APPROVE` — work item is ready for implementation
- `REVISE` — work item needs changes before implementation
- `COMMENT` — observations only, work item is acceptable as-is
When presenting a `COMMENT` verdict with major findings, note: "Work item is
acceptable but could be improved — see major findings below."
6. **Identify cross-cutting themes**: Look for findings that appear across
multiple lenses — issues flagged by 2+ agents reinforce each other and
should be highlighted in the summary.
7. **Compose the review summary**:
```markdown
## Work Item Review: [Work item Title]
**Verdict:** [APPROVE | REVISE | COMMENT]
[Combined assessment: synthesise each agent's summary into 2-3 sentences
covering the overall quality of the work item across all lenses]
### Cross-Cutting Themes
[Issues that multiple lenses identified — these deserve the most attention]
- **[Theme]** (flagged by: [lenses]) — [description]
### Findings
#### Critical
- 🔴 **[Lens]**: [title]
**Location**: [work item section]
[First 1-2 sentences of body as summary]
#### Major
- 🟡 **[Lens]**: [title]
**Location**: [work item section]
[First 1-2 sentences of body as summary]
#### Minor
- 🔵 **[Lens]**: [title]
**Location**: [work item section]
[First 1-2 sentences of body as summary]
#### Suggestions
- 🔵 **[Lens]**: [title]
**Location**: [work item section]
[First 1-2 sentences of body as summary]
### Strengths
- ✅ [Aggregated and deduplicated strengths from all agents]
### Recommended Changes
[Ordered list of specific, actionable changes to the work item, prioritised by
impact. Each should reference the finding(s) it addresses.]
1. **[Change description]** (addresses: [finding titles])
[Specific guidance on what to modify in the work item]
---
*Review generated by /review-work-item*
```
8. **Write the review artifact** to `{work_reviews_dir}/`:
Derive the review filename using the work item stem and the next available
review number. The work item stem is the basename of the work item path without
the `.md` extension. For example, if the work item is
`{work_dir}/0042-improve-search.md` and no prior reviews exist,
the review filename is
`{work_reviews_dir}/0042-improve-search-review-1.md`.
To determine the next review number:
```bash
mkdir -p {work_reviews_dir}
# Glob for existing reviews of this work item
ls {work_reviews_dir}/{work-item-stem}-review-*.md 2>/dev/null
# Extract the highest number, increment by 1. If none exist, use 1.
```
Extract the work item's stable 4-digit identifier from its filename using
`accelerator work show {path} --field id`
(or parse the 4-digit prefix from the filename directly).
#### Populate frontmatter
Before writing the work item review file, capture metadata and substitute
the unified base fields and per-type extras into the template's
frontmatter block:
1. Invoke `accelerator corpus metadata derive`
to obtain `Current Date/Time (UTC):`.
2. **Substitute** every field below with the indicated value:
- `type:` ← `work-item-review`
- `id:` ← the review filename stem (without `.md`), always quoted
as a YAML string
- `title:` ← `Work Item Review: {work item title}`
- `date:` ← the `Current Date/Time (UTC):` value
- `author:` ← the author value resolved per `create-work-item/SKILL.md:578-580`
- `producer:` ← `review-work-item`
- `status:` ← `complete`
- `last_updated:` ← the same `Current Date/Time (UTC):` value
- `last_updated_by:` ← the same value resolved for `author`
- `schema_version:` ← `1` (bare integer, not quoted)
- `parent:` ← typed-linkage ref to the parent work item
(`"work-item:NNNN"`). Fill when the review names a parent;
otherwise omit the key.
- `target:` ← `"work-item:<4-digit-id>"` (e.g. `"work-item:0042"`),
the typed-linkage ref to the work item under review, per
ADR-0034. Always fill — every review has a target.
- `relates_to:` ← list of typed-linkage refs to related reviews or
artifacts (`["work-item-review:NNNN", ...]`). Fill when prior
reviews are explicit; otherwise omit the key.
- `work_item_id:` ← the same 4-digit identifier as the `target`
payload's id portion (transitional alias — see Migration Notes;
the visualiser's `read_ref_keys` consumes this scalar today)
- `reviewer:` ← the reviewer value resolved per `create-work-item/SKILL.md:578-580`
- `verdict:` ← the verdict from Step 4.5 (`APPROVE | REVISE | COMMENT`)
- `lenses:` ← the list of work-item lens names used
- `review_number:` ← `N` (the next available review number from the
glob above)
- `review_pass:` ← `1` (initial-write pass count; re-reviews bump
per the Step 7 flow)
3. Write the file with the substituted frontmatter block, followed by
the review summary composed in Step 4.7 and the per-lens results as
a final section:
```markdown
{The full review summary from Step 4.7}
## Per-Lens Results
### {Lens 1 Name}
**Summary**: {agent summary}
**Strengths**:
{agent strengths}
**Findings**:
{agent findings — each with severity, confidence, location, and body}
### {Lens 2 Name}
...
```
The `target:` field stores the work item's stable 4-digit identifier
as a typed-linkage key (e.g. `"work-item:0042"`) per ADR-0034,
providing resilience against work item renames. A `work_item_id:`
field is also emitted as a transitional alias carrying the same
4-digit identifier — the visualiser's `read_ref_keys` consumes it
as the primary work-item cross-reference key today. Both fields
encode the same edge; the duplication is bounded by the visualiser
consumer update.
**Validate the frontmatter**: after writing the review file, run
```bash
accelerator corpus frontmatter validate --file <the review file path>
```
If it exits non-zero, the document violates the canonical frontmatter
standard; report the emitted violation and fix the frontmatter before
completing.
### Step 5: Present the Review
Present the composed review summary from Step 4.7 to the user.
After presenting, offer the user control before proceeding to iteration:
```
The review is complete. Verdict: [verdict]
```
Use the `AskUserQuestion` tool with four options:
1. **Address findings** — edit the work item to resolve issues
2. **Change the verdict** — currently: [verdict]
3. **Discuss specific findings** — explore any finding in more detail
4. **Re-run specific lenses** — adjust focus and re-review
### Step 6: Collaborative Work Item Iteration
After presenting the review:
1. **Discuss findings with the user**:
- Ask which recommendations they want to address
- Clarify any findings that need more context
2. **Edit the work item based on agreed changes**:
- Use the Edit tool to modify the work item file directly
- Make targeted edits to the relevant work item sections (Summary, Context,
Requirements, Acceptance Criteria, etc.)
- Do NOT modify the `status` field — that is a separate workflow decision
- Preserve the work item's existing frontmatter and section structure
3. **Summarise changes made**:
```
I've made the following changes to the work item:
- [Change 1] — addressing [finding]
- [Change 2] — addressing [finding]
- [Skipped] — [finding discussed and decided not to address, with reason]
```
### Step 7: Offer Re-Review
After edits are complete, use the `AskUserQuestion` tool with two options:
1. **Yes, run another review pass** — re-run the relevant lenses to verify the
changes address the findings
2. **No, done** — exit without re-reviewing
If the user chooses option 1:
- Re-run **only the lenses that had findings** in the previous pass
- Use the same spawn pattern and JSON extraction strategy from Steps 3-4
- Compare previous findings against new findings to determine resolution status
- Present a shorter, delta-focused review:
```
## Re-Review: [Work item Title]
**Verdict:** [APPROVE | REVISE | COMMENT]
### Previously Identified Issues
- [emoji] **[Lens]**: [title] — Resolved / Partially resolved / Still present
### New Issues Introduced
- [emoji] **[Lens]**: [title] — [brief description]
### Assessment
[Whether the work item is now ready for implementation or needs further iteration]
```
After composing the re-review summary, **update the review artifact**
as a single write operation:
1. Read the full content of the existing review document at
`{work_reviews_dir}/{work-item-stem}-review-{N}.md`
2. If the existing review file's frontmatter cannot be parsed (malformed
YAML or missing `---` delimiters), warn the user and write a fresh
`-review-{N+1}.md` file instead of appending in place
3. In memory, update exactly four frontmatter fields — `verdict`,
`review_pass`, `last_updated`, and `last_updated_by` — preserving
all other fields and body content verbatim. The `date` field retains
the original-review timestamp; only `last_updated` advances on
re-review. (`last_updated_by` may match `reviewer` if the
re-reviewer is the same person, but is computed independently.)
**Pre-0066-artifact handling**: when the re-reviewed artifact lacks
`last_updated:` and/or `last_updated_by:` (it was written pre-0066),
insert those fields rather than treating their absence as
malformed-frontmatter. Only an unparseable YAML block or missing
`---` delimiters triggers the fresh-`-review-{N+1}.md` fallback.
4. Append the re-review section at the end of the content
5. Write the complete modified content back to the same file in one
operation
The document reads chronologically: initial review, per-lens results,
then re-review sections in order. The frontmatter always reflects the
latest verdict and pass count:
```markdown
## Re-Review (Pass {N}) — {date}
**Verdict:** {verdict}
### Previously Identified Issues
- {emoji} **{Lens}**: {title} — {Resolved | Partially resolved | Still present}
### New Issues Introduced
- {emoji} **{Lens}**: {title} — {brief description}
### Assessment
{Whether the work item is now ready for implementation or needs further iteration}
```
If the user declines or the re-review shows all clear, the review is complete.
## Important Guidelines
1. **Read the work item fully** before doing anything else
2. **Spawn agents in parallel** — the work item lenses are independent and
should run concurrently for efficiency
3. **Synthesise, don't concatenate** — your value is in compiling a balanced
view across lenses, identifying themes, and prioritising actionable
recommendations
4. **Do not modify the work item's `status` field** — a REVISE verdict does not
automatically change the work item's status; that transition belongs to a
separate workflow decision by the team
5. **Do not run codebase exploration agents** — the reviewer agents stay
inside the work item and any documents it explicitly references; source code
is out of scope for work item review
6. **Be balanced** — highlight strengths alongside concerns
7. **Prioritise by impact** — structural issues that would block implementation
matter more than surface-level polish
8. **Handle malformed agent output gracefully** — use the `suggestion` severity
fallback (not `major`) so a single flaky agent does not force a REVISE
verdict
9. **Use emoji severity prefixes consistently** — 🔴 critical, 🟡 major,
🔵 minor/suggestion, ✅ strengths. **IMPORTANT**: Use the actual Unicode
emoji characters (🔴 🟡 🔵 ✅), NOT text shortcodes.
## What NOT to Do
- Don't skip writing the review artifact — always persist to
`{work_reviews_dir}/` so the review is visible to the team
- Don't modify the work item's `status` field during review
- Don't run codebase exploration agents or read source files
- Don't skip the lens selection step — always confirm with the user
- Don't present raw agent output — always aggregate and curate
- Don't make work item edits without user agreement
- Don't post findings as individual items for positive feedback —
strengths go in the summary only
## Relationship to Other Commands
Work item review sits in the work item lifecycle between authoring and implementation:
1. `/create-work-item` or `/extract-work-items` — Author or capture the work item
2. `/list-work-items` — Discover work items available for review
3. `/review-work-item` — Review and iterate work item quality (this command)
4. `/update-work-item` — Apply status transitions after review decisions
5. `/create-plan` — Create an implementation plan from an approved work item
!`accelerator config instructions review-work-item --fail-safe`
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!