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npx skills add layerai/skills --skill layer-quality -a claude-code -yGeneration is not delivery. A batch comes back, and something has to decide which of it is usable, against the brief and against whatever standards the studio has already set. Layer records those standards as output scoring rules, and records where each file stands as a lifecycle status:
| Tool | Purpose |
|---|---|
list_output_scoring_rules | The rules in force for a workspace, optionally a project |
score_files | Queue a scoring run. Asynchronous and billed |
get_file_scores | Read the verdicts recorded on one file |
list_file_lifecycle_statuses | The statuses this workspace uses, with their ids |
set_file_lifecycle_status | Mark files In Review, Approved, or any other status |
Generation mechanics are in the layer skill. If a sibling skill named here is missing from your
available skills, ask the user to install it (npx skills add layerai/skills --skill <name>);
unattended, proceed from tool schemas and flag the gap.
Call list_output_scoring_rules before judging anything by eye. Each rule is a standard the studio
has written down, and a delivery that contradicts one is wrong however good it looks. Rules can be
scoped to a project as well as a workspace, so pass the project when the work belongs to one.
When rules exist, score_files queues the batch and get_file_scores reads the verdicts back.
Three things about that contract are easy to get wrong and expensive to get wrong:
score_files is asynchronous. It returns as soon as the run is queued, not with results. Poll
get_file_scores afterwards; a large request takes a few minutes.scores list means not judged yet, not a zero. Treating the queue acknowledgement as
a verdict, or an empty list as a failing score, is the defect this contract invites.estimate_* tools price it. Scoring the same file
again is allowed and appends a fresh verdict rather than replacing the old one, so a re-score
because the first call "returned nothing" is a real double spend. Read get_file_scores first.When no rules exist, say so rather than implying the output passed a gate it never met, then review against the brief.
The question is never "is this good". It is "does this do what was asked". Work back through the brief item by item:
batch_size returns variations, and the temptation is to pick the most striking one. Pick the one
closest to the brief instead, because the striking one is usually striking for a reason that will not
repeat across the rest of the set.
When no candidate is close, the fix is the prompt, not another batch. Two identical rerolls in a row mean the prompt is underspecified: go back to what the prompt failed to name (framing, lighting, background treatment) rather than spending again on the same string.
Say what is wrong with what you deliver. A run that produced three usable assets and one with a
mangled hand is reported as exactly that, not as four assets. Where a reference set was degraded,
name it (layer-reference-sets). Where a constraint was missed, name the constraint.
Creative Units were spent either way, so a quiet pass costs the user a second discovery later, on work already built on the flawed asset.
A review that lives only in chat is lost. Close it on the files themselves with
set_file_lifecycle_status, so the team sees the state in Layer: passing files to the workspace's
approved status, failures back to review or on hold. Statuses belong to the workspace and may be
renamed, reordered, removed or added to, so call list_file_lifecycle_statuses for the ids and match
by name and phase rather than assuming "Approved" exists. One call sets up to 500 files; a
status_id of null clears the status. Set a status only when the user asked for the review to be
recorded or the workflow clearly expects it, since it is visible to the whole team.
"Are these eight icons ready to ship?"
list_output_scoring_rules for the workspace and the project. Two rules exist: transparent
background, and a minimum legibility standard.get_file_scores on the eight file_id values first, in case an earlier session already judged
them. For the ones with no scores, score_files to queue a run, telling the user it spends
Creative Units since no estimate tool prices scoring.get_file_scores until scores appear. An empty list means not yet judged, so keep polling
rather than re-scoring.background_removal (layer-image-editing).list_file_lifecycle_statuses, then set_file_lifecycle_status with
the passing file_id values and the approved status's id.score_files as if it returned verdicts, when it only acknowledges the queued run.scores list as a zero rather than as not yet judged.get_file_scores already holds
verdicts: both spend again and append a second verdict.list_file_lifecycle_statuses.--- name: layer-quality description: "Use when judging Layer output before it ships: scoring generated files against a workspace's output scoring rules, reading back verdicts on a file, reviewing a batch against the brief, or choosing which candidate to deliver. Also when a studio has automated quality standards, or a set must be checked for consistency before handoff. Keywords: quality gate, scoring, review, batch, verdict, approve, QA, consistency check." license: MIT --- # Layer Quality Review ## Overview Generation is not delivery. A batch comes back, and something has to decide which of it is usable, against the brief and against whatever standards the studio has already set. Layer records those standards as output scoring rules, and records where each file stands as a lifecycle status: | Tool | Purpose | | ------------------------------ | -------------------------------------------------------- | | `list_output_scoring_rules` | The rules in force for a workspace, optionally a project | | `score_files` | Queue a scoring run. Asynchronous and billed | | `get_file_scores` | Read the verdicts recorded on one file | | `list_file_lifecycle_statuses` | The statuses this workspace uses, with their ids | | `set_file_lifecycle_status` | Mark files In Review, Approved, or any other status | Generation mechanics are in the `layer` skill. If a sibling skill named here is missing from your available skills, ask the user to install it (`npx skills add layerai/skills --skill <name>`); unattended, proceed from tool schemas and flag the gap. ## Check for rules before inventing standards Call `list_output_scoring_rules` before judging anything by eye. Each rule is a standard the studio has written down, and a delivery that contradicts one is wrong however good it looks. Rules can be scoped to a project as well as a workspace, so pass the project when the work belongs to one. When rules exist, `score_files` queues the batch and `get_file_scores` reads the verdicts back. Three things about that contract are easy to get wrong and expensive to get wrong: - **`score_files` is asynchronous.** It returns as soon as the run is queued, not with results. Poll `get_file_scores` afterwards; a large request takes a few minutes. - **An empty `scores` list means not judged yet, not a zero.** Treating the queue acknowledgement as a verdict, or an empty list as a failing score, is the defect this contract invites. - **It is billed, and there is no estimate tool for it.** Every file and rule pair is a vision-model call that spends Creative Units, and none of the `estimate_*` tools price it. Scoring the same file again is allowed and appends a fresh verdict rather than replacing the old one, so a re-score because the first call "returned nothing" is a real double spend. Read `get_file_scores` first. When no rules exist, say so rather than implying the output passed a gate it never met, then review against the brief. ## Review against the brief, not against taste The question is never "is this good". It is "does this do what was asked". Work back through the brief item by item: - The **stated constraints**: aspect ratio, pixel size, transparent background, palette, poly budget, clip length. These are pass or fail, and they are the ones most often silently missed because the image looks fine. - The **intended use**: an icon judged at its target size, a texture judged tiled at 3x3, a loop judged across its seam, a background judged with a character on it. Judging an asset out of its context is how defects reach delivery. - The **set**, not the item. For anything that belongs to a group, lay the candidates out together. Drift between siblings is invisible one at a time and obvious side by side. ## Choosing from a batch `batch_size` returns variations, and the temptation is to pick the most striking one. Pick the one closest to the brief instead, because the striking one is usually striking for a reason that will not repeat across the rest of the set. When no candidate is close, the fix is the prompt, not another batch. Two identical rerolls in a row mean the prompt is underspecified: go back to what the prompt failed to name (framing, lighting, background treatment) rather than spending again on the same string. ## Report honestly Say what is wrong with what you deliver. A run that produced three usable assets and one with a mangled hand is reported as exactly that, not as four assets. Where a reference set was degraded, name it (`layer-reference-sets`). Where a constraint was missed, name the constraint. Creative Units were spent either way, so a quiet pass costs the user a second discovery later, on work already built on the flawed asset. ## Record the outcome A review that lives only in chat is lost. Close it on the files themselves with `set_file_lifecycle_status`, so the team sees the state in Layer: passing files to the workspace's approved status, failures back to review or on hold. Statuses belong to the workspace and may be renamed, reordered, removed or added to, so call `list_file_lifecycle_statuses` for the ids and match by name and phase rather than assuming "Approved" exists. One call sets up to 500 files; a `status_id` of null clears the status. Set a status only when the user asked for the review to be recorded or the workflow clearly expects it, since it is visible to the whole team. ## Worked example "Are these eight icons ready to ship?" 1. `list_output_scoring_rules` for the workspace and the project. Two rules exist: transparent background, and a minimum legibility standard. 2. `get_file_scores` on the eight `file_id` values first, in case an earlier session already judged them. For the ones with no scores, `score_files` to queue a run, telling the user it spends Creative Units since no estimate tool prices scoring. 3. Poll `get_file_scores` until scores appear. An empty list means not yet judged, so keep polling rather than re-scoring. 4. Two fail the transparency rule. Those are not judgement calls, so they go back through `background_removal` (`layer-image-editing`). 5. View the remaining six together at their target size, not at full resolution, and check stroke weight and palette against the two icons approved earlier. 6. One has drifted heavier than the set. Reroll that one against the approved icons as references. 7. With the user's go-ahead, `list_file_lifecycle_statuses`, then `set_file_lifecycle_status` with the passing `file_id` values and the approved status's id. 8. Deliver with the state named: six passing, one rerolled, two fixed for transparency. ## Common mistakes - Judging by eye without checking whether scoring rules exist. - Reporting output as passing a gate when no rules were ever in force. - Reading `score_files` as if it returned verdicts, when it only acknowledges the queued run. - Reading an empty `scores` list as a zero rather than as not yet judged. - Re-scoring because the first call "returned nothing", or when `get_file_scores` already holds verdicts: both spend again and append a second verdict. - Hard-coding a status name or id instead of reading `list_file_lifecycle_statuses`. - Judging an icon, texture, or loop outside the context it ships in. - Reviewing set members one at a time, so drift goes unnoticed. - Picking the most striking candidate rather than the one matching the brief. - Rerolling an underspecified prompt a third time instead of fixing it. - Delivering silently around a known defect.