CC workspace-eval
Thin agent-facing wrapper over `ralphy workspace eval <project>` (#469): score one project against its WORKSPACE's CUSTOM rubric (#468 config), surface the per-criterion scorecard, and hand failing criteria to the repair loop. The runner writes `workspace-eval.json` + `workspace-eval-report.md` (append-only) — deterministic criteria run in code, vision criteria in ONE deep-vision pass folding in the workspace STYLE_LOCK + benchmarks. The `overall.verdict` uses the #427 readiness vocab (ship | repair | needs-user-decision | blocked). Pairs with `/evaluator` (the built-in structural / audio / caption gates) and `/fixer` (repair) — this one runs the per-workspace universe rubric, NOT the generic gates. USE WHEN the user says "score this against the workspace rubric", "run the custom evaluator", "workspace eval", "check it against the universe's criteria", "run my universe rubric on <project>", "does this pass the workspace's bar", or has an active workspace with an `evaluators.json` rubric and wants a standalone score (outside the four-stage `/universe-studio` flow). TRIGGER (EN): "workspace eval", "run the universe rubric", "score against the workspace rubric", "run the custom evaluator", "check against the universe's criteria", "does it pass the workspace bar". See body for ALSO FIRE / DO NOT FIRE / HARD INVARIANTS.
Thin agent-facing wrapper over ralphy workspace eval <project> (469): score one project against its WORKSPACE's CUSTOM rubric (468 config), surface the…
As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
The same skill appears in 1 more place: ralphy
How to improve
- Shorten the description to 1024 characters.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1336 chars, limit 1024 - note
frontmatter-keyunknown frontmatter key "namespace"
Process rating: all ten parameters 57/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 5 mutating operations with no state check
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 21 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1162 tokens
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 1336: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 12 example trigger phrases
- +4Structure: 9 headings
- +3Step-by-step instructions: 21 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.