Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/alecs5am/ralphy/workspace-evalnpx skills add alecs5am/ralphy --skill workspace-evalgit clone --depth 1 https://github.com/alecs5am/ralphyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/alecs5am/ralphy/workspace-eval)<a href="https://agentmods.dev/skills/alecs5am/ralphy/workspace-eval"><img src="https://agentmods.dev/badge/skills/alecs5am/ralphy/workspace-eval.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00303 | $0.01490 |
| Opus 5 | $0.00151 | $0.00745 |
| Sonnet 5 | $0.00061 | $0.00298 |
| Haiku 4.5 | $0.00030 | $0.00149 |
Grade A, and why
workspace-eval scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
workspace-eval — run the universe rubric
A thin wrapper over the #469 runner. Your input is a project id + its workspace's custom rubric; your output is the per-criterion scorecard plus, on a non-clean verdict, a handoff to repair. The engine is ralphy workspace eval — this skill is only the agent-facing surface.
ALSO FIRE
- After a render, when the user wants a standalone score against the universe's bar without running the full four-stage
/universe-studioorchestrator. - When the user drops a
<project>and asks whether it clears the workspace's own criteria (distinct from the generic/evaluatorgates).
DO NOT FIRE
- For the generic structural / audio / caption / vision gates on an arbitrary mp4 — that is
/evaluator. This skill scores against the per-workspace CUSTOM rubric. - For applying fixes — that is
/fixer/ the repair loop (#409). This skill only produces the scorecard and routes failures onward. - For a workspace WITHOUT an
evaluators.jsonrubric — there are no custom criteria to score; the runner reports "no rubric configured". Route to/evaluatorfor the built-in gates instead. - As the per-stage gate inside the four-stage flow — that is
/universe-studio, which drives this same runner per stage.
HARD INVARIANTS
Inherited from AGENTS.md:
ralphyis the only entry-point. Run the eval throughralphy workspace eval— never call the model or probe the mp4 directly.- Append-only. The runner archives any existing
workspace-eval.json/workspace-eval-report.mdto.vNbefore writing the fresh one; never--force-overwritewithout the user asking. - Read
MODELS.mdbefore overriding the vision model (--model).
Run it
ralphy workspace eval <project>
Flags:
--no-vision— deterministic criteria only, NO model call (a free pass; use it to check the code-checked criteria without spending).--model <id>— override the deep-vision model (defaultgoogle/gemini-3.1-pro-preview; checkMODELS.mdfirst).--workspace <slug>— score against a different workspace's rubric (default: the project's registered workspace).--video <path>— override the scored video (default<project>/render/final.mp4).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 76 lines · 303 tokens per session scan A 6f6947a62e4c
workspace-eval is a skill published in the GitHub repository alecs5am/ralphy (129 stars, last pushed 10d ago), licensed Apache-2.0. It adds 303 tokens to every session and 1,490 once invoked, about $0.0015 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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