Borrowing it
Nothing to install: this file belongs to otis22/vetmanager-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/otis22/vetmanager-mcp/main/.codex/skills/super-review/SKILL.mdgit clone --depth 1 https://github.com/otis22/vetmanager-mcpWrote 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/otis22/vetmanager-mcp/super-review)<a href="https://agentmods.dev/skills/otis22/vetmanager-mcp/super-review"><img src="https://agentmods.dev/badge/skills/otis22/vetmanager-mcp/super-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/otis22/vetmanager-mcp/super-review"><img src="https://agentmods.dev/badge/skills/otis22/vetmanager-mcp/super-review.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00044 | $0.02826 |
| Opus 5 | $0.00022 | $0.01413 |
| Sonnet 5 | $0.00009 | $0.00565 |
| Haiku 4.5 | $0.00004 | $0.00283 |
Grade A, and why
super-review 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 10d 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 — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Super Review
Use this skill when the user asks for super-review, deep review, multi-agent review, review arbitration, Spark scout review, or cross-model review in this repository.
Contract
Use the same review protocol as .claude/commands/super-review.md, but adapt runtime-specific steps to Codex tools:
- scopes:
changeddefault,related,full,stage:N - flags:
--no-spark,--no-arbitration - output report:
artifacts/review/{YYYY-MM-DD}-{scope_slug}-stage-{N}.md - dismissed memory: append to
artifacts/review/inadequate-findings-index.md - findings schema: YAML items with
severity,reviewer,category,file,lines,problem,why_it_matters,suggested_fix,confidence
If the Claude command and this skill differ, prefer it only for shared review policy: scopes, model matrix, finding schema, report format, adequacy rules, and cross-CLI arbitration contract. Do not copy Claude-only mechanics such as .claude/agents/*, Agent tool-calls, or Claude command syntax into Codex execution.
Model Routing
Spark/GPT side:
gpt-5.3-codex-spark: scout/prepass only. Treat output as untrusted leads.gpt-5.4-miniorgpt-5.3-codex-spark: code/docs/tests candidate mining.gpt-5.4: observability and normal validation.gpt-5.5: security, architecture, product, hard disputes, and GPT-side aggregation if needed.
Claude side:
opus: external arbitration from Codex runtime; security/architecture/product/aggregator quality bar.sonnet: fallback external arbitration and routine code/docs/tests checks.
Never let Spark decide final severity or merge verdict.
Use the exact model name gpt-5.3-codex-spark. The shorter name gpt-5.3-spark is incomplete and must not be used.
Runtime Defaults And Fallbacks
Use these defaults when shelling out from Codex:
- Per reviewer/scout command timeout: 1200 seconds.
- External arbitration timeout: 900 seconds.
- First attempt sandbox:
-s read-only. - Classify failures before retrying:
- Sandbox/runtime failure: process fails before meaningful file reads due to local execution errors such as
bwrap: loopback: Failed RTM_NEWADDR, sandbox initialization, PTY/session startup, local timeout wrapper issues, or shell/env problems. Retry the same model once with the adjusted runtime settings described below. Do not switch models for these failures. - Model failure: stderr/stdout clearly indicates the requested model is unavailable, unknown, unsupported, denied for the account, capacity-limited, quota-limited, or otherwise rejected by the model provider. Only this class may use the documented fallback model.
- Review-output failure: command ran and read files but returned empty output, malformed YAML, non-findings prose, or a meta runtime error. Do not switch models automatically unless the output itself identifies a model/provider failure; mark the role
skipped_or_failedor rerun the same model once if the failure is obviously transient.
- Sandbox/runtime failure: process fails before meaningful file reads due to local execution errors such as
- If Codex CLI fails before reading files with sandbox/runtime errors such as
bwrap: loopback: Failed RTM_NEWADDR, retry that exact pass once with-s danger-full-accessand a prompt that explicitly says:Review only. Do not edit files. Do not run write commands. - If and only if a model failure is identified, retry once with the documented fallback model and record the fallback in the report header/limitations.
- If a role returns empty output, non-YAML output, or only a meta runtime error, do not silently treat it as "no findings"; mark that role as
skipped_or_failedin the report header and continue with available roles. - Before finalizing, check that no
codex exec/claude -pprocesses from this run are still alive.
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.
- 10d ago First seen · 188 lines · 44 tokens per session scan A 445cc414b7f5
super-review is a skill published in the GitHub repository otis22/vetmanager-mcp (1 stars, last pushed yesterday), licensed MIT. It adds 44 tokens to every session and 2,826 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
api-linter
MCP definition linter rules reference. Use when bun run lint:mcp or bun run devcheck reports a lint error or warning (format-parity, schema-is-object, name-format, server-json-, etc.) and you need to understand the rule, its severity, and how to fix it. Every rule ID the linter emits has an entry in this doc.
release-pr-review
Review pass on an open release PR (release/ → main) — the step between git-wrapup and release-and-publish when a project releases in gated release PR mode. Reads the PR's commit range through the code-simplifier lens plus a correctness review, verifies whatever an automated reviewer left on the PR, lands fixes as…
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code-review
Reviews a supplied code path or diff for correctness, security, maintainability, and style without executing or modifying it.
remarc
Manage Remarc session comments and contextual feedback. Use when the user mentions Remarc sessions, comments, handoff, triage, review, addressing, resolving, status updates, or summaries.
code-review
Review ServiceNow server-side scripts for ES5 violations, ACL/injection/XSS issues, N+1 queries, missing setLimit/error handling, hard-coded sysids, and business-rule recursion risks.