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 skills add coroboros/agent-skills --skill code-ultrareviewgit clone --depth 1 https://github.com/coroboros/agent-skillsWrote 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/coroboros/agent-skills/code-ultrareview)<a href="https://agentmods.dev/skills/coroboros/agent-skills/code-ultrareview"><img src="https://agentmods.dev/badge/skills/coroboros/agent-skills/code-ultrareview.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 5.1 | $0.00207 | $0.03901 |
| Opus 5 | $0.00103 | $0.01951 |
| Sonnet 5 | $0.00041 | $0.00780 |
| Haiku 4.5 | $0.00021 | $0.00390 |
Grade A, and why
code-ultrareview 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 4d 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 — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code ultrareview
Critical — Adversarial verification
These rules govern how this skill trusts its own output — apply them whenever it verifies a claim, a defect, a source, or a decision before acting on it.
- Refute by default. Treat each non-trivial finding as unproven until a fresh-context check fails to refute it — the context that produced a claim cannot reliably clear it.
- No silent drop. Every finding flips the conclusion, is refuted in writing, or is filed as a risk or open question. A finding that vanishes without a verdict is a defect.
- Don't re-litigate settled facts. Spend adversarial effort on load-bearing or contested claims; let established facts pass. Over-refutation manufactures false doubt — it does not add rigor.
- Stay selective and cost-aware. Scale verification to the stakes; reversible, low-impact work gets a light touch, not a full adversarial sweep.
- Concede only to a strong rebuttal. A weak counter folds into the finding or gets filed; it does not overturn it.
Important — Engineering discipline
These rules govern how this skill changes code — apply them whenever it writes, edits, or proposes a fix.
- Minimal scope. Only what's directly requested or clearly necessary — no extra files, no abstraction for one use, no configurability nobody asked for, no error handling for states that can't happen. Validate at system boundaries; trust internal code.
- General solution, not the test cases. Implement the real logic for all valid inputs; never hard-code to inputs or bolt on workaround scripts to make a test pass. Tests verify the solution; they don't define it. A test is wrong? Say so — don't bend correct code to a broken test.
- Investigate before claiming. Never speculate about code you haven't opened; read the referenced file before answering. Ground every claim in what you actually read, not a plausible guess.
What ships with it
57 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- evals/evals.json 32 KB
- references/anthropic-verbatim.md 6.4 KB
- references/axes-overview.md 4.7 KB
- references/axes/coherence.md 11 KB
- references/axes/correctness.md 4.0 KB
- references/axes/design-api.md 5.0 KB
- references/axes/documentation.md 10 KB
- references/axes/intent.md 4.5 KB
- references/axes/performance.md 3.6 KB
- references/axes/simplification.md 4.4 KB
- references/axes/style.md 3.7 KB
- references/axes/tests.md 4.4 KB
- references/markdownlint-base.markdownlint-cli2.jsonc 130 B
- references/orchestration.md 9.6 KB
- references/perf-rules/n-plus-one-sequelize.yml 944 B
- references/perf-rules/n-plus-one-sqlalchemy.yml 975 B
- references/perf-rules/sync-io-async-py.yml 1.0 KB
- references/pipeline.md 6.7 KB
- references/ultra-execution.md 16 KB
- scripts/apply_safe/__init__.py 385 B runs code
- scripts/apply_safe/_common.py 1.0 KB runs code
- scripts/apply_safe/description_sync.py 5.6 KB runs code
- scripts/apply_safe/failing_test_writer.py 4.5 KB runs code
- scripts/apply_safe/version_sync.py 4.6 KB runs code
- scripts/axis_dispatch.py 29 KB runs code
- scripts/battery_ingest.py 37 KB runs code
- scripts/build_detect.py 6.0 KB runs code
- scripts/coherence/__init__.py 398 B runs code
- scripts/coherence/_common.py 5.8 KB runs code
- scripts/coherence/capability_graph.py 4.8 KB runs code
- scripts/coherence/cross_reference_graph.py 6.3 KB runs code
- scripts/coherence/description_graph.py 5.3 KB runs code
- scripts/coherence/example_graph.py 3.8 KB runs code
- scripts/coherence/run.py 3.0 KB runs code
- scripts/coherence/spec_conformance_graph.py 3.0 KB runs code
- scripts/coherence/version_graph.py 5.7 KB runs code
- scripts/derivation/__init__.py 393 B runs code
- scripts/derivation/_common.py 7.2 KB runs code
- scripts/derivation/auto_detect.py 6.6 KB runs code
- scripts/derivation/extractor.py 4.6 KB runs code
- scripts/derivation/run.py 15 KB runs code
- scripts/fetch_commits.sh 2.3 KB runs code
- scripts/fetch_pr_meta.sh 2.4 KB runs code
- scripts/findings_to_jsonl.py 9.7 KB runs code
- scripts/manifest.py 7.0 KB runs code
- scripts/preflight_tools.sh 3.5 KB runs code
- scripts/process_timeout.py 5.2 KB runs code
- scripts/resolve_base.sh 4.5 KB runs code
- scripts/run_battery.sh 42 KB runs code
- scripts/run_build_verify.py 17 KB runs code
- scripts/run_mutation.py 19 KB runs code
- scripts/run_validators.py 31 KB runs code
- scripts/scope.py 23 KB runs code
- scripts/synthesis_core.py 12 KB runs code
- scripts/synthesize.py 31 KB runs code
- scripts/tool_runtime.py 8.3 KB runs code
- templates/code-ultrareview.md 6.0 KB
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.
- 4d ago Changed 5a8e3143c4fe
- 7d ago First seen · 153 lines · 207 tokens per session scan A c58000199d3f
code-ultrareview is a skill published in the GitHub repository coroboros/agent-skills (4 stars, last pushed yesterday), licensed MIT. It adds 207 tokens to every session and 3,901 once invoked, about $0.0010 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
verify-implementation
A workflow that runs a project’s verification skills to produce a report on coding patterns, architecture rules, and project conventions. It is intended for work after implementation, before a pull request, or during code review.
review-loop
Run the adversarial verification loop — implement, then hand the change to a fresh checker that did not write it, fix what it finds, and re-dispatch until APPROVE. Use before claiming any behavioural change is done, and on requests like "review loop", "adversarial review", "independent review", "get this verified"…
frontend-code-review
Trigger when the user requests a review of frontend files (e.g., .tsx, .ts, .js). Support both pending-change reviews and focused file reviews while applying the checklist rules.
no-mistakes
Validate committed feature-branch changes through the no-mistakes pipeline: intent, rebase, review, test, docs, lint, push, PR, and CI. Use when the user asks to run no-mistakes, ship safely, validate before pushing, or gate a change before it reaches upstream.
ai-slop-cleaner
Post-implementation cleanup that removes AI-generated bloat while preserving functionality. Runs pass-by-pass with test verification after each pass. Activate after kraken/spark complete a feature, or when a codebase needs hygiene work.
coding-standards
Universal coding standards - naming, formatting, error handling, immutability, SOLID principles.