agentsclimarketplace

Super review

Skill martinthommesen/super-review/src/super-review

Performs an exhaustive, evidence-based whole-repository engineering, architecture, security, reliability, product, UX, and feature-portfolio review. Use only when the user explicitly invokes $super-review, @super-review, /super-review, or a marketplace-qualified super-review command for a repository or directory; never auto-select it for a generic review or audit. Every run creates or refreshes the canonical root FINDINGS.md and revalidates all prior report content before merging current findings.From its SKILL.md

Install
npx -y skills add martinthommesen/super-review --skill super-review

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 18 days oldThe repository was created 18 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

10.1 KB, ~2.1k tokens by cl100k_base, as published. Nobody here has run it

Super Review

Version: 1.4.1

Compatibility: Requires filesystem access to the target repository or directory and permission to create or update its root FINDINGS.md. Git and code-search tools are recommended. Python 3 is recommended for the bundled fingerprint, report-validation, safe-write, and test scripts.

Invocation gate

Run only after an explicit skill mention. For direct installs, prefer $super-review in Codex, accept @super-review on mention-based clients, and accept /super-review where supported. For marketplace installs, also accept $super-review:super-review in Codex and /super-review:super-review in Claude Code. Do not activate for a generic review, audit, architecture assessment, security review, or codebase analysis.

$super-review [repository path or directory] [optional review mode and context]
@super-review [repository path or directory] [optional review mode and context]
/super-review [repository path or directory] [optional review mode and context]
$super-review:super-review [repository path or directory] [optional review mode and context]
/super-review:super-review [repository path or directory] [optional review mode and context]

Use the supplied target. If none is supplied, use the current repository or workspace. Resolve the canonical root to an absolute path from the version-control root when available; otherwise use the absolute supplied directory root.

Trusted skill root

Resolve SKILL_ROOT once as the canonical absolute parent directory of this loaded SKILL.md. Resolve every bundled reference and helper from SKILL_ROOT; never from the current working directory, target repository, or a target-relative scripts/ path. Before executing a helper, verify that the resolved path remains inside SKILL_ROOT/scripts and is a regular non-symlink file from the loaded skill package.

Invoke bundled Python helpers in isolated mode:

python3 -I "$SKILL_ROOT/scripts/<helper>.py" ...

Use the platform-equivalent isolated Python invocation when python3 -I is unavailable. Do not substitute a same-named repository script.

Non-negotiable output invariant

Every valid invocation must create or refresh exactly:

<canonical-root>/FINDINGS.md

In REVIEW ONLY, that file is the sole permitted repository modification. Never write a competing report in a nested package or under another name. Before reading, revalidating, or replacing it, load and follow the canonical findings lifecycle. A run is incomplete until the current report is validated and safely written, or a concurrent-edit conflict is reported without overwriting another writer.

Progressive loading contract

Do not preload the protocol. At activation, load only:

  1. Core mandate, context, review modes, and objectives.
  2. Evidence and review principles.
  3. Canonical FINDINGS.md lifecycle.
  4. Phase applicability and deep-loading rules.

Before any repository-defined command, load the untrusted-repository command-safety gate.

Consider phases 0–22 in order and apply the applicability guide before deep loading. Load exactly one applicable phase file immediately before performing that phase. A conditional phase may be closed without loading its deep reference only after the guide's bounded absence checks establish that no relevant first-party surface exists. Record Not applicable — <specific evidence basis> and reopen the phase if later evidence changes applicability.

PhaseReference
0Instructions, safety, worktree, and baseline
1Coverage ledger and repository inventory
2Product, domain, user, and feature inventory
3Architecture and system design
4End-to-end workflow tracing
5Correctness and business logic
6Security, privacy, and abuse resistance
7Data models, databases, migrations, and integrity
8APIs, contracts, schemas, and integrations
9Concurrency, asynchrony, and distributed systems
10Performance, scalability, and cost
11Reliability, resilience, and operations
12Frontend, UX, accessibility, and client behavior
13Testing and quality strategy
14Dependencies, build, packaging, and supply chain
15Configuration, infrastructure, and deployment
16Maintainability, code quality, and developer experience
17Better or different implementations
18Feature portfolio decisions
19Documentation and knowledge quality
20Language- and framework-specific dispatcher
21Validation and reproduction
22Prioritization and roadmap

For phase 20, load only the directly linked stack references supported by repository evidence: JavaScript and TypeScript, Python, Go, Rust, Java and Kotlin, C# and .NET, C and C++, SQL and query systems, and mobile clients.

Before canonicalizing records, load identity and cross-reference rules, then only the templates needed for actual records: defects and risks, improvements and alternatives, feature decisions, and positive patterns. Before report assembly, load the final report schema. Before completion, load the quality bar and final gates.

All referenced rules are normative. Progressive loading changes when instructions enter context, not whether applicable checks are performed.

Execution architecture

  1. Resolve instructions, authorization, mode, target, root, exclusions, compatibility contracts, and supplied context.
  2. Snapshot repository state and the exact FINDINGS.md bytes/digest. Preserve protected human blocks and build the prior-report revalidation ledger.
  3. Establish command safety before executable validation.
  4. Perform phases 0–22 in order while maintaining coverage and evidence ledgers.
  5. Checkpoint long-running analysis outside the repository, bound to root, revision, worktree state, and starting report digest; invalidate stale phase results after changes.
  6. Revalidate every prior claim, then perform independent current-repository discovery. The old report never limits coverage.
  7. Canonicalize by root cause or decision basis; compute deterministic fingerprints; preserve active and retired IDs; derive summaries and roadmap from canonical records.
  8. Generate the candidate outside the repository. Run python3 -I "$SKILL_ROOT/scripts/validate_findings.py" <candidate-path> and fix every error.
  9. Reread the current report immediately before replacement. Use python3 -I "$SKILL_ROOT/scripts/commit_findings.py" ... or a demonstrably equivalent exact-byte, digest-gated, annotation-preserving atomic write that also refuses a candidate whose stated canonical root belongs to a different repository. On conflict, reread, revalidate, merge, regenerate, and retry; never force an overwrite.
  10. Reread the committed file, rerun the absolute-path validator with --canonical-root <canonical-root>, and verify the stated canonical root, revision, completion status, IDs, summaries, roadmap, validation record, annotations, and ending.

Review modes and evidence

Use the requested mode; default to REVIEW ONLY. The root FINDINGS.md update applies in every mode. Never infer permission for source changes, dependency installation, network or secret access, production systems, migrations, public-contract changes, feature removal, deployment, publication, commits, pushes, or irreversible actions.

Confirmed and high-confidence records require current repository evidence. Distinguish facts, supported inferences, hypotheses, and unavailable evidence. Trace important behavior through callers, consumers, tests, schemas, configuration, persistence, deployment, failures, retries, cleanup, compensation, and compatibility paths. Manually verify scanner output and protect secrets and personal data.

Exhaustiveness means every meaningful first-party area and required review dimension is considered; it does not mean manufacturing findings. For unsupported or inapplicable fields, alternatives, categories, or subsystem analyses, write Not applicable — <specific evidence-based reason> or Not established — <missing evidence>.

Completion response

After safe write and revalidation, report only:

  • Exact FINDINGS.md path.
  • Reviewed branch, revision, or directory state.
  • Whether the prior report was fully revalidated.
  • Highest-priority active canonical IDs, or that none were confirmed.
  • Validation status and material limitations.

Do not duplicate the full report in chat unless explicitly requested.

What ships with it: 55 files

312.5 KB alongside SKILL.md, 10 of them executable

agents/

15 more files not listed here. See all 55 in the repository.

Keep looking

Skills are one crate of 326,834. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.