AgentStack
Browse Sign in
Browse Why AgentStack Sell Docs
Sign in
SKILL verified MIT Self-run

Cross Review

skill-eliasoulkadi-shokunin-cross-review · by EliasOulkadi

Delegate code review to a subagent running a specific model. Use ONLY when user explicitly names a model to review changes ("review with opus", "use sonnet to review", "review with gemini"). The root agent reconstructs changes from conversation history and spawns a subagent with the code-review skill using the specified model. Do NOT use for general code review (use code-review skill instead), fo…

No reviews yet
0 installs
31 views
0.0% view→install

Install

$ agentstack add skill-eliasoulkadi-shokunin-cross-review

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution Used
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

Verified badge

Passed review? Show it. Paste this badge into your README, it links to the public security report.

AgentStack Verified badge Links to your public security report.
[![AgentStack Verified](https://agentstack.voostack.com/badges/verified.svg)](https://agentstack.voostack.com/security/report/skill-eliasoulkadi-shokunin-cross-review)

Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
3mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
Are you the author of Cross Review? Claim this listing to set pricing, connect Stripe payouts, and keep 70% of every sale.
Sign up to claim

About

Reconstruct what you changed during this conversation, then delegate the actual review to a single subagent running the code-review skill with a user-specified model.

IMPORTANT: Steps 1-2 run in the current agent (the master). Only Step 3 spawns a subagent.

Workflow

Step 1: Parse the user request

Extract:

  • Model: The model ID from user's request. Validate against available models.
  • Review instructions: Any text after "Review instructions:" — pass verbatim.
  • Change scope: What should be reviewed. Default: all changes in this conversation.

Step 2: Gather context from your own changes

Reconstruct the diff from conversation history:

  1. Compose a unified diff of all changes (Edit, Write, Bash, etc.). Group by file.
  • If no changes: Inform user and stop.
  1. Read final state of changed files for surrounding context.
  1. Check related context:
  • Test files related to changed files (skip node_modules, .git, dist, build)
  • Config changes that affect behavior
  • Related type definitions or interfaces

Do NOT show gathered context to user. Use only for the subagent.

Step 3: Spawn the review subagent

spawn_subagent:
  skill: "code-review"
  model: 
  prompt: |
    Review the changes below using "code-review" skill.

    CONSTRAINTS:
    - Read-only review. Do NOT edit files.
    - All context is provided below. Read files only if clearly incomplete.
    - Review independently and objectively.

    ## Review Instructions
    {user's review instructions, verbatim}

    ## Changes
    {reconstructed diff, grouped by file}

    ## Additional Context
    {links to related files, tests, type definitions, requirements}

Step 4: Relay the result — READ-ONLY, NO ACTIONS

CRITICAL: Output the subagent's review AS-IS. Do NOT:

  • Summarize, rephrase, reorder, or filter
  • Fix, improve, or refactor based on findings
  • Add your own commentary or caveats

One-line model attribution is acceptable. You may offer to implement recommendations, but let the user decide.

Model Mapping

When user says "review with [model name]", map to a valid model ID:

| User says | Model ID | |-----------|----------| | opus, claude opus | claude-3-opus | | sonnet, claude sonnet | claude-3.5-sonnet | | gpt-4, gpt4 | gpt-4 | | gpt-4o | gpt-4o | | gemini | gemini-2.0-flash | | deepseek | deepseek-chat |

If the model name is unrecognized, ask for the exact model ID.

Error Handling

  • Subagent fails or times out: Inform user. Suggest retry or different model.
  • No changes in conversation: Inform user and stop.
  • Incomplete review: Relay what was returned. Note it may be incomplete.
  • Model not available: Offer alternative from the mapping table.
  • User requests unknown model: Map fuzzy names to model IDs using the mapping table. If no match, ask user to provide the exact model ID string.
  • Subagent returns malformed output: The review subagent may return text instead of structured findings. Relay what was returned and note the format deviation.
  • Diff context exceeds subagent limits: For very large changesets, split the diff by file or module and run multiple sequential subagent reviews. Inform user you are splitting the review.
  • Network or infrastructure failure during spawn: Retry once with the same configuration. If it fails again, offer to switch to a different model or perform the review inline.
  • Subagent produces factually incorrect findings: Relay findings as-is but append a note that some claims could not be verified against the codebase. Do not filter or censor.

Anti-Patterns

| Pattern | Problem | Fix | |---------|---------|-----| | Using cross-review for general PR review | User did not name a model. cross-review is for explicit model-named delegation only. | Use the standard code-review skill instead. | | Summarizing or filtering subagent output | The user requested an independent review. Any distortion defeats the purpose. | Relay output verbatim. Add only a 1-line model attribution. | | Acting on findings without user approval | The master agent is read-only in this workflow. Fixing issues automatically breaks the delegation contract. | Offer to implement recommendations but wait for user to decide. | | Skipping context gathering (Step 2) | Sending only the diff without file context produces shallow reviews that miss type errors and behavioral changes. | Always read final file state and related test/config files before spawning the subagent. | | Delegating to the same model the user is already talking to | If user says "review with sonnet" and master agent IS sonnet, this is circular. | Use a different model than the one running the master agent. | | Requesting review of unchanged code | cross-review only works on changes made in the current conversation. | If the user wants PR review from git, use the code-review skill directly. |

Model Comparison Methodology

When to use which model

| Model | Strengths | Best for | |-------|-----------|----------| | Claude Opus 4 | Deep reasoning, security analysis, architectural review | Complex refactors, auth code | | GPT-5 Codex | Code generation patterns, syntax accuracy | Implementation review, template checking | | Gemini 2.5 Pro | Multi-modal, context window size | Large PRs (200+ files), full-repo context | | DeepSeek V4 | Fast, cost-effective, strong at bug detection | Routine PRs, quick checks |

Confidence Scoring

Assign confidence (0.0-1.0) to each finding:

confidence = (models_agreeing / total_models) * evidence_score

evidence_score:
  1.0 = exact line + code excerpt proves the bug
  0.7 = logic analysis suggests probable issue
  0.4 = speculative (pattern matching without code walk)
  0.1 = style preference

Findings with confidence keep clearest description

Handling Conflicts

When models disagree:

  • Don't default to majority -- investigate the code yourself
  • The dissenting model may have caught something the others missed
  • Present both views: "Claude suggests X, Gemini suggests Y"
  • Let the human reviewer decide

Checklist

  • [ ] Valid model name passed (not an alias or unsupported ID)
  • [ ] Diff or context reconstructed accurately from conversation history
  • [ ] Subagent has the code-review skill loaded
  • [ ] Review result captured from subagent output (not assumed)
  • [ ] Fallback model specified if primary model is unavailable

Sources

  • MCP Protocol specification (modelcontextprotocol.io) — subprocess agent spawning and message passing
  • OpenAI API model list documentation (platform.openai.com/docs/models) — supported model IDs and capabilities
  • Anthropic Claude model documentation (docs.anthropic.com/en/docs/about-claude/models) — model IDs and feature comparison
  • Google Gemini API model documentation (ai.google.dev/models/gemini) — Gemini model identifiers and rate limits
  • DeepSeek API documentation (platform.deepseek.com/api-docs) — model IDs and context window limits
  • Conventional Comments specification (conventionalcomments.org) — structured review comment formatting
  • "Software Engineering at Google" by Titus Winters, Tom Manshreck, Hyrum Wright (O'Reilly, 2020) — code review best practices at scale

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

No reviews yet, be the first.

Versions

  • v0.1.0 Imported from the upstream source.