# code_review_depth_optimizer

As a CTO, this tool analyzes your team's historical DORA metrics (deployment frequency, lead time, MTTR, change failure rate) and GitHub pull request data to recommend an optimal code review depth. Input your repository identifier and time range, and receive a structured recommendation on review rigor (light, standard, thorough) with supporting metrics and risk-adjusted rationale.

Agent View of the PolicyLayer registry record for `code_review_depth_optimizer`. HTML page: https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/code-review-depth-optimizer

## Facts

- Tool: `code_review_depth_optimizer`
- Server: Mcp Knowledge (`https://mcp.gapup.io`) — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge.md
- Homepage: https://github.com/getgapup/gapup-mcp
- Risk category: Read (Low risk)
- Registry record: grade F, identity unverified
- Server auth posture: open
- Server rate-limited: no
- Parameters: 5 (2 required)
- Recommended policy verdict: Allowed

## Parameters

| Parameter | Type | Required | Description |
| --- | --- | --- | --- |
| `async` | boolean | no | If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti |
| `teamSize` | number | no | Number of active developers in the team |
| `repository` | string | yes | GitHub repository identifier in format owner/repo |
| `riskTolerance` | string | no | Organization's risk tolerance level |
| `timeRangeDays` | number | yes | Number of days of historical data to analyze |

Parameters from the server's own tool schema.

## Example call (MCP tools/call, JSON-RPC 2.0)

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "code_review_depth_optimizer",
    "arguments": {
      "repository": "<repository>",
      "timeRangeDays": 0
    }
  }
}
```

## Why code_review_depth_optimizer is rated Low

The tool reads and analyzes historical metrics and PR data to produce recommendations. There are no write, execute, destructive, or financial side effects described — it only retrieves data and returns structured analysis/recommendations.

From the tool's own definition: "analyzes your team's historical DORA metrics...and GitHub pull request data to recommend an optimal code review depth...receive a structured recommendation"

## Use case

AI agents call code_review_depth_optimizer to retrieve information from Mcp Knowledge without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

## Recommended policy (PolicyLayer)

Verdict: **Allowed**. Enforced by the PolicyLayer MCP gateway (https://policylayer.com/mcp-gateway) before a call reaches Mcp Knowledge:

```json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "code_review_depth_optimizer": {}
  }
}
```

## Other tools on Mcp Knowledge (270)

- `adversarial_input_stress_tester` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/adversarial-input-stress-tester.md
- `competitor_pricing_scrape` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/competitor-pricing-scrape.md
- `dora_operational_resilience_stress_tes` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/dora-operational-resilience-stress-tes.md
- `financial_model_3statement` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/financial-model-3statement.md
- `gl_reconciler` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/gl-reconciler.md
- `lgpd_data_subject_rights_automator` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/lgpd-data-subject-rights-automator.md
- `monte_carlo_portfolio` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/monte-carlo-portfolio.md
- `workflow_orchestrator` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/workflow-orchestrator.md
- `ma_arbitrage_hunter` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ma-arbitrage-hunter.md
- `repo_rate_arbitrage_scanner` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/repo-rate-arbitrage-scanner.md
- `tax_optimization` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/tax-optimization.md
- `treasury_optimizer` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/treasury-optimizer.md
- `usdc_x402_payments_intel` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/usdc-x402-payments-intel.md
- `working_capital_fx_hedge_optimizer` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/working-capital-fx-hedge-optimizer.md
- `pricing_in_deal` — Other — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/pricing-in-deal.md
- `term_sheet_negotiation` — Other — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/term-sheet-negotiation.md
- `abm_architect` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/abm-architect.md
- `abm_lookalike_account_finder` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/abm-lookalike-account-finder.md
- `account_expansion_mapper` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/account-expansion-mapper.md
- `affiliate_fraud_clickstream_detector` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/affiliate-fraud-clickstream-detector.md
- `africa_trade_barrier_breaker` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/africa-trade-barrier-breaker.md
- `africa_trade_finance_esg_rater` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/africa-trade-finance-esg-rater.md
- `africa_trade_preference_arbitrage` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/africa-trade-preference-arbitrage.md
- `africa_trade_preference_optimizer` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/africa-trade-preference-optimizer.md
- `agoa_eba_intelligence` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/agoa-eba-intelligence.md
- `ai_act_sandbox_regulatory_sandbox` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ai-act-sandbox-regulatory-sandbox.md
- `ai_act_training_data_audit` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ai-act-training-data-audit.md
- `ai_governance_full_report_async` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ai-governance-full-report-async.md
- `ai_governance_full_report_result` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ai-governance-full-report-result.md
- `ai_governance_pilot` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ai-governance-pilot.md
- …and 240 more: https://policylayer.com/tools/io-github-getgapup-mcp-knowledge.md

## For agents

This record is a snapshot. Live verdicts and the full registry:

- Check every server in your MCP config at once: `npx -y policylayer stack`
- Vet a server before you add it: install the mcp-precheck skill — `npx skills add https://policylayer.com` (skill text: https://policylayer.com/skill.md)
- Query the registry over MCP: endpoint `https://api.policylayer.com/mcp` — tools `check_mcp_server`, `check_mcp_stack`, `check_tool`, `search_registry`, `get_change_events`

---

Source: the PolicyLayer MCP registry — one continuously verified record per MCP server. Full record: https://policylayer.com/registry?q=io-github-getgapup-mcp-knowledge · API: https://policylayer.com/registry/api · Policy library: https://policylayer.com/policies/io-github-getgapup-mcp-knowledge