reviewing-findings

reviewing-findings is a skill for Claude Code from prajapatimehul/claude-aws-cost-saver. It costs 75 tokens per session (1,947 once invoked), scanned A, original, MIT.

An AWS cost-finding reviewer that checks entries in a findings.json file and adjusts their confidence based on resource details and operating context.

In plain words
What is it for?
Use it after an AWS cost scan to verify resources, recommendations, usage, savings calculations, and cases such as disaster recovery or infrastructure managed as code.
Why use it?
It helps remove false alarms and unsupported savings suggestions before they reach a report.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: positional $N argument.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the aws-cost-saver plugin — 2 skills, 1 command, 1 agent, 1 hook, 1 MCP server shipped together

Good fit Use it after an AWS cost scan to verify resources, recommendations, usage, savings calculations, and cases such as disaster recovery or infrastructure managed as code.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add prajapatimehul/claude-aws-cost-saver
Claude Code
/plugin install aws-cost-saver

Made for: Claude Code.

Or install aws-cost-saver, the plugin that ships this one along with the rest of its 2 skills, 1 command, 1 agent, 1 hook, 1 MCP server.

Wrote 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.

agentmods badge for reviewing-findings

README.md
[![agentmods](https://agentmods.dev/badge/skills/prajapatimehul/claude-aws-cost-saver/reviewing-findings/github.svg)](https://agentmods.dev/skills/prajapatimehul/claude-aws-cost-saver/reviewing-findings)
Your own site
<a href="https://agentmods.dev/skills/prajapatimehul/claude-aws-cost-saver/reviewing-findings"><img src="https://agentmods.dev/badge/skills/prajapatimehul/claude-aws-cost-saver/reviewing-findings/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.

agentmods 80×15 button for reviewing-findings

Your own site · 80×15
<a href="https://agentmods.dev/skills/prajapatimehul/claude-aws-cost-saver/reviewing-findings"><img src="https://agentmods.dev/badge/skills/prajapatimehul/claude-aws-cost-saver/reviewing-findings.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,947 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00075 $0.01947
Opus 5 $0.00037 $0.00974
Sonnet 5 $0.00015 $0.00389
Haiku 4.5 $0.00007 $0.00195

Measured 12d ago against content hash 37287de2352d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

reviewing-findings 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 12d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/review_findings.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

plugins/aws-cost-saver/skills/reviewing-findings/SKILL.md · 296 lines

How it starts

The opening of the file, as written. The whole thing — 296 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Reviewing AWS Cost Findings

Multi-perspective review of cost optimization findings with confidence-based filtering.

Quick Start

# Review findings and update findings.json in place
python3 "${CLAUDE_PLUGIN_ROOT}/skills/reviewing-findings/scripts/review_findings.py" findings.json --profile your-profile

# Re-review findings that already carry a review_status
python3 "${CLAUDE_PLUGIN_ROOT}/skills/reviewing-findings/scripts/review_findings.py" findings.json --force

For the detailed per-check confidence matrices and false-positive patterns, read REVIEW_CRITERIA.md in this skill's directory.

Review Process

1. Pre-flight Checks

Skip review if:

  • No findings.json exists
  • Findings already reviewed (has review_status)
  • Empty findings array

2. Multi-Agent Review (4 Parallel Agents)

Launch 4 independent review agents:

Agent #1: Resource Verification
├── Verify resource still exists
├── Check current utilization metrics
└── Confirm finding is still valid

Agent #2: Recommendation Quality
├── Validate recommendation is actionable
├── Check for edge cases (ASG, DR, scheduled)
└── Verify savings calculation logic

Agent #3: Business Context
├── Identify environment (prod/dev/staging)
├── Check for dependencies
└── Flag potential risks

Agent #4: Historical Pattern
├── Check for burst patterns
├── Identify seasonal usage
└── Review recent changes

3. Confidence Scoring

Each agent assigns confidence (0-100):

Score Meaning
90-100 Definite savings - act immediately
70-89 High confidence - safe to implement
50-69 Medium confidence - needs validation
25-49 Low confidence - likely false positive
0-24 Skip - insufficient evidence

Filter threshold: 50 (adjustable)

4. Update Findings

Add review metadata to each finding:

{
  "check_id": "EC2-001",
  "monthly_savings": 150.00,
  "review_status": {
    "reviewed_at": "2026-01-19T15:00:00Z",
    "final_confidence": 85,
    "agents": {
      "resource_verification": 90,
      "recommendation_quality": 80,
      "business_context": 85,
      "historical_pattern": 85
    },
    "action": "approved",
    "notes": "Resource verified idle for 21 days"
  }
}

Read the full file on GitHub · 296 lines

Files

What ships with it

2 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.

Changes

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.

  1. 12d ago First seen · 296 lines · 75 tokens per session scan A 37287de2352d

Subscribe to this mod's changes

reviewing-findings is a skill published in the GitHub repository prajapatimehul/claude-aws-cost-saver (22 stars, last pushed 2mo ago), licensed MIT. It adds 75 tokens to every session and 1,947 once invoked, about $0.0004 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 2026-08-30.

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